ppxscal/embedding_network huggingface dataset:
Synthesis and optimization of low-power custom nisc processors
Authors: Daniel Gajski
Venue:  (2007)

Increasing complexity, shortening time to market, and tight requirements of embedded systems require design methodologies that increase designer productivity without sacrificing design quality. To design at higher abstraction level, today two approaches exist: High-Level Synthesis (HLS) and Application-Specific Instruction-Set Processors (ASIP). HLS mostly focuses on smaller applications and allows little control over the quality of automatically generated micro-architecture. On the other hand, ASIP can handle larger applications but has a high overhead for smaller applications. It also has a complex flow and requires instruction-set design expertise. Therefore, a unifying design methodology is needed that addresses the shortcomings of both methodologies and can support applications ranging from small to large within a single framework. No-Instruction-Set-Computer (NISC) Technology is developed to be such unifying methodology. To simplify the design process and enable more aggressive datapath optimizations, in NISC, the instruction abstraction is replaced with nanocodes that directly control the datapath components in every cycle. In my PhD, I focused on different challenges of synthesizing efficient NISC processors and generating hardware. The first part of my thesis focuses on developing an Architecture Description Language (ADL) that captures NISC processors for compilation and synthesis. This ADL is called Generic Netlist Representation (GNR) which is a strongly-typed, aspect-oriented ADL for describing netlist of NISC processors. The rest of my thesis focuses on some of the possible controller and datapath optimizations that affect performance, area, and power consumption of NISC processors. For instance, I present a hybrid approach that optimizes the binary code to reduce both the code size and the switching activity of the datapath. I also discuss how a given datapath can be customized and optimized for an application through an aggressive resource sharing. As part of this thesis, two tools have been developed: (1) an RTL generator tool that converts GNR to synthesizable Verilog code; and (2) a datapath refiner tool that customizes a given datapath for an application within a given performance constraint. Both tools are integrated into NISC toolset and are available online at http://www.cecs.uci.edu/&sim;nisc/.
UMM Add-In: A UML Extension for UN/CEFACT's Modeling Methodology
Authors: B. Hofreiter, C. Huemer, P. Liegl, R. Schuster, M. Zapletal
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

The tighter coupling of enterprises in regard to information system technology has also changed the way business processes are modeled. Modeling interorganizational business processes is necessary in order to gain a profound and unique representation of the processes involved. However this requires a new methodology especially designed for modeling inter-organizational business processes. The United Nation's Center for Trade Facilitation and Electronic Business (UN/CEFACT) took up the challenge and started to develop such a methodology. The research efforts became known as UN/CEFACT's modeling methodology (UMM) [1]. UMM enables the business modeler to capture the business knowledge independent of the underlying implementation technology such as ebXML or Web Services.
Application of a Wavelet Packet Transform Based Radial Basis Function Neural Network to Analyze Overlapping Spectra
Authors: Shouxin Ren, Ling Gao
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

This paper suggested a novel method based on wavelet packet transform and radial basis function neural network (WPTRBFN) in simultaneous spectrophotometric determination of Mn (II), Zn (II), Co (II) and Cd (II) combining wavelet packet thresholding denoising with radial basis neural network. Wavelet packet representations of signals provided a local time–frequency description, thus in the wavelet packet domain, the quality of the noise removal can be improved. Radial basis function network was applied for overcoming the convergence problem met in back propagation training and facilitating nonlinear calculation. In this case, by optimization, wavelet function, decomposition level, the numbers of hidden nodes and the width σ of RBFN for WPTRBFN method were selected as Symmlet 5, 1, 20 and 1.2 respectively. The relative standard errors of prediction (RSEP) for all components with WPTRBFN, RBFN and PLS were 7.4, 8.9 and 8.1 percent respectively. The proposed method has been successfully applied to analyze overlapping spectra and better than others.
Surplus extraction by network providers: Implications for net neutrality and innovation
Authors: Gireesh Shrimali
Venue: Telecommunications Policy (2008)

