ppxscal/embedding_network huggingface dataset:
Discrete-Time Systems with the Decomposition Property
Authors: K. L. Doty, H. Frank
Venue: IEEE Transactions on Computers (1970)

The decomposition property, a necessary condition for linearity, is defined for discrete-time systems. N-state machines with this property have finite memory µ=N-1. Linear and autonomous systems are important classes of systems with decomposition. Several representations of systems with decomposition are given and a general form of the discrete-time state equations for a finite-memory system with decomposition is derived. An algorithm is developed by which an arbitrary complete-sequential machine may be tested for decomposition.
Back-propagation neural network for the prediction of the short-term storm surge in Taichung harbor, Taiwan
Authors: Tsung-Lin Lee
Venue: Engineering Applications of Artificial Intelligence (2008)

It is essential to forecast the variation of storm surge in coastal areas during the typhoon attacks. Conventional investigations of storm surge often used the method of numerical hydrodynamic models or empirical formula. In this paper, the back-propagation neural network (BPN) is applied to predict the short-term typhoon surge and surge deviation in order to overcome the problem of exclusive and nonlinear relationships. The observations obtained during three typhoons of Taichung harbor in Taiwan are verified by the present model. From the comparison with numerical methods, it can be found that the short-term storm surge and surge deviation can be efficiently predicted 1 to 6h ahead using BPN.
B74-9 Digital Computer Fundamentals
Authors: R. E. Swartwout
Venue: IEEE Transactions on Computers (1974)

This is the third edition of a rather well known textbook and/or reference book dealing with the principles of operation of digital computers or digital data handling devices. It is primarily concerned with hardware and discusses programming to the extent necessary to illustrate the principles of computer operation. It is most useful as a text for students without significant knowledge of the internal structure of digital machines but with a moderate maturity and a little mathematical sophistication. This reviewer has used it with all levels of undergraduates, with beginning graduate students when supplemented, and in adult education courses. The material is not covered in great depth but it is not a superficial survey either. This text might serve adequately for an introductory Computer Science course or even with a proper group of high school students.
Letters: Robust stability for neural networks with time-varying delays and linear fractional uncertainties
Authors: Tao Li, Lei Guo, Changyin Sun
Venue: Neurocomputing (2007)

The problem of robust stability for neural networks with time-varying delays and parameter uncertainties is investigated in this paper. The parameter uncertainties are described to be of linear fractional form, which include the norm bounded uncertainties as a special case. By introducing a new Lyapunov-Krasovskii functional and considering the additional useful terms when estimating the upper bound of the derivative of Lyapunov functional, new delay-dependent stability criteria are established in term of linear matrix inequality (LMI). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach.
A Cluster Structure as an Interconnection Network for Large Multimicrocomputer Systems
Authors: S. B. Wu
Venue: IEEE Transactions on Computers (1981)

This paper presents a cluster structure, characterized by a set of structure parameters and a set of interconnection functions, as a conceptual interconnection scheme for large multimicrocomputer systems. It is shown that three popular interconnection structures (hypercube, hierarchy, and tree structures) are examples of the cluster structure. Two communication problems (traffic congestion and message delay), which may result in interconnection limitation to a particular structure, are analyzed. The analysis provides a way to understand structural properties such as complexity, capacity, and limitation. Through the use of the cluster structure and the analytical model, topological optimization is presented to show how interconnection limitation can be minimized.
Narrating data structures: The role of context in CS2
Authors: Svetlana Yarosh, Mark Guzdial
Venue: Journal on Educational Resources in Computing (JERIC) (2008)

