ppxscal/embedding_network huggingface dataset:
A Novel Recurrent Generalized Congruence Neural Network for Dynamical System Identification
Authors: Tianyun Yan, Hefei Ling, Shurong Zou
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

A novel recurrent generalized congruence neural network (RGCNN) is presented. Compared with traditional recurrent neural networks (RNNs), RGCNN has the following advantages: simple structure (4 layers), no time-consuming iterative derivative operations in updating weights, and fast convergence induced by modulo arithmetic of the generalized congruence neuron. Computer simulations on benchmark examples of dynamical system identification have successfully validated the performance of the proposed RGCNN.
Multi-Task Learning for Classification with Dirichlet Process Priors
Authors: Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram
Venue: The Journal of Machine Learning Research (2007)

Consider the problem of learning logistic-regression models for multiple classification tasks, where the training data set for each task is not drawn from the same statistical distribution. In such a multi-task learning (MTL) scenario, it is necessary to identify groups of similar tasks that should be learned jointly. Relying on a Dirichlet process (DP) based statistical model to learn the extent of similarity between classification tasks, we develop computationally efficient algorithms for two different forms of the MTL problem. First, we consider a symmetric multi-task learning (SMTL) situation in which classifiers for multiple tasks are learned jointly using a variational Bayesian (VB) algorithm. Second, we consider an asymmetric multi-task learning (AMTL) formulation in which the posterior density function from the SMTL model parameters (from previous tasks) is used as a prior for a new task: this approach has the significant advantage of not requiring storage and use of all previous data from prior tasks. The AMTL formulation is solved with a simple Markov Chain Monte Carlo (MCMC) construction. Experimental results on two real life MTL problems indicate that the proposed algorithms: (a) automatically identify subgroups of related tasks whose training data appear to be drawn from similar distributions; and (b) are more accurate than simpler approaches such as single-task learning, pooling of data across all tasks, and simplified approximations to DP.
A queuing network model for the management of berth crane operations
Authors: Pietro Canonaco, Pasquale Legato, Rina M. Mazza, Roberto Musmanno
Venue: Computers and Operations Research (2008)

This paper focuses on the optimal management of container discharge/loading at any given berthing point, within a real maritime terminal. Productivity maximization of expensive resources, as rail-mounted berth cranes, should be matched with the vessel requirement of minimizing waiting times with an adequate rate of service completion. To this practical problem, a queuing network model is proposed. Due to its complexity, discrete-event simulation appears as the most appropriate approach to model solution. To get a systematic representation of real constraints and policies of resource allocation and activity scheduling, an event graph (EG)-based methodology has been exploited in simulator design. Alternative policies issued by the operation manager can be inserted in a suitable panel-like view of the queuing network model and then compared by means of simulation, to evaluate the average measures for all berth cranes, such as throughput and completion time. Numerical experiments for simulator validation against real data are encouraging. Some decisions on both straddle carrier assignment to berth cranes and hold assignment and sequencing upon the same crane could be improved by the proposed manager-friendly simulation tool.
Centre and Range method for fitting a linear regression model to symbolic interval data
Authors: Eufrásio de A. Lima Neto, Francisco de A. T. de Carvalho
Venue: Computational Statistics Data Analysis (2008)

This paper introduces a new approach to fitting a linear regression model to symbolic interval data. Each example of the learning set is described by a feature vector, for which each feature value is an interval. The new method fits a linear regression model on the mid-points and ranges of the interval values assumed by the variables in the learning set. The prediction of the lower and upper bounds of the interval value of the dependent variable is accomplished from its mid-point and range, which are estimated from the fitted linear regression model applied to the mid-point and range of each interval value of the independent variables. The assessment of the proposed prediction method is based on the estimation of the average behaviour of both the root mean square error and the square of the correlation coefficient in the framework of a Monte Carlo experiment. Finally, the approaches presented in this paper are applied to a real data set and their performance is compared.
Flexible Grid Client
Authors: Dingju Zhu, Jianping Fan
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

