ppxscal/embedding_network huggingface dataset:
Driver Recognition Using Gaussian Mixture Models and Decision Fusion Techniques
Authors: Kristin S. Benli, Remzi Düzagaç, M. Taner Eskil
Venue: Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence (2008)

In this paper we present our research in driver recognition. The goal of this study is to investigate the performance of different classifier fusion techniques in a driver recognition scenario. We are using solely driving behavior signals such as break and accelerator pedal pressure, engine RPM, vehicle speed, steering wheel angle for identifying the driver identities. We modeled each driver using Gaussian Mixture Models, obtained posterior probabilities of identities and combined these scores using different fixed and trainable (adaptive) fusion methods. We observed error rates as low as 0.35% in recognition of 100 drivers using trainable combiners. We conclude that the fusion of multi-modal classifier results is very successful in biometric recognition of a person in a car setting.
A modeling-based classification algorithm validated with simulated data
Authors: Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

We present a Generalized Lotka-Volterra (GLV) based approach for modeling and simulation of supervised inductive learning, and construction of an efficient classification algorithm. The GLV equations, typically used to explain the biological world, are employed to simulate the process of inductive learning. In addition, the modeling approach provides a key advantage over the more conventional constraint and optimization-based classification algorithms, as influences of outliers and local patterns, which can lead to problematic overfitting, are auto-moderated by the model itself. We present the bare-bones algorithm and motivate the model through axiomatic postulates. The algorithm is validated using benchmark simulated datasets, showing results competitive with other cutting-edge algorithms.
Environment Reuse in the WAM
Authors: Bart Demoen, Phuong-Lan Nguyen
Venue: Proceedings of the 24th International Conference on Logic Programming (2008)

The TOAM reuses eagerly allocated stack frames, while the WAM avoids to allocate environments. This is investigated by using the tak/4 benchmark as an inital case study for better understanding what one can expect from environment reuse for deterministic predicates in the WAM. Additionally, artificial programs are used to amplify the findings. The experiment compares the impact of reusing an environment versus avoiding to create it: the latter seems a superior technique.
Output-feedback stabilization techniques for the design of excitation controllers in a power system
Authors: A. K. Boglou, K. G. Arvanitis, D. I. Pappas
Venue: Proceedings of the 8th conference on Systems theory and scientific computation (2008)

In this paper two practical discrete optimal control methods are presented and applied to design suitable excitation controllers for a practical linear discrete power system model and thus enhance in an effective way the dynamic stability characteristics of the actual power system. The first method is a new optimal multirate control (OMCM) technique, whereas the second one is based on the establishment of two necessary and sufficient conditions for stability purposes using output feedback. The obtained relevant simulation results demonstrated clearly the validity, suitability, effectiveness and implementability of the so designed controllers.
Cross layer PHY-MAC protocol for wireless static and mobile ad hoc networks
Authors: Sylwia Romaszko, Chris Blondia
Venue: EURASIP Journal on Advances in Signal Processing (2009)

Multihop mobile wireless networks have drawn a lot of attention in recent years thanks to their wide applicability in civil and military environments. Since the existing IEEE 802.11 distributed coordination function (DCF) standard does not provide satisfactory access to the wireless medium in multihop mobile networks, we have designed a cross-layer protocol, (CroSs-layer noise aware power driven MAC (SNAPdMac)), which consists of two parts. The protocol first concentrates on the flexible adjustment of the upper and lower bounds of the contention window (CW) to lower the number of collisions. In addition, it uses a power control scheme, triggered by the medium access control (MAC) layer, to limit the waste of energy and also to decrease the number of collisions. Thanks to a noticeable energy conservation and decrease of the number of collisions, it prolongs significantly the lifetime of the network and delays the death of the first node while increasing both the throughput performance and the sending bit rate/throughput fairness among contending flows.
Integration of Region and Edge-based information for Efficient Road Extraction from High Resolution Satellite Imagery
Authors: T. T. Mirnalinee, Sukhendu Das, Koshy Varghese
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

