ppxscal/embedding_network huggingface dataset:
A fast robust LMS algorithm utilizing the dynamics of a damped pendulum
Authors: T. F. Haddad, M. A. Khasawneh
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

A new fast LMS-based adaptive algorithm is proposed. It is derived by incorporating a damping force in the LMS update recursion in analogy with the force acting upon a damped planar pendulum. An expression for the evolution and the steady-state behaviour for the mean weight vector is developed. This expression provides a mathematical bound which constrains the parameter that controls the maximum contribution of the introduced damping force. Simulation results show an improved robust performance for the new algorithm as compared with the conventional LMS algorithm in smoothly tracking the optimal solution in correlated and nonstationary power environments, especially, in the presence of plant noise.
Belief revision for AgentSpeak agents
Authors: Natasha Alechina, Rafael H. Bordini, Jomi Fred Hübner, Mark Jago, Brian Logan
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

The AgentSpeak agent-oriented programming language has recently been extended with a number of new features, such as speech-act based communication, internal belief additions, and support for ontological reasoning, which imply a need for belief revision within an AgentSpeak agent. In this paper, we show how a polynomial-time belief-revision algorithm can be incorporated into the Jason AgentSpeak interpreter. To the best of our knowledge, this is the first attempt to include belief revision within an interpreter for a practical agent programming language.
Information Technology and National Development in Iran
Authors: Asefeh Asemi
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

This article discusses the transmission and attraction of information technology (IT) and national development in Iran country. In view of this transmission, the Iran determined to research aimed at formulating policy recommendations on the removal of bottlenecks and problems preventing or slowing down the growth use of new technology in this country. From this study it can be concluded that the major bottlenecks for the application of IT can be found in using of technology. The use of technology is influenced by such factors as policy and infrastructure. However, also the economic and socio-cultural situation has a large impact on using new technology. To bridge the information technology gap of all the related organizations and user groups from industries & social institutes should liaise in development activities and supporting projects. The government should invest in the infrastructure development, by providing the necessary resources and training to the population.
A Random Field Model for Improved Feature Extraction and Tracking
Authors: Xiaotong Yuan, Stan Z. Li
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper presents a novel method for illumination-invariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. Features to be extracted are represented as a weight field. An energy function of the field is defined as an approximate variance in robust statistics. A simple non-linear iterative rule is derived to compute the optimal field. The optimal field is shown to be invariant to global illumination switching, and preserving target/background contrast. We incorporate the feature extraction method into a mean-shift tracker and this achieves reliable results on real-world sequences in complex scenes and varying illumination.
Dependence modeling for stochastic simulation
Authors: Bahar Biller, Soumyadip Ghosh
Venue: Proceedings of the 36th conference on Winter simulation (2004)

An important step in designing stochastic simulation is modeling the uncertainty in the input environment of the system being studied. Obtaining a reasonable representation of this uncertainty can be challenging in the presence of dependencies in the input process. This tutorial attempts to provide a coherent narrative of the central principles that underlie methods that aim to model and sample a wide variety of dependent input processes.
Computation in a reduced KII network based on synchronization: Research Articles
Authors: Dongming Xu, José C. Principe
Venue: International Journal of Intelligent Systems (2006)

When implementing dynamical systems for information processing, a well-defined set of computational primitives should be constructed to represent the state space. Based on the specific collective behavior of Freeman's computational model of the olfactory cortex, we study the computation of reduced KII networks by using the synchronization of output channels. The design of coupling coefficients in the network for obtaining a desired output state response is presented. We demonstrate the computational power of reduced KII networks by two applications that address logic computation and associative memory, respectively. &copy; 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 919&ndash;935, 2006.
NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs
Authors: Jin Chen, Wynne Hsu, Mong Li Lee, See-Kiong Ng
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Recent works in network analysis have revealed the existence of network motifs in biological networks such as the protein-protein interaction (PPI) networks. However, existing motif mining algorithms are not sufficiently scalable to find meso-scale network motifs. Also, there has been little or no work to systematically exploit the extracted network motifs for dissecting the vast interactomes.We describe an efficient network motif discovery algorithm, NeMoFinder, that can mine meso-scale network motifs that are repeated and unique in large PPI networks. Using NeMoFinder, we successfully discovered, for the first time, up to size-12 network motifs in a large whole-genome S. cerevisiae (Yeast) PPI network. We also show that such network motifs can be systematically exploited for indexing the reliability of PPI data that were generated via highly erroneous high-throughput experimental methods.
Domain-Based Dynamic Resource Management Mechanism Supporting Large-Scale Grid Application
Authors: Guo-min Zhang, Yong Zhang, Ming Chen, Huan Xiong
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

