ppxscal/embedding_network huggingface dataset:
SAT-based Abstraction Refinement for Real-time Systems
Authors: Stephanie Kemper, André Platzer
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

In this paper, we present an abstraction refinement approach for model checking safety properties of real-time systems using SAT-solving. We present a faithful embedding of bounded model checking for systems of timed automata into propositional logic with linear arithmetic and prove correctness. With this logical representation, we achieve a linear-size representation of parallel composition and introduce a quick abstraction technique that works uniformly for clocks, events, and states. When necessary, abstractions are refined by analysing spurious counterexamples using a promising extension of counterexample-guided abstraction refinement with syntactic information about Craig interpolants. To support generalisations, our overall approach identifies the algebraic and logical principles required for logic-based abstraction refinement.
Modeling of Artificial Life Based Virtual Fish Behavior
Authors: Xiaolin Quan, Shaochun Zhong, Wenyong Wang, Qian Xu, Ying Liang, Qingrong Zhang
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

Conventional virtual biology behavior cartoon has some shortages because that it is realized by means of key frames technology. We proposed a virtual biology behavior model based on artificial life method. Giving an example of virtual fish, we have realized many kinks of virtual fish behaviors simulations by combining artificial life method and the virtual reality technique, without need of any key frame. The virtual model owns not only the basic characteristics of virtual biology, but also high trueness, which can be used in the virtual biology education and experiment.
A Partial Solution to Last Issue's Homework Assignment: Beetles, Cannibalism, and Chaos--Analyzing a Dynamical System Model
Authors: Dianne P. O'Leary
Venue: Computing in Science and Engineering (2007)

The last issue's installment of Your Homework Assignment featured the final problem in Dianne O'Leary's popular long-running department. In this issue, she offers a partial solution to it.
A neurofuzzy-evolutionary approach for product design
Authors: Shih-Wen Hsiao, Elim Liu
Venue: Integrated Computer-Aided Engineering (2004)

This study investigates a systematic approach to product design based on artificial intelligence. This investigation proposes the use of artificial intelligence techniques, including fuzzy theory, back propagation neural networks (BPN), and genetic algorithms (GA), along with morphological analysis to synthesize, evaluate and optimize product design. This study focuses on (1) how to model imprecise market information by applying fuzzy theory; (2) mapping relationships between design parameters and customer requirements using BPN; (3) synthesizing design alternatives by morphological analysis, and (4) realizing the synthesis in GA, using its searching capacity to obtain the optimal solution. Two case studies illustrate the practical value of the proposed methodology.
Adaptive implementations of two blind channel estimation algorithms on MC-CDMA
Authors: H.-K. Garg, S. Attallah, A. M. Zoubir
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 01 (2002)

Recently, two non-adaptive algorithms have been proposed for blind channel estimation for multicarrier CDMA. The first one was proposed by Tureli et al. and the second one by Escudero et al. We develop in this paper two adaptive versions for the first algorithm that are based on the gradient. Whereas, for the second one, we propose an adaptive version that is based on a low-cost subspace adaptive algorithm (NOOJA). In both cases, our adaptive versions perform well while offering at the same time a low computational complexity as compared to their original non-adaptive versions.
A new indexing method with high storage utilization and retrieval efficiency for large spatial databases
Authors: Hung-Yi Lin, Po-Whei Huang, Kuang-Hua Hsu
Venue: Information and Software Technology (2007)

Storing and querying high-dimensional data are important problems in designing an information retrieval system. Two crucial issues, time and space efficiencies, must be considered when evaluating the performance of such a system. The KDB-tree and its variants have been reported to have good performance by using them as the index structure for retrieving multidimensional data. However, they all suffer from low storage utilization problem caused by imperfect ''splitting policies.'' Unnecessary splits increase the size of the index structure and deteriorate the performance of the system. In this paper, a new data insertion algorithm with a better splitting policy was proposed, which arranges data entries in the leaf nodes as many as possible. Our new index scheme can increase the storage utilization up to nearly 100% and reduce the index size to a smaller scale. As a result, both time and space efficiencies are significantly improved. Analytical and experimental results show that our indexing method outperforms the traditional KDB-tree and its variants.
Point-and-edge model for edge-preserving splatting
Authors: Haitao Zhang, Arie E. Kaufman
Venue: The Visual Computer: International Journal of Computer Graphics (2007)