Learning computing with respect to the context of its use has been linked in previous reports to student motivation in introductory Computer Science (CS) courses. In this report, we consider the role of context in a second course. We present a case study of a CS2 data structures class that uses a media computation context. In this course, students learn data structures and object-oriented (OO) programming through a pervasive narrative about how real media professionals use data structures to model the real world and to construct the digital images, sounds, and animations with which the students are familiar in their daily lives. We found that context played a different role in a second course than in a first course. We found evidence that some students did not need context to appreciate computing, but we also found evidence that context can help students get engaged with the material that they otherwise do not find interesting. In particular, the narrative aspect of a context may help students in relating the elements of the course and may even help with learning.
Research on the Control Strategy of Hydraulic Turbine Generating Units Based on Improved FNNC
Authors: Shuqing Wang, Suyi Liu, Zipeng Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Because hydraulic turbine generating units system is a complicated non-linear MIMO system, it is difficult to gain better control performance using tradition control strategy to control it. The improved fuzzy neural network controller is presented to control hydraulic turbine generating units. The learning method of network is improved according to the existent problem of fuzzy neural network in on-line learning. The designed fuzzy neural network controller can make reasoning on-line based on fuzzy reasoning system. In training, fuzzy reasoning rules, member function and parameters can be trained on-line through neural network. Simulation experiment results show that the designed improved fuzzy neural network controller may control hydraulic turbine generating units efficaciously and has quick controlling speed and less controlling max-error. So it provides a good control strategy for hydraulic turbine generating units system.
Self-Stabilization in Preference-Based Networks
Authors: Fabien Mathieu
Venue: Proceedings of the Seventh IEEE International Conference on Peer-to-Peer Computing (2007)

Participants in a decentralized system often use some local ranking information in selecting effective collaborations. We say that such systems are preference-based. For most practical types of preferences, such systems converge towards a unique stable configuration. In this paper, we investigate the speed and quality of the convergence process with respect to the model parameters. Our results provide insight into the design of system parameters, such as the number of connections or the algorithm for choosing new partners.
Pattern Recognition for Ship Based on Bayesian Networks
Authors: QingJiang Wang, Xiaoguang Gao, DaQing Chen
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Bayesian networks (BNs) are a powerful tool for pattern recognition. A BNs has two parts: parameters and structure composed of a directed acyclic graph (DAG) with some nodes. Then, according to the target feature, an approach based on BNs for pattern recognition is presented and the step of the approach is presented: constructing its nodes, modifying the node's states and distributing the node's probability. The process using the approach for pattern recognition is showed by an experiment, and the empirical results provide evidences that the approach is reasonable and effective.
Analysis of Different Scheduling Strategies in 802.11e Networks with Multi-Class Traffic
Authors: Renato Lo Cigno, Luigi Palopoli, Alessio Colombo
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

This paper tackles the problem of traffic and packet scheduling in HCCA, the contention-free portion of the 802.11e MAC protocol. Scheduling traffic belonging to different categories or priorities on a shared channel, as in Wireless LANs, is a multi-class complex optimization problem. We consider two different scheduling techniques, one based on an extremely simple positional controller and one based on the optimal solution of the linearized control problem based on a fluid approximation. Simulation results are presented discussing pros and cons of the two solutions both in terms of performances (resource exploitation and traffic differentiation properties) and in terms of implementation complexity and fairness.
Probabilistic Isolation of Malicious Vehicles in Pseudonym Changing VANETs
Authors: Bisheng Liu, YiPing Zhong, ShiYong Zhang
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Privacy is one of the most important security requirements of VANETs. To avoid being tracked, the idea of pseudonym changes is introduced, which leads to a problem that a malicious vehicle can easily create a new identity without being punished. In this paper, we present a probabilistic method to isolate malicious vehicles with the existence of pseudonym in VANETs. The main idea is to use Bloom filters to record both dishonest and trusted nodes, periodically broadcast these feedbacks and thereby receivers can update their own credits. In our scheme, we assume each car has a tamper-proof device (TPD) carrying out secure operations, such as signing and credit updating. Honest majority is also assumed. A mathematical model is presented to securely evaluate the credit of a node itself with the help of TPD. The credit will then be attached to each important message as a proof of the reliability of the message. We also discuss the potential attacks.
Top-Down System Design A Tutorial Overview
Authors: A. V. Pohm
Venue: Computer (1981)

In this introduction to hardware design topics within the ongoing tutorial series, the editors accent the essential link between software and hardware design.
Experience with Module-Level Specification Methods
Authors: J. W. Braken
Venue: Computer (1975)