In Remote sensing systems one of the most important features needed are roads, which require automated procedures to rapidly identify them from high-resolution satellite imagery, Many approaches for automatic road extraction have appeared in literature [2][7][9], which vary due to the differences in their goals, available information, algorithms used and assumptions about roads. In this paper, we propose an approach for automatic road extraction by integrating region and edge information. The complimentary information of road segments obtained using Probabilistic SVM(PSVM) and road edges obtained using Dominant Singular Measure (DSM) are integrated using a modified Constraint Satisfaction Neural Network -Complementary Information Integration(CSNN-CII) [1] to improve the accuracy of the system. Results are shown on real-world images and quantitatively evaluated with manual hand-drawn road layouts.
Research of Distributed Algorithm Based on Usage Mining
Authors: Qingtian Han, Xiaoyan Gao
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data and traces users' visiting characteristics, and then extracts the users’ using pattern. This article will study on Web Mining Algorithm based on Usage Mining. And it also produces the design mentality of the electronic commerce website application algorithm. Web usage mining is an application of data mining technology to mining the data of the web server log file. It can discover the browsing patterns of user and some kind of correlations between the web pages. Web usage mining provides the support for the web site design, providing personalization server and other business making decision, etc. This algorithm is simple, effective and easy to realize, it is suitable to the web usage mining demand of construct a low cost B2C website.
A hypercube-based encoding for evolving large-scale neural networks
Authors: Kenneth O. Stanley, David B. D'Ambrosio, Jason Gauci
Venue: Artificial Life (2009)

Research in neuroevolution---that is, evolving artificial neural networks (ANNs) through evolutionary algorithms---is inspired by the evolution of biological brains, which can contain trillions of connections. Yet while neuroevolution has produced successful results, the scale of natural brains remains far beyond reach. This article presents a method called hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT) that aims to narrow this gap. HyperNEAT employs an indirect encoding called connective compositional pattern-producing networks (CPPNs) that can produce connectivity patterns with symmetries and repeating motifs by interpreting spatial patterns generated within a hypercube as connectivity patterns in a lower-dimensional space. This approach can exploit the geometry of the task by mapping its regularities onto the topology of the network, thereby shifting problem difficulty away from dimensionality to the underlying problem structure. Furthermore, connective CPPNs can represent the same connectivity pattern at any resolution, allowing ANNs to scale to new numbers of inputs and outputs without further evolution. HyperNEAT is demonstrated through visual discrimination and food-gathering tasks, including successful visual discrimination networks containing over eight million connections. The main conclusion is that the ability to explore the space of regular connectivity patterns opens up a new class of complex high-dimensional tasks to neuroevolution.
Strengthening Buffer Operator Close to the Law of Indices and its Properties
Authors: Qin Wan, Yong Wei
Venue: Proceedings of the 2009 Second International Symposium on Intelligent Information Technology and Security Informatics (2009)

Construct one kind of new strengthening buffer operator which is close to the law of indices, and the examples have shown that the new strengthening buffer operator can enhance the forecasting simulation precision of GM model in shock disturbed system. When disturbance from the factor of the shock disturbed system affect to the primary data, then can use the new strengthening buffer operator to eliminate it. The strengthening new buffer operator has certain usability and validity. This paper provides methods for solving the contradiction between quantitative forecasting result and qualitative analysis conclusion
Grounding interpersonal privacy in mediated settings
Authors: Natalia A. Romero, Panos Markopoulos
Venue: Proceedings of the ACM 2009 international conference on Supporting group work (2009)

Recent technologies supporting continuous connectivity enable sustained awareness within social networks, which eventually boosts interaction and therefore the need of individuals to manage their interpersonal privacy. This paper introduces the Privacy Grounding Model that describes how people develop and use mechanisms to establish a shared understanding of their intentions to interact with others. The main design implication of this model is the need for lightweight interactive mechanisms by which individuals can collaboratively ground needs for interaction. To illustrate how the model supports the design of grounding mechanisms, we present examples and discuss a case study that informs about their use during several weeks.
FPGA based neural network position and speed estimator for switched reluctance motor drive
Authors: Jakub Talla, Josef Stehlik
Venue: Proceedings of the 7th conference on Circuits, systems, electronics, control and signal processing (2008)

This paper presents the design and implementation of the sensorless control system for the Switched Reluctance Motor (SRM) drive without a position sensor. The SRM has been receiving attention for industry applications due to its low cost in mass production, reduced maintenance requirements, rugged behavior and large torque output over very high speed range. On the other hand, torque ripple, acoustic noise and rotor position sensor requirements are the main disadvantages. This work has been supported by the Czech Ministry of Education - project: Modern Control of the Switched Reluctance Motor Drives - 913/2008/G1.
Heat Transfer in Thin Films
Authors: Thomas V. Prevenslik
Venue: Proceedings of the 2009 Third International Conference on Quantum, Nano and Micro Technologies (2009)