This paper looks at surplus extraction by network providers who control the medium of information transfer between application developers and consumers, and addresses the following questions: is net neutrality beneficial to society? and does providing network providers flexibility in pricing stunt innovation in the long run? To answer the first question, it looks at a market consisting of a monopoly network provider and two application providers with non-substitutable products, using a simple single period model. It shows that net neutrality is necessary to ensure maximal benefit to the society. To answer the second question, the paper shows that a monopoly network provider, if allowed complete flexibility in pricing, does not necessarily stunt innovation. Looking at a market that consists of one network provider and one application provider, and using a simple multi-period model, it shows that given maximum flexibility the network provider not only encourages innovation when the potential benefits are sufficiently high but also maximizes surplus. This paper takes the view that the topic of net neutrality is not only controversial but also complicated, and suggests that policy makers use a balanced approach based on sound analysis.
The Excitation Controller of Synchronous Generator Employing PID and Fuzzy Integrated Algorithm Based on S3C2410A
Authors: Lingyan Hu, Yong Xin, Jie Peng, Helei Wu
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

A new kind of excitation controller of harmonic wave excited synchronous generator is proposed in this paper. The controller can adjust the excitation current by adjusting duty circle of the PWM wave, in order to keep the terminal voltage at the expectation value. To solve the problems existing in the conventional PID algorithm, the duty circle of the PWM wave is calculated by PID and fuzzy integrated algorithm which can employ different control algorithm to adapt to the different case. In addition, the S3C2410A with ARM920T CPU core has been used as CPU of the controller, which makes the controller finish the complex algorithm in time. So the high speed and real-time performance can be guaranteed.The simulation result shows the controller with PID-FUZZY composite algorithm is better than traditional PID controller both in speediness and in stability. What’s more important, the controller can be adapted to the different generators without change the parameters as the controller with traditional PID algorithm. In addition, the experiment on the W6-90 KW harmonic excitation generator has shown the generator with excitation controller designed in this paper can running steadily, and its various parameters performances can reach the national standards.
Mathematics and Scientific Markup
Authors: Peter Murray Rust
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

The development of e-Science (cyberScience, Grid, etc.) is starting to become a reality with formalised data resources, services on demand, domain-specific search engines, digital repositories, etc. Increasingly STM information will be contained in compound XML documents, representing scientific communication (articles, theses, repository entries, etc.). In physical sciences such as chemistry, materials science, engineering, physics, earth sciences, these "datuments" [1] normally contain hypertext, graphics, tables, graphs and numerical data, mathematical objects and relationships. In addition they may also contain domain-specific content such as chemical formula and reactions, thermodynamic and mechanical properties, electric, magnetic and optical properties.Among the domain-specific languages, CML (Chemical Markup Language) is the oldest and broadest, and is now being actively used for publishing by the Royal Society of Chemistry (Project Prospect [2]) which gives an idea of what chemistry in datuments can look like. CML has had to develop the domain-specific objects (molecules, atoms, bonds, spectra, crystallography, etc.) and the relationships between them. However, due to the text-based nature of early XML, it has also had to design an implement domain-independent infrastructure which can support much of physical science. Originally called STMML [3] it supports data types (float, integer, complex, etc.), data structures (arrays, lists, matrices, etc.), geometrical concepts (points, planes, lines, etc.) and scientific units of measurement. In addition CML bases much of its flexibility one usercreated dictionaries (ontologies) which are hyperlinked from objects in the datuments.
A Performance Study of Mutual Exclusion/Synchronization Mechanisms in an IEEE 796 Bus Multiprocessor
Authors: E. O'Grady, Raul Lozano
Venue: IEEE Micro (1985)

Of three mechanisms evaluated, the FIFO semaphore tied up the system bus the least.
Passive dynamic walker controller design employing an RLS-based natural actor-critic learning algorithm
Authors: Baeksuk Chu, Daehie Hong, Jooyoung Park, Jae-Hun Chung
Venue: Engineering Applications of Artificial Intelligence (2008)

A passive dynamic walker belongs to a class of bipedal walking robots that are able to walk stably down a small decline without using any actuators. The purpose of this research is to design a controller in order to build actuated robots capable of walking on a flat terrain based on passive dynamic walking. To achieve this objective, a control algorithm was used based on reinforcement learning (RL). The RL method is a goal-directed learning of a mapping from situations to actions without relying on exemplary supervision or complete models of the environment. The goal of the RL method is to maximize a reward, which is an evaluative feedback from the environment. In the process of constructing the reward of the actuated passive dynamic walker, the control objective, which is stable walking on level ground, is directly included. In this study, an RL algorithm based on the actor-critic architecture and the natural gradient method is applied. Also, the recursive least-squares (RLS) method was employed for the learning process in order to improve the efficiency of the method. The control algorithm was verified with computer simulations based on the eigenvalue analysis for stable locomotion.
A Hybrid Genetic Algorithm with Simulated Annealing for Nonlinear Blind Equalization Using RBF Networks
Authors: Soowhan Han, Imgeun Lee, Changwook Han
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