We introduce the point-and-edge model for edge-preserving modeling and rendering. Besides a set of surface points, the point-and-edge model also includes edge points representing the sharp edges in the model. The surface points and the sharp edges are relatively independent of each other. We present a feedback algorithm to simplify the point-and-edge model with bounded error based on an edge-preserving clustering method. An efficient constrained splatting method is used to preserve the sharp edges in the rendering, regardless of the surface point density.
Message from the Program Chairs
Authors: J. Sterbenz, D. Stiliadis
Venue: Proceedings of the High Performance Interconnects, 2004. on Proceedings. 12th Annual IEEE Symposium (2004)

Summary form only given. The Internet has grown enormously over the last decade and has become ubiquitous. Most past research has focused on improving the performance and scalability of the Internet. The issue of securing the Internet has become a central issue due to a series of attacks that shut down some of the world's most high profile Web sites. Moreover, the growing concerns for cyber terrorism have made governments and researchers realize the importance of Internet security. Securing the Internet, as in any other field of computers, is based on the principle of confidentiality and integrity. This principle exists in every field, but the presence of packet sniffers, malicious routers, covert channels, eavesdroppers, denial-of-service (DoS) in the Internet makes this problem quite challenging. There has been a surge of Internet security research in the field of information assurance, which primarily focused on protecting the data using techniques such as authentication and encryption. However, information assurance assumes that the devices responsible for encrypting, forwarding and sending are trustworthy. Researchers are now questioning these assumptions, as instances have occurred where the network infrastructure (e.g., routers, servers) is compromised to the advantage of the malicious adversaries. Therefore, Internet infrastructure security is the need of the hour.
Efficient routing for peer-to-peer overlays
Authors: Anjali Gupta, Barbara Liskov, Rodrigo Rodrigues
Venue: Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1 (2004)

Most current peer-to-peer lookup schemes keep a small amount of routing state per node, typically logarithmic in the number of overlay nodes. This design assumes that routing information at each member node must be kept small, so that the bookkeeping required to respond to system membership changes is also small, given that aggressive membership dynamics are expected. As a consequence, lookups have high latency as each lookup requires contacting several nodes in sequence. In this paper, we question these assumptions by presenting two peer-to-peer routing algorithms with small lookup paths. First, we present a one-hop routing scheme. We show how to disseminate information about membership changes quickly enough so that nodes maintain accurate routing tables with complete membership information. We also deduce analytic bandwidth requirements for our scheme that demonstrate its feasibility. We also propose a two-hop routing scheme for large scale systems of more than a few million nodes, where the bandwidth requirements of one-hop routing can become too large. This scheme keeps a fixed fraction of the total routing state on each node, chosen such that the first hop has low latency, and thus the additional delay is small. We validate our analytic model using simulation results that show that our algorithms can maintain routing information sufficiently up-to-date such that a large fraction (e.g., 99%) of the queries will succeed without being re-routed.
Conceptual Framework for Knowledge Management Support in Logistics and Supply Chain Simulation
Authors: Gaby Neumann
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

This paper relates logistics and supply chain modeling and simulation to knowledge flow analysis and knowledge management methodology. Knowledge gained in the course of a simulation project quite often remains in the heads of the people involved in the project. It is not sufficiently externalized because documentation tasks are time-consuming, seen as an add-on to the real problem-solving process and poorly supported. As a result, project-specific knowledge about assumptions, decisions, modeling philosophy, implementation, experiments and results is not kept but lost, even if it is retained by the people involved. As a contribution to overcoming this problem, logistics simulation knowledge is identified and processes of knowledge sharing, creation and acquisition in the course of a logistics simulation project are analyzed. Although closely related to logistics and supply chain simulation, the methods proposed are easily adapted to other application areas of modeling and simulation -- and should be applied to them as well.
Task-oriented modeling for the discovery of web user navigational patterns
Authors: Bamshad Mobasher
Venue:  (2006)