A grid computing environment enables sharing of loosely coupled resources and services required by various applications in a large-scale. In such an environment, one of the key challenges is to develop a flexible, scalable, and self-adaptive resource management system which would allow users to carry out their jobs by transparently accessing autonomous, distributed, and heterogeneous resources. A Domain-based dynamic resource self maintain mechanism (DDRM) supporting large-scale distributed application is proposed. Grid distributed applications can be ensured to run regularly and stably by maintaining dynamic resource information, detecting abnormality and adjusting system timely. Conceptions of Monitoring Domain and domain agent are defined. Global resource view is acquired through resource pool and the corresponding triggering update algori-thm. Dynamic resource maintenance mechanism are adopted to handle resource abnormality. DDRM can scale to any large distributed application system with strong real-time and reliability. Finally, complexity and convergence time of DDRM are analyzed.
Sensitive Periods in the Development of the Brain and Behavior
Authors: Eric I. Knudsen
Venue: Journal of Cognitive Neuroscience (2004)

Experience exerts a profound influence on the brain and, therefore, on behavior. When the effect of experience on the brain is particularly strong during a limited period in development, this period is referred to as a sensitive period. Such periods allow experience to instruct neural circuits to process or represent information in a way that is adaptive for the individual. When experience provides information that is essential for normal development and alters performance permanently, such sensitive periods are referred to as critical periods. Although sensitive periods are reflected in behavior, they are actually a property of neural circuits. Mechanisms of plasticity at the circuit level are discussed that have been shown to operate during sensitive periods. A hypothesis is proposed that experience during a sensitive period modifies the architecture of a circuit in fundamental ways, causing certain patterns of connectivity to become highly stable and, therefore, energetically preferred. Plasticity that occurs beyond the end of a sensitive period, which is substantial in many circuits, alters connectivity patterns within the architectural constraints established during the sensitive period. Preferences in a circuit that result from experience during sensitive periods are illustrated graphically as changes in a ''stability landscape,'' a metaphor that represents the relative contributions of genetic and experiential influences in shaping the information processing capabilities of a neural circuit. By understanding sensitive periods at the circuit level, as well as understanding the relationship between circuit properties and behavior, we gain a deeper insight into the critical role that experience plays in shaping the development of the brain and behavior.
Activity Topology Estimation for Large Networks of Cameras
Authors: Anton van den Hengel, Anthony Dick, Rhys Hill
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Estimating the paths that moving objects can take through the fields of view of possibly non-overlapping cameras, also known as their activity topology, is an important step in the effective interpretation of surveillance video. Existing approaches to this problem involve tracking moving objects within cameras, and then attempting to link tracks across views. In contrast we propose an approach which begins by assuming all camera views are potentially linked, and successively eliminates camera topologies that are contradicted by observed motion. Over time, the true patterns of motion emerge as those which are not contradicted by the evidence. These patterns may then be used to initialise a finer level search using other approaches if required. This method thus represents an efficient and effective way to learn activity topology for a large network of cameras, particularly with a limited amount of data.
Coordination Strategy for Production Planning in Supply Chain Based on Lagrange Relaxation Algorithm
Authors: Cuihua Zhang, Guangshu Chang, Yan Fan, Haibin Yu
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

To solve the coordination problem of multi-enterprises supply chain production planning, a coordination and optimization strategy of distributed decision-making based on Lagrange relaxation algorithm is presented. By relaxing the material flow balance constraints among enterprises with the internal price, i.e. Lagrange multipliers, the whole supply chain production planning problem is decomposed into multiple single enterprise production planning sub problems, each of which can make its own production plan through local information. Through iterative update of the internal price for each kind of products provided by enterprises, the supply chain could be coordinated and the nearest optimal solution can be achieved. The simulation experiments show that the method can better solve the multi-enterprise supply chain production planning problem.
Dynamic Routing as paradigm for decentralized flexible process management
Authors: Alistair Barros, Gero Decker
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

