ppxscal/embedding_network huggingface dataset:
A probabilistic plan recognition algorithm based on plan tree grammars
Authors: Christopher W. Geib, Robert P. Goldman
Venue: Artificial Intelligence (2009)

We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution. We show that this clarifies several difficult issues in plan recognition including the execution of multiple interleaved root goals, partially ordered plans, and failing to observe actions. We present the PHATT algorithm's theoretical basis, and an implementation based on tree structures. We also investigate the algorithm's complexity, both analytically and empirically. Finally, we present PHATT's integrated constraint reasoning for parametrized actions and temporal constraints.
Double mobility: coverage of the sea surface with mobile sensor networks
Authors: Ji Luo, Dan Wang, Qian Zhang
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2009)

We are interested in the sensor networks for scientific applications to cover and measure statistics on the sea surface. Due to flows and waves, the sensor nodes may gradually lose their positions; leaving the points of interest uncovered. Manual readjustment is costly and cannot be performed in time. We argue that a network of mobile sensor nodes which can perform self-adjustment is the best candidate to maintain the coverage of the surface area. A key observation of our scheme is that the motion of the flows is not only a curse but should also be considered as a fortune. The sensor nodes can be pushed by free to some locations that potentially improve the overall coverage. To this end, we present a dominating set maintenance scheme to maximally exploit the uncontrollable mobility and balance the energy consumption among all the sensor nodes. We proved that the coverage is guaranteed in our scheme. The simulation demonstrates that the network lifetime can be significantly extended, compared to a straight forward back-to-original reposition scheme.
Security-Enhanced Fuzzy Fingerprint Vault Based on Minutiae's Local Ridge Information
Authors: Peng Li, Xin Yang, Kai Cao, Peng Shi, Jie Tian
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Fuzzy vault is a practical and promising fingerprint template protection technology. However, this scheme has some security issues, in which cross-matching between different vaults may be the most serious one. In this paper, we develop an improvement version of fuzzy vault integrating minutiae's local ridge orientation information. The improved fuzzy fingerprint vault, a two factor authentication scheme to some extent, can effectively prevent cross-matching between different fingerprint vaults. Experimental results show that, if and only if the fingerprint and the password of users are simultaneity obtained by the attacker, the fuzzy vault can be cracked. Results under three scenarios indicate that, although the authentication performance of Scena.1 decreases a little in term of GAR, the security of Scena.2 and Scena.3, hence the security of the whole scheme, is enhanced greatly.
Introduction to Logic Design, 1st edition
Authors: Svetlana N. Yanushkevich, Vlad P. Shmerko
Venue:  (2008)

With an abundance of insightful examples, problems, and computer experiments, Introduction to Logic Design provides a balanced, easy-to-read treatment of the fundamental theory of logic functions and applications to the design of digital devices and systems. Requiring no prior knowledge of electrical circuits or electronics, it supplies the essential material to understand the basic operation and design of digital systems. Satisfying the Requirements of an Introductory Course The text presents a clear picture of basic concepts, effective problem-solving techniques, modern technologies, and applications. It focuses on the relationships between and the manipulation of various data structures. By examining the similarities and differences between assorted theoretical approaches for the representation, manipulation, and optimization of Boolean functions, the authors provide a unified overview of the relationships among digital system design, computer organization, micro- and nanoelectronics, and numerical methods. The book also describes classical minimization techniques, along with advanced and emerging problems of logic design. Meeting the Needs of Developing Technology Reflecting the integrated nature of modern engineering, this text shows how theoretical ideas, physical devices, and design methodologies come together to form a successful design approach. It provides the basis to explore even more sophisticated aspects in the field.
A numerical scheme for the Stefan problem on adaptive Cartesian grids with supralinear convergence rate
Authors: Han Chen, Chohong Min, Frédéric Gibou
Venue: Journal of Computational Physics (2009)