Heat transfer in thin films treats phonons as particles in the Boltzmann Transport Equation (BTE). However, phonons only allow slow thermal response. Rapid film heat transfer is possible provided films are allowed to promptly emit non-thermal electromagnetic (EM) radiation. Quantum mechanics (QM) used in the response of nanoparticles (NPs) is extended to thin films through the theory of QED induced EM radiation. Here QED stands for quantum electrodynamics. Atoms in thin films are generally under EM confinement at vacuum ultraviolet (VUV) levels that by QM are restricted to vanishing small levels of thermal kT energy, and therefore heat gain cannot be conserved by an increase in temperature. Heat is low frequency EM energy, and therefore the gain is conserved by VUV emission following QED induced up-conversion to the VUV confinement frequency of the film. The effective conductivity appears reduced only because EM emission is excluded from the heat balance. If included, the film maintains bulk conductivity through the thickness. The generality of QED induced EM radiation in thin films is extended to NPs that enhance heat transfer in nanofluids and as nanocatalysts increase the rate of chemical reactions.
Bridge configurations in piezoresistive two-axis accelerometers
Authors: Einar Halvorsen, Svein Husa
Venue: Analog Integrated Circuits and Signal Processing (2009)

In piezoresistive two-axis accelerometers with two proof masses suspended by cantilever beams, there are generally many ways to configure the Wheatstone bridges. The configurations are different both with respect to functionality and performance. The main distinction is between bridges that contain resistors belonging to both proof masses, and the one bridge that doesn't. We compare the different bridge configurations by analytical calculations of bridge non-linearity, robustness towards manufacturing variations and electronic noise. We consider accelerometers where the ratio between the sensitivity to acceleration normal and parallel to the chip plane vary over a wide range. For numerical examples we use representative values for p-type silicon. The performance of the configuration with one bridge connected to each proof mass is superior to those that combine resistors belonging to different proof masses.
Analysis on investment behavior deviation of China's securities investment funds and the amending paths to choose
Authors: Mingliang Li, Xinhui Zhou
Venue: Proceedings of the 3rd WSEAS international conference on Computer engineering and applications (2009)

The paper adopts from the investment behavior theory and studies the affecting factors of financial investors in investment decision-making and the investment fund behavioral deviation. At the same time, the thesis also analyzes the efficiency of asset allocation and investment behavior of China's securities investment funds, and studies its impact on China's securities market. On the basis of this, it also uses LSV model to test the Fund's herding behavior, the investment behavior of the deviation and its effect on China's market orientation. At the last, it proposes some suggests and points out the paths and strategies on correcting investment behavior deviation of China's investment fund.
Automatic joint classification and segmentation of whole cell 3D images
Authors: Rajesh Narasimha, Hua Ouyang, Alexander Gray, Steven W. McLaughlin, Sriram Subramaniam
Venue: Pattern Recognition (2009)

We present a machine learning tool for automatic texton-based joint classification and segmentation of mitochondria in MNT-1 cells imaged using ion-abrasion scanning electron microscopy (IA-SEM). For diagnosing signatures that may be unique to cellular states such as cancer, automatic tools with minimal user intervention need to be developed for analysis and mining of high-throughput data from these large volume data sets (typically ~2GB/cell). Challenges for such a tool in 3D electron microscopy arise due to low contrast and signal-to-noise ratios (SNR) inherent to biological imaging. Our approach is based on block-wise classification of images into a trained list of regions. Given manually labeled images, our goal is to learn models that can localize novel instances of the regions in test datasets. Since datasets obtained using electron microscopes are intrinsically noisy, we improve the SNR of the data for automatic segmentation by implementing a 2D texture-preserving filter on each slice of the 3D dataset. We investigate texton-based region features in this work. Classification is performed by k-nearest neighbor (k-NN) classifier, support vector machines (SVMs), adaptive boosting (AdaBoost) and histogram matching using a NN classifier. In addition, we study the computational complexity vs. segmentation accuracy tradeoff of these classifiers. Segmentation results demonstrate that our approach using minimal training data performs close to semi-automatic methods using the variational level-set method and manual segmentation carried out by an experienced user. Using our method, which we show to have minimal user intervention and high classification accuracy, we investigate quantitative parameters such as volume of the cytoplasm occupied by mitochondria, differences between the surface area of inner and outer membranes and mean mitochondrial width which are quantities potentially relevant to distinguishing cancer cells from normal cells. To test the accuracy of our approach, these quantities are compared against manually computed counterparts. We also demonstrate extension of these methods to segment 3D images obtained using electron tomography.
Design of Control Circuit of Seawater Treatment System Based on Microprocessor
Authors: Yanping Gao, Xianjiu Guo, Xianqiang Lv
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Among numerous seawater treatment methods, electrolysis belongs to a relatively ideal method with good treatment effect. Basically, it can reach the standards of safe, effective, economical and environment-friendly. The control circuit part design of ballast seawater treatment system based on electrolysis is finished in this paper. This system takes a MCU as its control core, synchronous circuit module design, trigger module design and data acquisition module design, etc are mainly introduced during system design.
Performance Observations on MAC Protocols of VANETs in Intelligent Transportation System
Authors: Chang Cuyu, Xiang Yong, Shi Meilin, Lin Liang
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 02 (2009)