Web user modeling which studies users' diverse online navigation behavior and infers their interests has become crucial in many applications, such as Web recommendation, Web site evaluation and reorganization. There exists a wide range of Web user modeling approaches, including supervised learning approaches such as classification, and unsupervised learning approaches such as association rule mining and clustering. Most of existing approaches discover users' browsing patterns by either exploring the similarity between users' navigation paths, or inferring Web page associations based on their co-occurrence in users' visits. However, these discovered patterns are page-level patterns, such as an association rule pageA &rArr; pageB (support 50%, confidence 70%), implying these two pages are likely to be visited together. These patterns are too simple to represent users' diverse, complex navigation behavior, nor can they characterize users' underlying interests or information needs which lead to the specific navigation behavior. In this thesis, we present a Task-Oriented Web user modeling framework for studying Web users' navigation behavior from multiple sources of knowledge, including users' navigation data, Web site content data and other possible sources. In this framework, we introduce the notion of task, which is defined as a set of functionalities provided by a Web site, for meeting users' diverse information needs. These tasks are not directly visible, but implicitly lay underlying users' interactions with the site, and the site's content and structure information. Our framework consists of two task-oriented models, i.e. task learning from user navigation data, and task learning from Web site content information. In these two models, we use hidden variable models to automatically discover tasks from Web user navigation data and content data respectively, quantitatively characterize users' interests, discover page-level and task-level usage patterns, and conduct various types of user behavior analyses. Furthermore, usage patterns from these two task models are seamlessly integrated under the maximum entropy principle, allowing us to develop various types of Web applications.
On the design of a transversal filter bank for parallel processing multiple image lines in real-time acoustic imaging
Authors: Jian Shen
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

We present a new method for designing a transversal filter bank for parallel processing echo data in real-time active acoustic imaging. The method is based on a discretized linear spatio-temporal formulation of an imaging system which uses transmitter arrays with coded-excitation. The filter coefficients are derived from a pseudo-inverse operator which not only decouples echoes from different image lines, but also provides pulse compression along the range direction. The new method, together with the proposed coded-excitation imaging modality, may find many applications in sonar, NDE and biomedical imaging areas.
A framework for ontology-driven multimedia analysis and composition
Authors: Stamatia Dasiopoulou, Ioannis Kompatsiaris, Lyndon J. B. Nixon
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

The task of resource retrieval and composition is particularly challenging in the case of multimedia resources. Usual approaches focus on the use of textual multimedia annotations to enable computer-based management of multimedia repositories. In this paper, we introduce two approaches which make use of a logical formalism called an ontology to improve on the state of the art in multimedia retrieval and composition. Through the use of ontologies, these approaches form a part of the emerging Semantic Web, and offer important contributions to enabling multimedia-based Semantic Web applications.
An innovative integrated learning laboratory environment
Authors: M. Walworth
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

The current paradigm in engineering course instruction builds on a lecture prerequisite structure but ignores the need for a laboratory prerequisite structure. Educational quality is therefore diminished as instructors optimize specific laboratories but fail to optimize the overall program laboratory experience. This paper presents a learning environment that forces students to use not only concepts and skills acquired from the lecture, but also actual data and models acquired from lower division laboratories, in upper division laboratories. The integration occurs because students must utilize their previous laboratory work as a reference and/or building blocks as they study the different facets of the same experimental set-ups in multiple engineering laboratories. The students learn to appreciate the integrated nature of modern systems since they get to use the same set-ups in multiple courses. There are other indirect advantages of this approach in terms of financial economy and faculty professional development.
Interactive presentation: Implementation of a transaction level assertion framework in SystemC
Authors: Wolfgang Ecker, Volkan Esen, Thomas Steininger, Michael Velten, Michael Hull
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Current hardware design and verification methodologies reflect a trend towards abstraction levels higher than RTL, referred to as transaction level (TL). Since transaction level models (TLMs) are used for early prototyping and as reference models for the verification of their RTL representation, the quality assurance of TLMs is vital. Assertion based verification (ABV) of RTL models has improved quality assurance of IP blocks and SoC systems to a great extent. Since mapping of an RTL ABV methodology to TL poses severe problems due to different design paradigms, current ABV approaches need extensions towards TL. In this paper we present a prototype implementation of a TL assertion framework using SystemC which is currently the de facto standard for system modeling.
The Design of a Genetic Muller C-Element
Authors: Nam-Phuong D. Nguyen, Hiroyuki Kuwahara, Chris J. Myers, James P. Keener
Venue: Proceedings of the 13th IEEE International Symposium on Asynchronous Circuits and Systems (2007)