We present a level set approach to the numerical simulation of the Stefan problem on non-graded adaptive Cartesian grids, i.e. grids for which the size ratio between adjacent cells is not constrained. We use the quadtree data structure to discretize the computational domain and a simple recursive algorithm to automatically generate the adaptive grids. We use the level set method on quadtree of Min and Gibou [C. Min, F. Gibou, A second order accurate level set method on non-graded adaptive Cartesian grids, J. Comput. Phys. 225 (2007) 300-321] to keep track of the moving front between the two phases, and the finite difference scheme of Chen et al. [H. Chen, C. Min, F. Gibou, A supra-convergent finite difference scheme for the poisson and heat equations on irregular domains and non-graded adaptive Cartesian grids, J. Sci. Comput. 31 (2007) 19-60] to solve the heat equations in each of the phases, with Dirichlet boundary conditions imposed on the interface. This scheme produces solutions that converge supralinearly (~1.5) in both the L^1 and the L^~ norms, which we demonstrate numerically for both the temperature field and the interface location. Numerical results also indicate that our method can simulate physical effects such as surface tension and crystalline anisotropy. We also present numerical data to quantify the saving in computational resources.
Geometric dynamics of d'Onofrio model of tumor-immune system competition
Authors: Armando Ciancio, Carlo Cattani, Nicola Barbalace
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

This paper combines an idea of d'Onofrio [2], [3] for modeling tumor-immune system competition and immunotherapy with Udriste theory [6]-[8] of the geometric dynamics. Section 1 refines the tumor-immune flow. Section 2 describes the critical points of energy and formulates two criteria for nonexistence of periodic orbits. Section 3 analyzes the least squares technique for a flow and a geometric structure. Section 4 studies the linearization of tumor-immune geometric dynamics. Section 5 underlines the novelty of our results.
Recognition of Altered Rock Based on Improved Particle Swarm Neural Network
Authors: Yunjun Zhan, Yanyan Wu
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

PSO (particle swarm optimization) algorithm is apt to slow down and prematurity during the evolutionary anaphase. Besides, the algorithm of BP neural network also encounters some problems such as slowness in constringency, longer training time and so on. Aimed at these phenomena, PSO algorithm can be improved in two aspects: reinforcing the diversity of particles and avoiding the prematurity of particle swarm, therefore the algorithm of particle swarm neural network based on improved algorithm is presented here. Finally, this algorithm is applied to the recognition of hyper-spectral altered rock, which overcomes the disadvantage of local minimization for BP algorithm, and trained network shows great generalization ability. The instance indicates that improved PSO-BP algorithm is effective in the recognition of hyper-spectral altered rock.
Graphics and Visualization: Principles & Algorithms
Authors: T. Theoharis, G. Papaioannou, N. Platis, N. M. Patrikalakis
Venue:  (2007)

This book is a comprehensive introduction to visual computing, dealing with the acquisition, analysis, and synthesis of visual data by means of computers. What sets this book apart from other computer graphics texts is the integrated coverage of computer graphics and visualization topics, including important techniques such as subdivision surfaces, scene graphs, multi-resolution models, shadow generation, and ambient occlusion. Practitioners and students will benefit from the complete coverage of the principles that are the basic tools of their trade, from elementary computer graphics to advanced visualization techniques.
Index minimization of differential-algebraic equations in hybrid analysis for circuit simulation
Authors: Satoru Iwata, Mizuyo Takamatsu
Venue: Mathematical Programming: Series A and B (2009)

Modern modeling approaches for circuit analysis lead to differential-algebraic equations (DAEs). The index of a DAE is a measure of the degree of numerical difficulty. In general, the higher the index is, the more difficult it is to solve the DAE. The index of the DAE arising from the modified nodal analysis (MNA) is determined uniquely by the structure of the circuit. Instead, we consider a broader class of analysis method called the hybrid analysis. For linear time-invariant electric circuits, we devise a combinatorial algorithm for finding an optimal hybrid analysis in which the index of the DAE to be solved attains the minimum. The optimal hybrid analysis often results in a DAE with lower index than MNA.
Adaptive Learning in a Mobile Environment
Authors: Tat Wai Ho, Vincent To-Yee Ng, Stephen C. F. Chan, King Kang Tsoi
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Mobile devices are getting more and more popular. With the advanced wireless technology, students can assess Internet with their PDAs. This study aims to develop an adaptive e-learning system on PDA. The idea is to distribute learning materials to the students adaptively. The adaptive engine is based on two levels of Bayesian networks. The first level measures the student performance and the second level determines the redistribution of materials when a student needs retaking. We divide the student performance into the study performance and the quiz performance. The quiz performance is measured by a computerized adaptive testing (CAT) while the study performance relates to the learning behavior of a student. Preliminary experiments demonstrated that student performance has been improved via the adaptive system.
A second-order pruning step for verified global optimization
Authors: Marco Schnurr
Venue: Journal of Global Optimization (2009)