In the vehicle communication system based on ADHOC network, besides fairness, QoS, hidden and exposed terminal problems, the MAC protocol must fulfill the requirement of practical applications. In order to decrease the transmission collisions in VANETs, a reliable and efficient medium access control (MAC) protocol is needed. Firstly, this paper introduces the applications, the characteristics of VANETs, and the difficulties of MAC protocols in VANETs. Secondly, based on different reactive routing protocols, various MAC protocols (wireless LAN and Adhoc MAC) applied to VANETs are theoretically compared and analyzed for sub-urban, urban, and freeway situations. A qualitative comparison of VANETs MAC protocols were given. Finally, the goals and the design essentials of transmission control in VANET are proposed.
Élie Cartan's geometrical vision or how to avoid expression swell
Authors: Sylvain Neut, Michel Petitot, Raouf Dridi
Venue: Journal of Symbolic Computation (2009)

The aim of the paper is to demonstrate the superiority of Cartan's method over direct methods based on differential elimination for handling otherwise intractable equivalence problems. In this sense, using our implementation of Cartan's method, we establish two new equivalence results. We establish when a system of second order ODEs is equivalent to flat system (second derivations are zero), and when a system of holomorphic PDEs with two independent variables and one dependent variable is flat. We consider the problem of finding transformation that brings a given equation to the target one. We shall see that this problem becomes algebraic when the symmetry pseudogroup of the target equation is zerodimensional. We avoid the swelling of the expressions, by using non-commutative derivations adapted to the problem.
Significant Location Identification Based on User Behavior Modeling
Authors: Onoriu Bradeanu, Doru-Petru Munteanu
Venue: Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies (2008)

We describe a cost-effective method which enables location-aware applications in PLMN environments. The proposed approach is assuming no terminal support and it is based on signaling traffic analysis in respect to selected invariant patterns of human behavior, IHAP, and network topology. The experiments carried out in real-life network environment are revealing robust performance, in terms of accuracy and quality of experience (QoE), for certain classes of context aware applications.
Supporting Unstructured Activities in Crisis Management: A Collaboration Model and Prototype to Improve Situation Awareness
Authors: Cláudio Sapateiro, Pedro Antunes, Gustavo Zurita, Nelson Baloian, Rodrigo Vogt
Venue: Mobile Response: Second International Workshop on Mobile Information Technology for Emergency Response, MobileResponse 2008. Bonn, Germany, May 29-30, 2008, Revised Selected Papers (2009)

In this paper we explore the construction of Situation Awareness using a collection of mobile, collaborative and visual-interactive devices. These devices provide a shared workspace where multiple users may correlate information about the problematic situation at hand and organize the unstructured activities necessary to handle the situation. A PDA prototype of these mobile, collaborative and visual-interactive devices has already been developed with the purpose to evaluate the feasibility of the collaboration model. The paper describes the collaboration model and presents an application scenario in the emergency management area currently being used to evaluate the prototype.
Public Key Authentication with Memory Tokens
Authors: Camille Vuillaume, Katsuyuki Okeya, Erik Dahmen, Johannes Buchmann
Venue: Information Security Applications: 9th International Workshop, WISA 2008, Jeju Island, Korea, September 23-25, 2008, Revised Selected Papers (2009)

We propose a very low-cost authentication scheme based on Merkle signatures, which does not require any computation on the prover side, but instead, has moderate memory requirements. Our technique is particularly attractive on platforms where memory is already available, since it can be implemented at practically no cost, without any CPU, and with an extremely simple memory access control mechanism.
Still Image and Video Fingerprinting
Authors: Nikos Nikolaidis, Ioannis Pitas
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

Multimedia fingerprinting, also know as robust/perceptual hashing and replica detection is an emerging technology that can be used as an alternative to watermarking for the efficient Digital Rights Management (DRM) of multimedia data. Two fingerprinting approaches are reviewed in this paper. The first is an image fingerprinting technique that makes use of color and texture descriptors,R-trees and Linear Discriminant Analysis (LDA). The second is a two-step, coarse-to-fine video fingerprinting method that involves color-based descriptors, R-trees and a frame-based voting procedure. Experimental performance evaluation is provided for both methods.
A new approach for ACET based scheduling of soft real-time systems
Authors: X. Guo, M. Boubekeur, J. Mc Enery, D. Hickey
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

In certain real-time systems worst-case execution time estimates often lead to a waste of resources. In hard real-time systems these types of estimates are essential to guarantee temporal requirements are met. However in soft-real time systems using other measurements, such as average-case timing, to complement the worst-case estimates can lead to better utilisation of resources while ensuring most, if not all, deadlines are met. In this paper we propose a methodology to integrate ACET information as a base for scheduling of soft real-time systems. We demonstrate the usability of the approach and illustrate it via a typical Real-Time Java sorting program.