Since companies face continuously changing business processes, centralized process repositories and execution engines have been integrated into the heart of enterprise systems. These systems are then able to support repetitive processes. In order to extend the reach of process orientation into more collaborative settings, employees must be given the possibility to adapt and refine the processes to their individual needs. Personalized process templates are applied to tasks and running process instances are subject to massive changes by the participants. These flexible processes require for process management infrastructures of a more peer to peer style. We argue that the concept of Dynamic Routing is a valuable paradigm for supporting highly flexible processes. We identified three patterns for Dynamic Routing and sketch future enterprise system architectures implementing these. We present two case studies where dynamically routed interactions are at the center of attention.
New technology and old habits: the role of age as a technology chasm
Authors: Daniel P. Lorence, Heeyoung Park
Venue: Technology and Health Care (2006)

Familiarity with and use of computers is increasingly cited as a limiting factor related to the potential of the Internet as an effective healthcare resource for the elderly. This study sought to examine differences across age groups in their access to and use of computers and the Internet as a health information resource. We perform multivariate analysis with data from a stratified sample of survey-reported health information-seeking behaviors on the Internet. The results suggest that access to online health information among Internet users varies significantly from the use of computers and Internet. Younger participants showed the highest rates in the use of computer and Internet, and exhibited the lowest rates in the access to online health information. In 2000, 56.7% and 55.9% of medium and older Internet users ever looked for health information on the Web, respectively, whereas 49.4% of young Internet users ever did. By 2002, these fractions had increased by 14.6%, 13.5% and 9.1%, respectively. The comparison of ORs between 2000 and 2002 indicated that the gap is somewhat increased, although the increase was not statistically significant at 0.05 level (the ORs of old to young at2000 = 1.30 [0.933, 1.817]; the ORs at2002 = 1.61 [1.157, 2.255]). Findings show that the gap between old and young seekers users of computers and the Internet for information appears to have widened in recent years, even as advocates of consumer-centric healthcare continue to promote the Internet as a key source of empowerment for the elderly.
Efficient agents for cliff-edge environments with a large set of decision options
Authors: Ron Katz, Sarit Kraus
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

This paper proposes an efficient agent for competing in Cliff Edge (CE) environments, such as sealed-bid auctions, dynamic pricing and the ultimatum game. The agent competes in one-shot CE interactions repeatedly, each time against a different human opponent, and its performance is evaluated based on all the interactions in which it participates. The agent, which learns the general pattern of the population's behavior, does not apply any examples of previous interactions in the environment, neither of other competitors nor its own. We propose a generic approach which competes in different CE environments under the same configuration, with no knowledge about the specific rules of each environment. The underlying mechanism of the proposed agent is a new meta-algorithm, Deviated Virtual Learning (DVL), which extends existing methods to efficiently cope with environments comprising a large number of optional decisions at each decision point. Experiments comparing the performance of the proposed algorithm with algorithms taken from the literature, as well as another intuitive meta-algorithm, reveal a significant superiority of the former in average payoff and stability. In addition, the agent performed better than human competitors executing the same task.
Neuro Fuzzy Reasoner for Student Modeling
Authors: Zoran Sevarac
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper presents a neuro-fuzzy system that can be used for student modeling. The proposed system enables classification of students based on qualitative observations of their characteristics. The system is very flexibile and can be easily adapted to individual teacher's preferences. It is available as a Java component and it can be used in e-learning applications.
Whole-program optimization of global variable layout
Authors: Nathaniel McIntosh, Sandya Mannarswamy, Robert Hundt
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