We consider pruning steps used in a branch-and-bound algorithm for verified global optimization. A first-order pruning step was given by Ratz using automatic computation of a first-order slope tuple (Ratz, Automatic Slope Computation and its Application in Nonsmooth Global Optimization. Shaker Verlag, Aachen, 1998; J. Global Optim. 14: 365---393, 1999). In this paper, we introduce a second-order pruning step which is based on automatic computation of a second-order slope tuple. We add this second-order pruning step to the algorithm of Ratz. Furthermore, we compare the new algorithm with the algorithm of Ratz by considering some test problems for verified global optimization on a floating-point computer.
Methods for Constructing Symbolic Ensembles from Symbolic Classifiers
Authors: Flavia Cristina Bernardini, Maria Carolina Monard
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

Practical Data Mining applications use learning algorithms to induce knowledge. Thus, these algorithms should be able to operate in massive datasets. Techniques such as dataset sampling can be used to scale up learning algorithms to large datasets. A general approach associated with sampling is the construction of ensembles of classifiers, which can be more accurate than the individual classifiers. However, ensembles often lack the facility to explain its decisions. In this work we explore a method for constructing ensembles of symbolic classifiers, such that the ensembles are able to explain its decisions to the user. This idea has been implemented in the ELE system described in this work.
Interactive Visualization Tools for Meta-Clustering
Authors: Ida Bifulco, Francesco Iorio, Francesco Napolitano, Giancarlo Raiconi, Roberto Tagliaferri
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

In this work we propose a scientific data exploration methodology and software environment that permits to obtain both data meta-clustering and interactive visualizations. Our approach is based on an elaboration pipeline, including data reading, multiple clustering solution generation, meta clustering and consensus clustering. Each stage is supported by dedicated visualization and interaction tools. Involved techniques include a Price based global optimization algorithm able to build a set of solutions that are local minima of the K-means objective function; different consensus methods aimed to reduce the set of solutions; tools for the interactive hierarchical agglomeration of clusterings and for the exploration and visualization of the space of clustering solutions.
Heterogeneous modulation for trading-off energy balancing with bandwidth efficiency in hierarchical sensor networks
Authors: Maryam Soltan, Inkwon Hwang, Massoud Pedram
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

With power efficiency and lifetime awareness becoming critical design concerns in wireless sensor networks (WSN), it has become essential to exploit the physical layer characteristics at the system deployment stage. This paper focuses on how certain physical layer attributes can affect both the lifetime and the end-to-end delay in a hierarchical WSN. We present a heterogeneous modulation scheme and report its impact on the spatial distribution of energy dissipation and the resulting network lifetime. Moreover, we study how this heterogeneous modulation scheme affects the end-to-end delay due to inherent trade-offs in power efficiency and bandwidth efficiency of the different modulation schemes.
Integrated Enterprise Information Systems: Thinking in Component Concepts
Authors: Audrone Lupeikiene
Venue: Proceeding of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006 (2007)

Current component-oriented theory does not provide adequate support for information systems development. To say more precisely, it is forming. The main purpose of this paper is to discuss the attempts to combine classical enterprise information systems development methodologies with component-based approach. The paper advocates and argues for the use of component-based paradigm for the development of systems at all three layers of enterprise. It presents concepts and principles of this paradigm in enterprise engineering context. The integrated enterprise information system components, their structure and types are discussed and defined.
System Programming with C and Unix, 1st edition
Authors: Adam Hoover
Venue:  (2009)

KEY BENEFIT: A conceptual approach to C and Unix programming with hands-on examples. KEY TOPICS: Readers are introduced to commonly used system tools (libraries, debuggers, system calls, shells and scripting languages) and an explanation of how to utilize these tools to optimize program development. The text also examines lower level data types with an emphasis on memory and understanding how and why different data types are used. MARKET: Ideal for introductory programmers.
Design and analysis of a self-tuning feedback controller for the Internet
Authors: Naixue Xiong, Yi Pan, Xiaohua Jia, Jong Hyuk Park, Yingshu Li
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