During the past three years, SofTech has been developing design and specification methods with the goals of improving design quality, reducing integration problems, increasing software portability, and enhancing project control and estimating methods. In particular we wanted to increase the visibility of the detailed design process in order to facilitate design reviews and design iterations. We also hoped to improve the description and management of all module interfaces in order to reduce integration problems and to allow alternative implementations of a module to be "plug-to-plug" compatible-an important consideration when software systems requiring several man-years to build are designed to be portable. 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
Updating a priori information in fuzzy pattern recognition to improve classification performance
Authors: Sameer Singh
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

The main aim of this paper is to develop and implement the concept of incremental learning for fuzzy statistical classifiers. Such a scheme involves continuous modification of training data as learning progresses and is implemented with classifier systems that adapt to incremental information. This paper discusses the implementation of the above approach using a real-time fuzzy classifier system. The recognition performance of this approach on the three spiral benchmark is compared with conventional static training. The paper also discusses the generalisation performance of the system in the context of recognising noisy spiral data.
High Confidence Rule Mining for Microarray Analysis
Authors: Tara McIntosh, Sanjay Chawla
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2007)

We present an association rule mining method for mining high confidence rules, which describe interesting gene relationships from microarray datasets. Microarray datasets typically contain an order of magnitude more genes than experiments, rendering many data mining methods impractical as they are optimised for sparse datasets. A new family of row-enumeration rule mining algorithms have emerged to facilitate mining in dense datasets. These algorithms rely on pruning infrequent relationships to reduce the search space by using the support measure. This major shortcoming results in the pruning of many potentially interesting rules with low support but high confidence. We propose a new row-enumeration rule mining method, MaxConf, to mine high confidence rules from microarray data. MaxConf is a support-free algorithm which directly uses the confidence measure to effectively prune the search space. Experiments on three microarray datasets show that MaxConf outperforms support-based rule mining with respect to scalability and rule extraction. Furthermore, detailed biological analyses demonstrate the effectiveness of our approach -- the rules discovered by MaxConf are substantially more interesting and meaningful compared with support-based methods.
Object-Oriented Quantum Cryptography Simulation Model
Authors: Xiufeng Zhang, Qiaoyan Wen, Fuchen Zhu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

Quantum computation simulation has been a hot research topic recently and a few softwares used in research have been developed. Compared with these existed softwares and their approaches, this paper proposes an object oriented quantum cryptography simulation model. Furthermore, we also firstly integrate classical cryptography algorithms into this model. Finally, the advantages and disadvantages of this model over other simulation approaches are given.
Application and evaluation of edge detection system employing the ADD
Authors: Jong-Gu Lee, Eun-Mi Kim, Cheol-Jung Yoo, Ok-Bae Chang
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.
Slotted Optical Burst Switching (SOBS) networks
Authors: Zhenghao Zhang, Lin Liu, Yuanyuan Yang
Venue: Computer Communications (2007)

In the paper, we study Optical Burst Switching (OBS) networks. Since OBS still suffers high loss ratio due to the lack of buffer at the OBS core routers, we study methods to reduce the loss without using optical buffers. We consider time-slotted OBS called Slotted OBS (SOBS), where routers are synchronized and only send fixed length bursts at the beginning of time slots. Our simulation results show that SOBS reduces the packet loss probability significantly. Moreover, we show that SOBS can be implemented with little or no additional cost and has other advantages such as providing better support for Quality of Service (QoS).
A High Performance European OCR System
Authors: K. Wang, Q. Wang
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

The construction of Latin based European OCR system is studied in this paper. Compared with English, other Latin based European languages use more characters, which is called European special characters in this paper to be distinct from English letters. To construct a European system with high performance, the key is the recognition of the European special characters. In this paper, the European special characters are automatically divided into three subsets by the different handwritten position. And two solutions are proposed, one solution in which is used to recognize "i", "j" and the European special characters in subset 1, while another solution is used to recognize other English characters, digits and the European special character in other subsets. Experiment shows, the new system is more effective than the old one, which provides an experimental support for our research work.
Design Considerations for Semiconductor Ramdom Access Memory Systems
Authors: B. A. Kute
Venue: Computer (1971)