Synthetic biology uses engineering principles to design circuits out of genetic materials that are inserted into bacteria to perform various tasks. While synthetic combinational Boolean logic gates have been constructed, there are many open issues in the design of sequential logic gates. One such gate common in most asynchronous circuits is the Muller C-element, which is used to synchronize multiple independent processes. This paper proposes a novel design for a genetic Muller C-element using transcriptional regulatory elements. The design of a genetic Muller C-element enables the construction of virtually any asynchronous circuit from genetic material. There are, however, many issues that complicate designs with genetic materials. These complications result in modifications being required to the normal digital design procedure. This paper presents two designs that are logically equivalent to a Muller C-element. Mathematical analysis and stochastic simulation, however, show that only one functions reliably.
Scalable cooperative multiagent reinforcement learning in the context of an organization
Authors: Victor Lesser
Venue:  (2006)

Reinforcement learning techniques have been successfully used to solve single agent optimization problems but many of the real problems involve multiple agents, or multi-agent systems. This explains the growing interest in multi-agent reinforcement learning algorithms, or MARL. To be applicable in large real domains, MARL algorithms need to be both stable and scalable. A scalable MARL will be able to perform adequately as the number of agents increases. A MARL algorithm is stable if all agents (eventually) converge to a stable joint policy. Unfortunately, most of the previous approaches lack at least one of these two crucial properties. This dissertation proposes a scalable and stable MARL framework using a network of mediator agents. The network connections restrict the space of valid policies, which reduces the search time and achieves scalability. Optimizing performance in such a system consists of optimizing two subproblems: optimizing mediators' local policies and optimizing the structure of the network interconnecting mediators and servers. I present extensions to Markovian models that allow exponential savings in time and space. I also present the first integrated framework for MARL in a network, which includes both a MARL algorithm and a reorganization algorithm that work concurrently with one another. To evaluate performance, I use the distributed task allocation problem as a motivating domain.
A Web-based tutorial and tele-operation system for earthquake engineering education
Authors: S. R. Smith
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

We describe a system for the demonstration, explanation, and control of a laboratory setup comprising a scale-model of a building affixed to a "shaker-table" that simulates earthquakes. Senior design class students are creating a system to control the shaker-table. The signal generator controlling the table's translation is interfaced to a Web page, allowing the user to easily select different ground motion patterns. The building's reactions exhibit various modes of vibration. A 3D graphics model of the building is also shown on the Web page using VRML. This model is animated using Java programs so that it also exhibits the vibration modes of the real building. A set of associated Web pages provide a tutorial for the structural and earthquake engineering concepts that can be demonstrated with the shaker-table scale building in creative combination with the computer graphics models.
On the Complexity of Decontaminating an Hexagonal Mesh Network
Authors: Paola Flocchini, Nicola Santoro, Lisa Xiuli Song
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2007)

We consider the problem of decontaminating a network infected by mobile viruses. The goal is to perform the task using as small a team of antiviral agents as possible, avoiding any recontamination of decontaminated areas; other cost measures include the amount of agents' movements across the network and the time required by the decontamination process. The network we consider is a regular cellular space, namely an Hexagonal Mesh. We examine the decontamination problem of such a network in two different settings, depending on the sensorial capabilities of the agents. In the first setting, the only knowledge that an agent has is local to the node in which it is currently residing; in the other setting, each agent can also "see" the state of the neighbouring nodes. We examine the complexity of decontamination in both settings; for each, we design strategies that are optimal in terms of number of agents employed and efficient in the other two cost measures. We show that visibility power allows a drastic decrease in time complexity, extending the known results for regular meshes.
Fractal dimension characterizes seizure onset in epileptic patients
Authors: R. Esteller
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

We present a quantitative method for identifying the onset of epileptic seizures in the intracranial electroencephalogram (IEEG), a process which is usually done by expert visual inspection, often with variable results. We performed a fractal dimension (FD) analysis on IEEG recordings obtained from implanted depth and strip electrodes in patients with refractory mesial temporal lobe epilepsy (MTLE) during evaluation for epilepsy surgery. Results demonstrate a reproducible and quantifiable pattern that clearly discriminates the ictal (seizure) period from the pre-ictal (pre-seizure) period. This technique provides an efficient method for IEEG complexity characterization, which may be implemented in real time. Additionally, large volumes of IEEG data can be analyzed through compact records of FD values, achieving data compression on the order of one hundred fold. This technique is promising as a computational tool for determination of electrographic seizure onset in clinical applications.