At present, all existent grid clients need install web browser or applications, so they are fat. While they can not almost support streaming media and their devices can not be accessed by grid services. Like thin-client (TC), flexible grid client (FGC) only requires clients to have basic input and display functions, so FGC is thinner than any kind of existent grid clients. However, FGC can support streaming media better than all existent grid clients and TC. In addition, FGC enables grid services to access client devices, such as printers, USB memory and scanner, which would be impossible with all existent grid clients and TC. As a result, grid computing would be more pervasive and more powerful with FGC, which elegantly combines the strengths of grid computing, thin-client computing and fat-client computing. Key words: grid computing; flexible grid client; thin-client computing; fat-client computing
Protocol Engineering Principles for Cryptographic Protocols Design
Authors: Ling Dong, Kefei Chen, Mi Wen, Yanfei Zheng
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Design of cryptographic protocols especially authentication protocols remains error-prone, even for experts in this area. Protocol engineering is a new notion introduced in this paper for cryptographic protocol design, which is derived from software engineering idea. We present and illustrate protocol engineering principles in three groups: cryptographic protocol security requirements analysis principles, detailed protocol design principles and provable security principles. Furthermore, we illustrate that some of the well-known Abadi and Needham's principles are ambiguous. This paper is useful in that it regards cryptographic protocol design as system engineering, hence it can efficiently indicate implicit assumptions behind cryptographic protocol design, and present operational principles on uncovering these subtleties. Although our principles are informal, but they are practical, and we believe that they will benefit other researchers.
On Arithmetical Shift for Walsh Functions
Authors: Le Dinh Chon Tam
Venue: IEEE Transactions on Computers (1972)

A general expression for oo such that cal (k,?+?0)= sal (k,?) is obtained and a proof is given. This new form of ?0 is more direct and thus easier to use than other existing formulas.
Firing Patterns and Synchronization of Neuronal Population with Excitatory and Inhibitory Connection
Authors: Xianfa Jiao, Rubin Wang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

We propose a stochastic model of neuronal population with excitatory and inhibitory connection. We investigate the phase synchrony and firing patterns of a neuronal population by means of Fokker-Planck approach. Numerical simulations show that in a lower excitatory coupling, the presence of inhibitory connection hinders the emergence of synchronous activity in the population, whereas in a stronger coupling, the presence of inhibitory connection facilitates the synchronous activity in the population. Numerical simulations also show that the pattern of firing is low-frequency and regular in a neuronal population without inhibitory connection, but in the presence of inhibitory connection, the pattern of firing becomes stochastic oscillations.
Extending Traditional Graph-Coloring Register Allocation Exploiting Meta-heuristics for Embedded Systems
Authors: Shengning Wu, Sikun Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

This paper presents a hybrid meta-heuristic algorithm for graph-coloring register allocation problems for embedded systems. This technique uses a classic graph-coloring register allocator as the frontend to preprocess a interference graph and uses a meta-heuristic component to deal with the remaining complex graph. It applies some genetic operators to evolve a population of solutions and to preserve diversity between these solutions. It augments Tabu Search with the power of diversification and intensification based on the probabilistic solution construction and the vocabulary building principle of Tabu Search. This technique and several classic graph-coloring register allocation algorithms have been implemented in the SUIF/MachineSUIF compiler research framework, and experimental results show that the former can often generate much better solutions than the latter for a group of benchmarks for embedded systems.
A special issue on "Garbage"
Authors: JonL White
Venue: ACM SIGPLAN Lisp Pointers (1987)

In this issue of Lisp Pointers, we are featuring two articles on memory management for Lisp systems: Overview of Garbage Collection in Symbolic Computing by Timothy McEntee is an excellent short tutorial on the current state of garbage collecting techniques; and Address/Memory Management for a Gigantic LISP Environment, or GC Considered Harmful by JonL White proposes a novel technique for use in large virtual memories that abandons the notion of "collecting" garbage and focuses instead on the problem of maintaining a relatively small working set. Both of these articles have appeared elsewhere, in forums with very limited distribution, and so are being reprinted here. The first article originally appeared in longer form in the Texas Instruments Engineering Journal, which is primarily distributed to TI employees; the second article originally appeared in the historic 1980 Lisp Conference. [Since 1982, the biennial Lisp Conferences have enjoyed ACM sponsorship, and the proceedings are more widely distributed.] 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
Guest Editor's Introduction: Firmware the Lessons of Software Engineering
Authors: B. D. Shriver
Venue: Computer (1978)

The term "software engineering" was first introduced nearly 10 years ago, at a NATO-sponsored conference held in October, 1968, in Garmish, Germany.1 Since that time, a variety of tools to assist in the specification, production, and management of reliable software have been proposed. 2 Although we are yet far from the visionary's goal of automatic generation of maintainable code, we are making progress.
ManyEyes: a Site for Visualization at Internet Scale
Authors: Fernanda B. Viegas, Martin Wattenberg Frank van Ham
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We describe the design and deployment of Many Eyes, a public web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around visualizations at a large scale by fostering a social style of data analysis in which visualizations not only serve as a discovery tool for individuals but also as a medium to spur discussion among users. To support this goal, the site includes novel mechanisms for end-user creation of visualizations and asynchronous collaboration around those visualizations. In addition to describing these technologies, we provide a preliminary report on the activity of our users.
Quantization Error Correction Scheme for Lattice-Reduction Aided Linear Detection in MIMO Systems
Authors: Tien Duc Nguyen, Tadashi Fujino, Xuan Nam Tran
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

