ppxscal/embedding_network huggingface dataset:
Efficient Implementation of SVM Training on Embedded Electronic Systems
Authors: Paolo Gastaldo, Giovanni Parodi, Sergio Decherchi, Rodolfo Zunino
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

The implementation of training algorithms for SVMs on embedded architectures differs significantly from the electronic support of trained SVM systems. This mostly depends on the complexity and the computational intricacies brought about by the optimization process, which implies a Quadratic-Programming problem and usually involves large data sets. This work presents a general approach to the efficient implementation of SVM training on Digital Signal Processor (DSP) devices. The methodology optimizes efficiency by suitably adjusting the established, effective Keerthi's optimization algorithm for large data sets. Besides, the algorithm is reformulated to best exploit the computational features of DSP devices and boost efficiency accordingly. Experimental results tackle the training problem of SVMs by involving real-world benchmarks, and confirm both the computational efficiency of the approach.
Multivariate quadratic trapdoor functions based on multivariate quadratic quasigroups
Authors: Danilo Gligoroski, Smile Markovski, Svein Johan Knapskog
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

We have designed a new class of multivariate quadratic trapdoor functions. The trapdoor functions are generated by quasigroup string transformations based on a class of quasigroups called multivariate quadratic quasi-groups (MQQ). The public key schemes using these trapdoor functions are bijective mappings, they do not perform message expansions and can be used both for encryption and signatures. The public key consist of n quadratic polynomials with n variables where n = 140; 160; 180,.... A particular characteristic of our public key scheme is that it is very fast; it has the speed of decryption/signature generation as a typical symmetric block cipher.
Displaying Expression in Musical Performance by Means of a Mobile Robot
Authors: Birgitta Burger, Roberto Bresin
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In recent times several attempts have been made to give a robot or broader spoken a computer some kind of feelings in order to understand and model human capacities. The main idea of our work was the design of expressive robot movements for the display of emotional content embedded in the audio layer in both live and recorded music performance. Starting from results in studies on musicians' body in emotional expressive music performance (see [3]), we tried to map different movement cues (e.g. speed, fluency) to movements of a small mobile robot. The robot had constraints of sensors and motors, so the emotions were implemented taking into account only the main characteristics of musicians' movements. We implemented movements for the three emotions happiness, anger and sadness. Subjects were asked to judge in a perceptual test which emotional intentions were communicated by the movements.
Wheelchair Propulsion Analysis System That Incorporates Human Skeletal Muscular Model Analyses on the Flat Floor and Slope
Authors: Akihiko Hanafusa, Motoki Sugawara, Teruhiko Fuwa, Tomozumi Ikeda, Naoki Suzuki, Asaki Hattori
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

A wheelchair propulsion analysis system that can be used to generate the motion of propulsion and calculate the driving force and the muscular force using a human model having a skeleton and muscles was developed. To evaluate the driving force and muscular forces calculated by the analysis system, typical forward movement of two cycles of propulsion from the start-up on a flat floor and on a slope were measured and the movement including the trunk was input to the system. In addition, the muscular forces of biceps, triceps, clavicular and acromion deltoids, pectoralis major and extensor carpi radialis were evaluated by electromyogram. The calculated driving force was in good agreement with the measured driving force even on the slope and the trend of calculated muscular force corresponded with measured electromyogram data. The system is effective for analyzing the driving force and load on muscles during the wheelchair propulsion.
Large Datasets Visualization with Neural Network Using Clustered Training Data
Authors: Sergėjus Ivanikovas, Gintautas Dzemyda, Viktor Medvedev
Venue: Proceedings of the 12th East European conference on Advances in Databases and Information Systems (2008)

This paper presents the visualization of large datasets with SAMANN algorithm using clustering methods for initial dataset reduction for the network training. The visualization of multidimensional data is highly important in data mining because recent applications produce large amount of data that need specific means for the knowledge discovery. One of the ways to visualize multidimensional dataset is to project it onto a plane. This paper analyzes the visualization of multidimensional data using feed-forward neural network. We investigate an unsupervised backpropagation algorithm to train a multilayer feed-forward neural network (SAMANN) to perform the Sammon`s nonlinear projection. The SAMANN network offers the generalization ability of projecting new data. Previous investigations showed that it is possible to train SAMANN using only a part of analyzed dataset without the loss of accuracy. It is very important to select proper vector subset for the neural network training. One of the ways to construct relevant training subset is to use clustering. This allows to speed up the visualization of large datasets.
Petite Feature Set Defining Solid Structural and Color Assets in CBIR Processes
Authors: Waqas Rasheed, Wonil Yang, Jongan Park
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Content-based Image analyses and retrieval systems, most of the time, deal with histogram refinement techniques. The coarse characterization of histograms is researched and a very brief list of features is proposed in this paper, which is recommended for RGB images carrying some structure or colored information with similar appearance. The R, G, and B contents are split and their color and edge features are considered. These features include the count of horizontal, vertical and slanting edges, the number of clusters, and the percentage of noticeable colored channel by area. Iteration is committed onto the limited set of results generated by this procedure, which further refines the results based on the overall appearance of these selective images. This reduces the order of complexity, and simultaneously, enhances searching ability by reducing number of computations and comparison time.
A Generalized Associative Petri Net for Reasoning
Authors: Dong-Her Shih, Hsiu-Sen Chiang, Binshan Lin
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