Active queue management (AQM) is an effective method used in Internet routers for congestion avoidance, and to achieve a tradeoff between link utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping. This paper proposes a novel packet dropping scheme, called self-tuning proportional and integral RED (SPI-RED), as an extension of RED. SPI-RED is based on a self-tuning proportional and Integral feedback controller, which considers not only the average queue length at the current time point, but also the past queue lengths during a round-trip time to smooth the impact caused by short-lived traffic dynamics. Furthermore, we give theoretical analysis of the system stability and give guidelines for selection of feedback gains for the TCP/RED system to stabilize the average queue length at a desirable level. The proposed method can also be applied to the other variants of RED. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed SPI-RED algorithm outperforms the existing AQM schemes in terms of drop probability and stability.
Dynamic performance tuning for speculative threads
Authors: Yangchun Luo, Venkatesan Packirisamy, Wei-Chung Hsu, Antonia Zhai, Nikhil Mungre, Ankit Tarkas
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

In response to the emergence of multicore processors, various novel and sophisticated execution models have been introduced to fully utilize these processors. One such execution model is Thread-Level Speculation (TLS), which allows potentially dependent threads to execute speculatively in parallel. While TLS offers significant performance potential for applications that are otherwise non-parallel, extracting efficient speculative threads in the presence of complex control flow and ambiguous data dependences is a real challenge. This task is further complicated by the fact that the performance of speculative threads is often architecture-dependent, input-sensitive, and exhibits phase behaviors. Thus we propose dynamic performance tuning mechanisms that determine where and how to create speculative threads at runtime. This paper describes the design, implementation, and evaluation of hardware and software support that takes advantage of runtime performance profiles to extract efficient speculative threads. In our proposed framework, speculative threads are monitored by hardware-based performance counters and their performance impact is estimated. The creation of speculative threads is adjusted based on the estimation. This paper proposes speculative threads performance estimation techniques, that are capable of correctly determining whether speculation can improve performance for loops that corresponds to 83.8% of total loop execution time across all benchmarks. This paper also examines several dynamic performance tuning policies and finds that the best tuning policy achieves an overall speedup of 36.8%on a set of benchmarks from SPEC2000 suite, which outperforms static thread management by 9.5%.
Learning whom to trust: using graphical models for learning about information providers
Authors: Philip Hendrix, Ya'akov Gal, Avi Pfeffer
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In many multi-agent systems, information is distributed among potential providers that vary in their capability to report useful information and in the extent to which their reports may be biased. This abstract shows that graphical models can be used to simultaneously learn complex reporting policies that agents use and learn their capabilities; weigh the benefits of different combinations of information providers; and optimally choose a combination of information providers to minimize error. An agent's policy refers to the way in which the agent reports information. We show that these models are able to capture agents that vary in their capabilities and reporting policies. Agents using these graphical models outperformed the top contestants of the recent international Agent Reputation and Trust testbed competition. Further experiments show that graphical models can accurately model agents that use complex policies to decide how to report information, and determine how to combine these reports to minimize error.
A two-level knowledge approach to support multilingual legislative drafting
Authors: T. Agnoloni, L. Bacci, E. Francesconi, W. Peters, S. Montemagni, G. Venturi
Venue: Proceeding of the 2009 conference on Law, Ontologies and the Semantic Web: Channelling the Legal Information Flood (2009)

The quality of legislative drafting process at European and national levels is highly influenced by the legal drafters control over the multilingual complexity of European legislation and over the linguistic and conceptual issues involved in its transposition into national laws. The DALOS project aims at ensuring coherence and alignment in the legislative language, providing law-makers with a knowledge (ontological-linguistic) resource and knowledge management tools to support the multilingual legislative drafting process. This paper outlines the activities within DALOS, aiming at the definition of the characteristics of a the knowledge resource, at its implementation, at its integration in a legislative drafting environment for the project prototype.
Group assignments in computer science courses: handling the "free riders" in an introduction to OOP course
Authors: G. M. Muriithi
Venue: Proceedings of the 2009 Annual Conference of the Southern African Computer Lecturers' Association (2009)

The design, development, implementation and management of modern Information Technology systems call for IT professionals who can seamlessly combine technical competence with strong communication and teamwork skills. Group assignments present a common strategy that lecturers use to nurture teamwork and communication skills in their students. However, several challenges need to be overcome if group assignments are to be effective. One key challenge is how to handle students who fail to participate in group assignments and yet stand to unfairly earn credit for work they did not do. By failing to participate in group assignments, "free-riders" may coast through the course without acquiring the requisite teamwork and presentation skills that group work set out to inculcate in the first place. This paper discusses some observations made in an introductory course in object oriented programming and demonstrates that by revising the assessment strategy in such a way that students in a group do not know upfront who among them will defend a group's practical work, the level of participation is significantly raised. This spike in participation levels leads to a reduction in the number of free-riding students.