Recently, lattice reduction aided (LRA) detector has been introduced into conventional detectors for MIMO systems, to improve the performance. In LRA detectors, the first quantization step is simply a rounding operation, regardless to the original constellation. Sometimes, it causes quantiza- tion error that makes the obtained point to lie outside of the original constellation. In this paper, we propose a method to reduce the effect of quantization error. We investigated and found out that almost every time detection errors occur there are also quantization errors. Sphere detector (SD) is combined to get the optimal solution in case of quantiza- tion error. Simulation shows that the combined SD-LRA- detectors gives significant improvement with slightly addi- tional complexity.
Mentoring collaborative user centred design
Authors: Patrick Kennedy
Venue: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces (2007)

User-centred design is a key part of best practice website design, but becomes increasingly difficult when undertaken by an inexperienced, multidisciplinary team gathered from various parts of an organisation. Mentoring is one approach that can help alleviate the pressure and assist such a team in delivering solid results. This paper describes the experiences of a team and its mentor during the ground-up redesign of a website for an Australian government agency, referred to by the pseudonym 'ESA' in this paper.
An Optical/Digital Processor: Hardware and Applications
Authors: D. Casasent
Venue: IEEE Transactions on Computers (1975)

A real-time two-dimensional hybrid processor consisting of a coherent optical system, an optical/digital interface, and a PDP-11/15 control minicomputer is described. The input electrical-to-optical transducer is an electron-beam addressed potassium dideuterium phosphate (KD2PO4) light valve. The requirements and hardware for the output optical-to-digital interface, which is
Computing and the Handicapped: A Promising Alliance
Authors: M. J. Giannini
Venue: Computer (1981)

The advantages of computer technology are now reaching the handicapped. The author here surveys some NIHR-sponsored research. 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
Privacy skyline: privacy with multidimensional adversarial knowledge
Authors: Bee-Chung Chen, Kristen LeFevre, Raghu Ramakrishnan
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Privacy is an important issue in data publishing. Many organizations distribute non-aggregate personal data for research, and they must take steps to ensure that an adversary cannot predict sensitive information pertaining to individuals with high confidence. This problem is further complicated by the fact that, in addition to the published data, the adversary may also have access to other resources (e.g., public records and social networks relating individuals), which we call external knowledge. A robust privacy criterion should take this external knowledge into consideration. In this paper, we first describe a general framework for reasoning about privacy in the presence of external knowledge. Within this framework, we propose a novel multidimensional approach to quantifying an adversary's external knowledge. This approach allows the publishing organization to investigate privacy threats and enforce privacy requirements in the presence of various types and amounts of external knowledge. Our main technical contributions include a multidimensional privacy criterion that is more intuitive and flexible than previous approaches to modeling background knowledge. In addition, we provide algorithms for measuring disclosure and sanitizing data that improve computational efficiency several orders of magnitude over the best known techniques.
The V Kernel: A Software Base for Distributed Systems
Authors: D. R. Cheriton
Venue: IEEE Software (1984)

Developed to take advantage of the facilities of today's powerful personal workstations, the V kernel provides good system performance, not just good kernel performance.
Design and results of the 2nd annual satisfiability modulo theories competition (SMT-COMP 2006)
Authors: Clark Barrett, Leonardo Moura, Aaron Stump
Venue: Formal Methods in System Design (2007)