On machines with high-performance processors, the memory system continues to be a performance bottleneck. Compilers insert prefetch operations and reorder data accesses to improve locality, but increasingly seek to modify an application's data layout to reduce cache miss and page fault penalties. In this paper we discuss Global Variable Layout (GVL), an optimization of the placement of entire static global data objects in the binary. We describe two practical methods for GVL in the HP-UX Integrity optimizing compiler for the Itanium © architecture. The first layout strategy relies on profile feedback, collaboratively employing the compiler, the linker and a pre-link tool to facilitate reordering. The second strategy uses whole-program analysis to drive data layout decisions, and does not require the use of a dynamic profile. We give a detailed description of our implementation and evaluate its performance for the SPEC integer benchmark programs, as well as for a large commercial database application.
Towards Cognitive Modeling of Students' Self-Efficacy
Authors: Francine Bica, Regina Verdin, Rosa Maria-Vicari
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper presents a study of a Student Model based on beliefs of Self-Efficacy to improve the effectiveness of Intelligent E-Learning System. The Self-efficacy means the student's belief on his capacity of performing a task. This belief affects his behavior, motivation, affectivity and the choices he makes. We design an e-Learning System, called InteliWeb, this environment is composed by the Self-Efficacy Mediator Agent, an animated pedagogical agent and offers instruction material on Biological sciences. We use fuzzy theory for dealing with uncertainty in the assessment of the students and the incomplete knowledge about his Self-Efficacy.
Simulation and optimization as effective DFSS tools
Authors: Karl Luce, Lucie Trepanier, Fred Ciochetto, Lawrence Goldman
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Simulation and optimization techniques can provide Design for Six Sigma (DFSS) practitioners with reduced reliance on physical prototypes, rapid time-to-market, minimal defects and post-design rework. These advantages lead to quantifiable benefits within the product development life-cycle, in terms of time and cost. Through one case study, this paper will provide Six Sigma, Process Excellence and Lean practitioners with the rationale for spreadsheet simulation and optimization in DFSS initiatives. Discussion topics include the role of simulation and optimization in the DMADV methodology, disadvantages of not quantifying uncertainty in DFSS projects, differences between deterministic and stochastic optimization, and tradeoff considerations when running optimizations. Practical techniques for efficiently identifying robust, high quality solutions are demonstrated through the use of Monte Carlo simulation and optimization.
Shape from Shading: Recognizing the Mountains through a Global View
Authors: Qihui Zhu, Jianbo Shi
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Resolving local ambiguities is an important issue for shape from shading (SFS). Pixel ambiguities of SFS can be eliminated by propagation approaches. However, patch ambiguities still exist. Therefore, we formulate the global disambiguation problem to resolve these ambiguities. Intuitively, it can be interpreted as flipping patches and adjusting heights such that the result surface has no kinks. The problemis intractable because exponentially many possible configurations need to be checked. Alternatively, we solve the integrability testing problems closely related to the original one. It can be viewed as finding a surface which satisfies the global integrability constraint. To encode the constraints, we introduce a graph formulation called configuration graph. Searching the solution on this graph can be reduced to a Max-cut problem and its solution is computuble using semidefinite programming (SDP) relaxation. Tests carried out on synthetic and real images show that the global disambiguation works well for complex shapes.
Graph orientation algorithms to minimize the maximum outdegree
Authors: Yuichi Asahiro, Eiji Miyano, Hirotaka Ono, Kouhei Zenmyo
Venue: Proceedings of the 12th Computing: The Australasian Theroy Symposium - Volume 51 (2006)

We study the problem of orienting the edges of a weighted graph such that the maximum weighted out-degree of vertices is minimized. This problem, which has applications in the guard arrangement for example, can be shown to be NP-hard generally. In this paper we first give optimal orientation algorithms which run in polynomial time for the following special cases: (i) the input is an unweighted graph, or more generally, a graph with identically weighted edges, and (ii) the input graph is a tree. Then, by using those algorithms as sub-procedures, we provide a simple, combinatorial, min{wmax/wmin, (2-ε)}-approximation algorithm for the general case, where wmax and wmin are the maximum and the minimum weights of edges, respectively, and ε is some small positive real number that depends on the input.
Reduced complexity algorithms for space-time coded systems over frequency selective fading channels
Authors: Tolga M. Duman
Venue:  (2006)

Space-time coding (STC) techniques have become popular since they offer high data rates while achieving low error rates over wireless links. When the transmission rates are increased by making the symbol periods smaller, the channel becomes frequency-selective (FS). The optimal receivers for STC systems over FS fading channels require prohibitively high hardware/software complexity. With the motivation of reducing this complexity, this dissertation proposes several simplified approaches for STC transmissions over multiple input multiple output (MIMO) FS fading channels. In the first part of the dissertation, we study a low complexity iterative MIMO receiver based on MIMO decision feedback equalization (DFE). We show that the MIMO DFE can be modified to utilize the soft inputs from the decoder which is essential for the design of iterative receivers. In the second part, we study a soft-input soft-output equalization based on the stack decoding algorithm. The new technique can be used in both coded and uncoded systems, and in single or multiple antenna scenarios. Based on simulation results, we show that the proposed technique performs close to the maximum-a-posteriori probability (MAP) equalizer while having significantly lower computational complexity. In the third part, we study the performance of STC techniques with transmit antenna selection and with joint transmit and receive antenna selection over flat fading channels. Furthermore, we extend the antenna selection results to the MIMO FS fading channels. Using pairwise error probability analysis and simulation results, we show that the receive and/or transmit antenna selection based on received power levels does not degrade the achievable diversity order when full rank STC are employed.