In this study, a hybrid genetic algorithm, which merges a genetic algorithm with simulated annealing, is derived for nonlinear channel blind equalization using RBF networks. The proposed hybrid genetic algorithm is used to estimate the output states of a nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. From these estimated output states, the desired channel states of the nonlinear channel are derived and placed at the center of a RBF equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm (GA) and a simplex GA. It is shown that the relatively high accuracy and fast convergence speed have been achieved.
A 3D Simulator of Multiple Legged Robots Based on USARSim
Authors: Marco Zaratti, Marco Fratarcangeli, Luca Iocchi
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

This paper presents a flexible 3D simulator able to reproduce the appearance and the dynamics of generic legged robots and objects in the environment at full frame rate (30 frames per second). Such a simulator extends and improves USARSim (Urban Search and Rescue Simulator), a robot simulator in turn based on the game platform Unreal Engine. This latter provides facilities for good quality rendering, physics simulation, networking, highly versatile scripting language and a powerful visual editor. Our simulator extends USARSim features by allowing for the simulation and control of legged robots and it introduces a multi-view functionality for multi-robot support. We successfully tested the simulator capabilities by mimicking a virtual environment with up to five network-controlled legged robots, like AIBO ERS-7 and QRIO.
A Comparative Study of Reasoning Techniques for Service Selection
Authors: Murat Şensoy, Pınar Yolum
Venue: Agents and Peer-to-Peer Computing: 5th International Workshop, AP2PC 2006, Hakodate, Japan, May 9, 2006, Revised and Invited Papers (2006)

Open multiagent systems do not provide guarantees about the quality of the service of its providers. This makes it difficult for service consumers to find correct service providers. Many existing approaches share the intuition that service consumers can share their knowledge about service providers to help locate useful service providers. However, representing existing past knowledge and reasoning about this knowledge are two important challenges. A traditional approach for dealing with these challenges is to represent past dealings with ratings and to aggregate the ratings. However, rating-based approaches lack the expressiveness to articulate objective information about service dealings. To enable richer representations, we have developed an objective experience-based approach for service provider selection, in which consumers record their experiences with service providers rather than the overall, subjective ratings for a provider. A consumer's experience with a service provider is represented using an ontology that can capture subtle details including the context in which the service was requested. When a service consumer decides to share her experiences with a second service consumer, the receiving consumer evaluates the experience using its own context and evaluation criteria. In this work, we tackle the problem of reasoning about the collected experiences. We study different reasoning techniques for consumer agents to use in selecting service providers. We formulate these techniques into agent strategies and examine their strengths and weaknesses through simulations.
Improving the Performance of Multiple Conjugate Gradient Solvers by Exploiting Overlap
Authors: José Carlos Sancho, Darren J. Kerbyson
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Conjugate gradient solvers are often being the most time-consuming part of many scientific applications. These solvers exhibit communications operations that can prevent high performance from being achieved at large scale systems. In this paper we present a novel technique to boost the performance of these solvers. In this technique multiple independent solvers that occur in some applications are combined allowing for the overlapping many communications with other communication and computation resulting with increased performance. This work is the first time that combination of CG solvers is exploited and offers performance improvements which may be particularly important in very large-scale systems. Results are presented for the MIMD Lattice (MILC) application and show that the cost of collective communications can be reduced by a factor of 2.5×. Moreover the performance of MILC is significantly improved, by over 10% for typical lattice sizes on a 1,024-processor system.
Ultrasonic Sensor Based Fuzzy-Neural Control Algorithm of Obstacle Avoidance for Mobile Robot
Authors: Hongbo Wang, Chaochao Chen, Zhen Huang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper presents a novel fuzzy-neural control algorithm to realize obstacle avoidance of a mobile robot. A heuristic fuzzy-neural network is developed based on heuristic fuzzy rules and the Kohonen clustering network. By applying the off-line and unsupervised training method to this network, the pattern mapping relation between ultrasonic sensory input and velocity command is established. This paper describes mechanical design of the mobile robot, the arrangement of ultrasonic sensors, the obstacle avoidance system based on FKCN, classification of obstacle, the control algorithm for obstacle avoidance and training data library. In order to verify the effectiveness of this algorithm, we give the results of simulation in a computer virtual environment.
Blind and Visually Impaired People: Human-Computer Interaction and Access to Graphics
Authors: Ilvio Bruder, Gerhard Jaworek
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Graphical interfaces for modern information and communication systems are state of the art in computer interaction. Graphical interfaces stand for fast, comprehensive, and flexible usage of computer in working as well as in private environments. Impaired people, especially visually impaired, have major problems using the graphical interface. These people can not use contemporary computer programs. That is one reason for comprehensive less number of visually impaired employees. Helping these people is a necessary, but difficult challenge. The introduced special thematic session "Blind and Visually Impaired People: Human-Computer Interaction and Access to Graphics" represents current research towards solutions for visually impaired and brings together researchers and practitioners. The STS represents topics from hard- and software user interfaces, screen reader, accessibility of specific applications, and e-learning and communication strategies.
Automatic Labeling of Anatomical Structures in MR FastView Images Using a Statistical Atlas
Authors: Matthias Fenchel, Stefan Thesen, Andreas Schilling
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present a method for fast and automatic labeling of anatomical structures in MR FastView localizer images, which can be useful for automatic MR examination planning. FastView is a modern MR protocol, that provides larger planning fields of view than previously available with isotropic 3D resolution by scanning during continuous movement of the patient table. Hence, full 3D information is obtained within short acquisition time. Anatomical labeling is done by registering the images to a statistical atlas created from training image data beforehand. The statistical atlas consists of a statistical model of deformation and a statistical model of grey value appearance. It is generated by non-rigid registration and principal component analysis of the resulting deformation fields and registered images. Labeling of an unseen FastView image is done by non-rigid registration of the image to the statistical atlas and propagating the labels from the atlas to the image. In our implementation, the statistical models of deformation and appearance are both implemented on the GPU (graphics processing unit), which permits computing the atlas based labeling using GPU hardware acceleration. The running times of about 10 to 30 seconds are of the same magnitude as the image acquisition itself, which allows for practical usage in clinical MR routine.
Advanced genetic operators and techniques: an analysis of dominance & diploidy, reordering operator in genetic search
Authors: Anuradha Sanjiv Deshpande, Ramesh Balabhau Kelkar
Venue: Proceedings of the 9th WSEAS International Conference on Evolutionary Computing (2008)