The Satisfiability Modulo Theories Competition (SMT-COMP) arose from the SMT-LIB initiative to spur adoption of common, community-designed formats, and to spark further advances in satisfiability modulo theories (SMT). The first SMT-COMP was held in 2005 as a satellite event of CAV 2005. SMT-COMP 2006 was held August 17---19, 2006, as a satellite event of CAV 2006. This paper describes the rules and competition format for SMT-COMP 2006, the benchmarks used, the participants, and the results.
Identifying New IT-Based Service Concepts Based on the Technological Strength: A Text Mining and Morphology Analysis Approach
Authors: Changyong Lee, Hyeonju Seol, Yongtae Park
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Service providers are increasingly offering customer new IT-based services to sustain competitive advantages. However, theory and practice of IT-based service is still in its early stage. Especially, new service development remains one of the least studied and understood topics due to lack of understanding in the relations between technologies and services. The purpose of this paper is to propose a systematic approach to developing new IT- based service concepts based on the firm's technological strength using patent information. First, the technology- service network is suggested to investigate the use and application of different types of technologies in IT-based services with text mining-based patent analysis. Then, based on the generated network, the firm's technological strength is measured and new IT-based service concepts are identified by conducting morphology analysis in the service industry. The proposed approach is expected to help practitioners to formulate technology-based strategy in IT-based service.
Cuspidal and noncuspidal robot manipulators
Authors: Philippe Wenger
Venue: Robotica (2007)

This article synthezises the most important results on the kinematics of cuspidal manipulators i.e. nonredundant manipulators that can change posture without meeting a singularity. The characteristic surfaces, the uniqueness domains and the regions of feasible paths in the workspace are defined. Then, several sufficient geometric conditions for a manipulator to be noncuspidal are enumerated and a general necessary and sufficient condition for a manipulator to be cuspidal is provided. An explicit DH-parameter-based condition for an orthogonal manipulator to be cuspidal is derived. The full classification of 3R orthogonal manipulators is provided and all types of cuspidal and noncuspidal orthogonal manipulators are enumerated. Finally, some facts about cuspidal and noncuspidal 6R manipulators are reported.
The Chief Architect's Reflections on Symbol IIR
Authors: R. Rice
Venue: Computer (1981)

Designed and built 15 years ago with modest funding and SSI technology, the Symbol system demonstrated the feasibility of HLL direct hardware implementation. 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
Solving a real-time allocation problem with constraint programming
Authors: Pierre-Emmanuel Hladik, Hadrien Cambazard, Anne-Marie Déplanche, Narendra Jussien
Venue: Journal of Systems and Software (2008)

In this paper, we present an original approach (CPRTA for ''Constraint Programming for solving Real-Time Allocation'') based on constraint programming to solve a static allocation problem of hard real-time tasks. This problem consists in assigning periodic tasks to distributed processors in the context of fixed priority preemptive scheduling. CPRTA is built on dynamic constraint programming together with a learning method to find a feasible processor allocation under constraints. Two efficient new approaches are proposed and validated with experimental results. Moreover, CPRTA exhibits very interesting properties. It is complete (if a problem has no solution, the algorithm is able to prove it); it is non-parametric (it does not require specific tuning) thus allowing a large diversity of models to be easily considered. Finally, thanks to its capacity to explain failures, it offers attractive perspectives for guiding the architectural design process.
A cortical network for control of voluntary movements in a robot finger
Authors: Francisco García-Córdova
Venue: Neurocomputing (2007)

Neurobiological control systems have long been studied as possible inspiration for the construction of robotic controllers. In this paper, a control of voluntary joint movements using a cortical network within constraints from neurophysiology and motor psychophysics is presented. The neural controller is proposed to control desired joint trajectories of an anthropomorphic robot finger. Each joint is driven by an agonist-antagonist actuator pair with muscle-like properties. Dynamical neural network proposes functional roles for pre-central cortical cell types in the computation of a descending command to spinal alpha and gamma motor neurons. Neurons in anterior area 5 are proposed to compute the position of the link in question using corollary discharges from area 4 and feedback from muscles spindles. Neurons in posterior area 5 use the position perception signal and desired position signal to compute a desired joint movement direction. The network reinterprets the ''neural population activity'' to afford unified control of posture, movement and force production. In addition, it suggests how the brain may set automatic and volitional gating mechanisms to vary the balance of static and dynamic feedback information to guide the movement command and to compensate for external forces. The reliability of the cortical neural controller is demonstrated by experimental results, where control system exhibits key kinematic properties of human movement, dynamic compensation and includes asymmetric bell-shaped velocity profiles.
Input data for decision trees
Authors: Selwyn Piramuthu
Venue: Expert Systems with Applications: An International Journal (2008)

Data Mining has been successful in a wide variety of application areas for varied purposes. Data Mining itself is done using several different methods. Decision Trees are one of the popular methods that have been used for Data Mining purposes. Since the process of constructing these decision trees assume no distributional patterns in the data (non-parametric), characteristics of the input data are usually not given much attention. We consider some characteristics of input data and their effect on the learning performance of decision trees. Preliminary results indicate that the performance of decision trees can be improved with minor modifications of input data.