The application of fuzzy Petri Nets to the development of intelligent systems has received an increasing attention recently. However, the fuzzy production rules are rather limited if the determination of certainty factor for each proposition is subjective. Unfortunately, this is the case for many existing fuzzy Petri nets. This paper proposes a generalized associative Petri net model with associative degree and knowledge representation of a rule-based system. Based on the generalized associative Petri net model, an efficient reasoning algorithm is proposed. The ontology mapping and the associative reasoning algorithm are described formally in details. An example of malicious email reasoning is also included as an illustration.
Factors influencing the effective use of computers
Authors: R. D. Huntoon
Venue: Proceedings of the February 4-6, 1953, western computer conference (1953)

The second keynote address for the Western Computer Conference was given by Dr. R. D. Huntoon, Director of the Corona, California, Laboratories of the National Bureau of Standards (a center of activity for work in guided missiles). 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
A Tagged Corpus-Based Study for Repeats and Self-repairs Detection in French Transcribed Speech
Authors: Rémi Bove
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

We present in this paper the results of a tagged corpus-based study conducted on two kinds of disfluencies (repeats and self-repairs) from a corpus of spontaneous spoken French. This work first investigates the linguistic features of both phenomena, and then shows how --- from a corpus output tagged with TreeTagger --- to take into account repeats and self-repairs using word N-grams model and rule-based pattern matching. Some results on a test corpus are finally presented.
Balancing computation and communication costs: The case for hybrid execution in sensor networks
Authors: Joel Koshy, Ingwar Wirjawan, Raju Pandey, Yann Ramin
Venue: Ad Hoc Networks (2008)

Virtual machines (VM) are promising as system software in sensor networks. A major impediment to their widespread acceptance is their performance overhead. The compilation of VM byte code to native code improves performance, but increases the code's footprint and cost of code distribution. Thus, there is an important tradeoff between the cost of computing and the cost of communication due to code distribution. We describe a remote Just-In-Time compilation service that is effective in combining interpretation with native execution to arrive at an efficient hybrid execution configuration. The principles may be applied to any middleware that is used to develop applications for sensor networks.
Automatic Generation of Integration and Preprocessing Ontologies for Biomedical Sources in a Distributed Scenario
Authors: Alberto Anguita, David Pérez-Rey, José Crespo, Víctor Maojo
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Access to a large number of remote data sources has boosted research in biomedicine, where different biological and clinical research projects are based on collaborative efforts among international organizations. In this scenario, the authors have developed various methods and tools in the area of database integration, using an ontological approach. This paper describes a method to automatically generate preprocessing structures (ontologies) within an ontology-based KDD model. These ontologies are obtained from the analysis of data sources, searching for: (i) valid numerical ranges (using clustering techniques), (ii) different scales, (iii) synonym transformations based on known dictionaries and (iv) typographical errors. To test the method, experiments were carried out with four biomedical databases ―containing rheumatoid arthritis, gene expression patterns, biological processes and breast cancer patients― proving the performance of the approach. This method supports experts in data analysis processes, facilitating the detection of inconsistencies.
Optimal design of an impact damper for a nonlinear friction-driven oscillator
Authors: Ehsan Maani Miandoab, Aghil Yousefi-Koma, Dana Ehyaei
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

In the present study a Friction-Driven oscillator is investigated analytically using perturbation method and numerically with Runge-Kutta's intergration procedure. The analytical method is aslo used to investigate damping performance of a single-particle-impact damper on amplitude and frequency of system over a wide range of particle-to-structure mass ratios, clearance, and coefficient of restitution. Considering sensitivity of the system to variation of mass ratio and coefficient of restitution, optimal values are obtained for these parameters. These optimal values are plotted as a function of the other two parameters. The frequency of the system has low sensitivity to the variation of coefficient of restitution but varies with clearance and mass ratio changes.
Efficient First-Order Model-Checking Using Short Labels
Authors: Bruno Courcelle, Cyril Gavoille, Mamadou Moustapha Kanté
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