The paper explains use of low level advanced Genetic Algorithm operator DOMINANCE & DIPLOIDY for getting new binary string structure in terms of heterozygous or homozygous expression of dominated & recessive alleles. It also highlights role of schema representation (physical schema and expressed schema) on population size, as an attempt to improve upon the robustness of simple GA's. The paper has demonstrated numerically pattern of selection of dominant and recessive alleles. It has suggested numerically the probability of gene movement and gene disruption for various REORDERING OPERATORS LIKE INVERSION, CYCLE CROSSOVER, and order crossover etc. Theory of reordering operator is tested and verified upon string / schema representation. Thus the paper aims to analyze the advanced genetic operators and techniques in GA search.
Measuring the diffusion of eParticipation: A survey on Italian local government
Authors: Rony Medaglia
Venue: Information Polity (2007)

The use of ICT to enable citizen participation (eParticipation) is expanding, especially at the local level of government. But to what extent is this actually occurring, how can we reliably measure it and what are the variables that affect eParticipation adoption at the local level? This paper tackles these three questions by looking at the case of Italian local government. A data collection tool, validated by a group of experts, was proposed and used to conduct a survey on the official websites of 113 Italian local authorities. Findings from primary data show that, within a context of a low level, overall, of adoption of advanced participatory features, institutional background factors such as scale, socio-economic status and centre-left political orientation are positively associated with greater information and consultation features.
Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion
Authors: Roberto Gallea, Edoardo Ardizzone, Roberto Pirrone, Orazio Gambino
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction. This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.
Evolution of NAND Flash Memory Interface
Authors: Sang Lyul Min, Eyee Hyun Nam, Young Hee Lee
Venue: Proceedings of the 12th Asia-Pacific conference on Advances in Computer Systems Architecture (2007)

In this paper, we describe the basics of NAND flash memory and describe the evolution of its interface to facilitate easy integration, to provide high bandwidth, to offer disk-like interface, and/or to guarantee interoperability.