Random access semiconductor memory systerm components available today reflect a broad spectrum of engineering, financial and managerial judgment. Each of the products was intended to satisfy the performance and cost goals of a particular segment of the memory market. The decisions which were made regarding technology to be used, chip density, package density, package type, electrical performance and environmental performance, reflect the weighted factors of market segment need versus investment required. The resulting product is in many cases a compromise. For example, a lower chip density may result in lower cost per bit at the chip level due to higher yields. However, higher chip densities, inherent when decoding is on the chip, may be required due to the lack of a package with enough leads to accommodate a non-decoded chip. The assumption is that need to capitalize a new package production line represents higher financial risk than that which results from the lower yields at the chip level. 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
Identity management: multiple presentations of self in facebook
Authors: Joan Morris DiMicco, David R. Millen
Venue: Proceedings of the 2007 international ACM conference on Supporting group work (2007)

As the use of social networking websites becomes increasingly common, the types of social relationships managed on these sites are becoming more numerous and diverse. This research seeks to gain an understanding of the issues related to managing different social networks through one system, in particular looking at how users of these systems present themselves when they are using one site to keep in contact with both their past social groups from school and their current social connections in the workplace. To do this, we examined online profile pages and interviewed employees at a large software development company who frequently use the website Facebook, a site primarily used by college students and young graduates transitioning into the work force. The outcome of this initial case study is a framework for understanding how users manage self-presentation while maintaining social relationships in heterogeneous networks.
Development of MR application families: an InTml-based approach
Authors: Pablo Figueroa, José Ferreira, Camilo Castro
Venue: Proceedings of the 2007 ACM symposium on Virtual reality software and technology (2007)

We show an approach for the development of families of MR applications. A family of MR applications is a set of applications that share some common tasks but differ mainly in their user interfaces. The development of a family of applications allows reusability of design and code, adaptability to new hardware and context, and distributed and heterogeneous deployments. Some examples are presented and future trends are discussed.
An Edge Detection Algorithm Based on Improved CANNY Operator
Authors: Xun Wang, Jian-Qiu Jin
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

Edge detection is an important aspect for image processing, and primary step of spatial data extraction in geography information system. For contour detection, this paper proposed the improved template algorithm, which is not only including the gradient directions of X and Y, but also the first order partial finite differences of directions 45 and 135 degree in calculating the amplitude values. These mostly improved the calculation accuracy of the amplitude values. In the non-maxima suppression process, the factor ratio of four quadrants of linear interpolation is improved to achieve better detection results. Experiments showed that this improved CANNY algorithm has better noise suppression and edge continuity.
Construction and scheduling of extrapolated parity packets for dead reckoning in network gaming
Authors: Gene Cheung, Takashi Sakamoto
Venue: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games (2007)

Game update packets of typical First Person Shooting (FPS) network games, small and of delay-sensitive and self-healing characteristics, are disseminated periodically among players for dead reckoning (DR) to predict the current locations of the opposing avatars. To improve delivery of these updates over networks with substantial packet losses and transmission delays, we propose the use of Extrapolated Parity Packets (EPPs). EPPs are application-aware parity packets that can fully recover missing game updates or prediction information. Our proposed scheduling of EPP makes maximal use of the available network bandwidth. Experiments showed noticeable improvements in prediction accuracy at receiver using EPP schemes over non-EPP schemes.
The Evolution of Computerized Presentation Graphics at Dicomed
Authors: Wayne Huelskoetter
Venue: IEEE Computer Graphics and Applications (1983)

With origins in space exploration and earth satellite programs, image-recording technology now makes computer-generated graphics available to almost any organization. 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
Conceptual modeling by analogy and metaphor
Authors: Karin K. Breitman, Simone D. J. Barbosa, Marco A. Casanova, Antonio L. Furtado
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Metaphor is not merely a rhetorical device, characteristic of language alone, but rather a fundamental feature of the human conceptual system. A metaphor is understood by finding an analogy mapping between two domains. This paper argues that analogy mappings facilitate conceptual modeling by allowing the designer to reinterpret fragments of familiar conceptual models in other contexts. The contributions of the paper are expressed within the tradition of the Entity-Relation model.