We prove that there exists an O(log(n))-labeling scheme for every first-order formula with free set variables in every class of graphs that is nicely locally cwd-decomposable, which contains in particular, the nicely locally tree-decomposable classes. For every class of graphs of bounded expansion we prove that every bounded formula has an O(log(n))-labeling scheme. We also prove that every quantifier-free formula has an O(log(n))-labeling scheme in graphs of bounded arboricity. Some of these results are extended to counting queries.
Activities of the Applied Science Mathematical Committee on the 701
Authors: William F. McClelland
Venue: IEEE Annals of the History of Computing (1983)

Editor's Note: In this section William F. McClelland describes the activities of the Applied Science Mathematical Committee on the 701. He lists the programs that were supplied to customers and gives a tracing program as an example. He also gives some 1951 ideas looking toward automatic programming. In his paper in the Architecture section of this issue, Rochester refers to programming, and we print here names of several programs he listed in October 1951.
Neural Mechanism for Extracting Object Features Critical for Visual Categorization Task
Authors: Mitsuya Soga, Yoshiki Kashimori
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

The ability to group visual stimuli into meaningful categories is a fundamental cognitive process. Some experiments are made to investigate the neural mechanism of visual categorization. Although experimental evidence is known that prefrontal cortex (PFC) and inferiortemporal (IT) cortex neurons sensitively respond in categorization task, little is known about the functional role of interaction between PFC and IT in categorization task To address this issue, we propose a functional model of visual system, and investigate the neural mechanism for the categorization task of line drawings of faces. We show here that IT represents similarity of face images based on the information of the resolution maps of early visual stages. We show also that PFC neurons bind the information of part and location of the face image, and then PFC generates a working memory state, in which only the information of face features relevant to the categorization task are sustained.
On Bandwidth-Efficient Data Broadcast
Authors: De-Nien Yang, Ming-Syan Chen
Venue: IEEE Transactions on Knowledge and Data Engineering (2008)

In this paper, we leverage network coding to reduce the bandwidth consumption for data broadcast. We use the concept of mixing in a different way from the traditional network coding. Traditional network coding mixes all data items together. However, we mix each data item from only some data items according to the queried and stored data of receivers. Therefore, each receiver in our approach is required to receive fewer coded data to decode the required information, and the sender thereby is able to broadcast fewer data items. We formulate an optimization problem with integer-linear programming to minimize the bandwidth consumption in data broadcast. We prove that the problem is NP-hard and design an approximation algorithm that can be implemented in the data server. In addition, we show that different mixings of data items lead to different decoding costs for receivers. We design an algorithm to optimally code the data items with the minimum decoding cost.
Extensible Multi-Robot System
Authors: Wojciech Turek
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

In recent decades many important problems concerning mobile robots control algorithms have been solved. In order to integrate those solutions into complex, reliable, production-quality systems, an effort must be made to define abstract methodologies, architectures and frameworks, that would provide common functionalities and support features desirable in production systems: scalability, extensibility, flexibility and durability. This paper presents an agent-based architecture, which should provide extensibility of Multi-Robot Systems. 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-Throughput Analysis of the Drug Mode of Action of PB28, MC18 and MC70, Three Cyclohexylpiperazine Derivative New Molecules
Authors: Vitoantonio Bevilacqua, Paolo Pannarale, Giuseppe Mastronardi, Amalia Azzariti, Stefania Tommasi, Filippo Menolascina, Francesco Iorio, Diego Bernardo, Angelo Paradiso, Nicola A. Colabufo, Francesco Berardi, Roberto Perrone, Roberto Tagliaferri
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Objective: This work explores the mode of action of PB28, MC70 and MC18 three molecules that showed anti-tumoral properties by arresting cellular growth and inhibiting glycoprotein P. Methods: Here we conduct a microarray-based study and analyze the expression patterns associated with the action of drugs. An ontology based analysis has been conducted, and the individuated cellular processes have been analyzed with gene networks, examining the interactions among genes. A clustering analysis revealed mechanisms shared with other drugs. Results: The results indicate that this compounds have side effects that include inflammatory response and fever, induced by the interleukin signaling pathway. Other evidences related with known effects of the compounds were highlighted. Conclusions: The results indicate that the direct effects could be reached at a post-transcriptional level of P-gp or through other targets, further studies will address these hypothesis. The prediction of side effects will be useful in subsequent in vivo experiments.
An example of applying the analytical methodology in case of asymmetric conflict
Authors: Ion Badoi, Eugen Trana, Tudor Chereches, Marin Bica
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This very brief example of military simulation shows usefulness as a practical basis for education, training, analysis, and decision-support. As an analytically challenging field of pursuit, military simulation has the potential to make a significant improvement to the effectiveness of military personnel.
Insights on ICI and its effects on performance of OFDM systems
Authors: Khoa N. Le
Venue: Digital Signal Processing (2008)

Three-dimensional analyses on inter-carrier interference power (P"I"C"I) reduction methods using a rectangular pulse (RP), a raise-cosine pulse (RCP), a ''better-than'' raised-cosine pulse (BTRCP), a sinc power pulse (SPP) and an improved sinc power pulse (ISPP) are given. The effects of sub-carrier interference are analysed. Bit error rates (BER) of an orthogonal frequency division multiplexing (OFDM) system and a communications system employing BPSK modulation over an additive white Gaussian noise (AWGN) channel as a function of carrier frequency offset @Df, carrier phase noise @q and pulse shaping P(f) are derived. Detailed discussions are given. Future work is also outlined.
Semi-Automatic Segmentation and Volume Determination of Brain Mass-Like Lesion
Authors: Soontharee Koompairojn, Antoniya Petkova, Kien A. Hua, Pichest Metarugcheep
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

In this paper, a semi-automatic segmentation technique for brain mass-like lesions in Magnetic Resonance (MR) image sequences is proposed. With the graphical user interface of ImageJ, the user can interactively determine the lesion volume. The user needs to only provide the tumor contour on one MR slice using LiveWire, after which the system automatically segments and determines the gross lesion volume. Our experimental results, based on MR image sequences from Prasat Neurological Institute, indicate that the proposed system is effective.
Generating Novel Information Salient Maps for Foreground Object Detection in Video
Authors: Chang Liu, Pong C. Yuen, Guoping Qiu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The conceptual model of visual saliency in human vision system has been employed in extracting salient features from images and multimedia data in the last decade. This paper proposes to employ the visual saliency for moving object detection. The crucial factor is to compute a saliency map such that visual attention can be performed. This paper proposes a new method for saliency map construction based on information theory and spatio-temporal model, called information saliency map (ISM). The ISM provides rich information content of the video. Moving object detection are then performed based on the ISM. Two popular and publicly available visual surveillance databases from CAVIAR and PETS are selected for evaluation. Experimental results show that the proposed method is robust for moving object detection in complex background and illumination changes. The average detection rate is 90.35% while the false alarm rate is 2.46% in CAVIAR (INRIA entrance hall) dataset with ground truth data, and it has shown merits comparing with the current state of the art.
Distributed Coordination of Massively Multi-Agent Systems
Authors: Nadeem Jamali, Xinghui Zhao
Venue: Massively Multi-Agent Technology: AAMAS Workshops, MMAS 2006, LSMAS 2006, and CCMMS 2007 Hakodate, Japan, May 9, 2006 Honolulu, HI, USA, May 15, 2007 Selected and Revised Papers (2008)

Coordination is a key problem in massively multi-agent systems. As applications execute on distributed computer systems, coordination mechanisms must scalably bridge the network distance between where decisions are made and where they are to be enforced.Our work on the CyberOrgs model addresses this challenge by encapsulating distributed multi-agent computations along with computational and communication resources they require (for carrying out the application's functions as well as for coordinating actions of the agents) plus purchasing power represented by an amount of eCash for acquiring additional resources. Resources are defined in time and space, and are owned by cyberorgs. Resource ownership changes as a result of trade between cyberorgs.Ownership of resources coupled with an effective and scalable control structure creates a predictable resource environment for multi-agent systems and their coordination mechanisms to execute in. Particularly, the coordination mechanism can reason about the possibility of successful coordinated action based on predictable communication and processing delays.This paper presents our experience with hierarchical coordination of distributed processor resource for a system of cyberorgs internally distributed across a number of physical nodes. We demonstrate that encapsulation of network resources creates a scalable opportunity for reasoning about distributed coordinated action to support decision making.Experimental results show that the CyberOrgs based resource-aware approach scalably increases opportunities for successful coordinated distributed actions involving up to 1500 agents (in much larger systems) by reducing the delay in determining their feasibility, as well as helps avoid attempts of infeasible actions.