ppxscal/embedding_network huggingface dataset:
A Hybrid Recurrent Neural Network for Machining Process Modeling
Authors: Xingyu Lai, Chunyan Yan, Bangyan Ye, Weiguang Li
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

A new hybrid recurrent neural network (HRNN) for machining process modeling is presented based on the diagonal recurrent neural network (DRNN). In order to overcome the weakness of back propagation (BP) algorithm, a generalized entropy square error (GESE) criterion is defined and a dynamic recurrent back propagation algorithm is developed to guarantee the global convergence. The HRNN based on the GESE is then used for nonlinear system identification and neural network modeling of the machining process. The numeral experiments results show that the HRNN has better approximate effectiveness, tracking and dynamic performance than traditional BP neural network.
Computational analysis of the interfacial effect on electromigration in flip chip solder joints
Authors: Dongchoul Kim
Venue: Microelectronic Engineering (2009)

Recent experiments have shown failure in flip chip micro solder joints induced by electromigration. This paper proposes a three-dimensional computational model to simulate the evolution of micro and sub-micro scale solder joints due to electromigration induced diffusion. The evolving morphology of the solder joint related with multiple mechanisms causes a computational challenge. This is addressed by employing a diffuse interface model with multiple concentrations. To efficiently resolve complications, a semi-implicit Fourier spectral scheme and a biconjugate-gradient method are adopted. Results have demonstrated rich dynamics and solder breakage at the interface on the cathode side. Furthermore, the effect of the designed interface region on the reliability of solder joints has been investigated with the developed model.
On the Anonymity of Home/Work Location Pairs
Authors: Philippe Golle, Kurt Partridge
Venue: Proceedings of the 7th International Conference on Pervasive Computing (2009)

Many applications benefit from user location data, but location data raises privacy concerns. Anonymization can protect privacy, but identities can sometimes be inferred from supposedly anonymous data. This paper studies a new attack on the anonymity of location data. We show that if the approximate locations of an individual's home and workplace can both be deduced from a location trace, then the median size of the individual's anonymity set in the U.S. working population is 1, 21 and 34,980, for locations known at the granularity of a census block, census track and county respectively. The location data of people who live and work in different regions can be re-identified even more easily. Our results show that the threat of re-identification for location data is much greater when the individual's home and work locations can both be deduced from the data. To preserve anonymity, we offer guidance for obfuscating location traces before they are disclosed.
GPSel: A Gestural Perceptual-Based Path Selection Technique
Authors: Hoda Dehmeshki, Wolfgang Stuerzlinger
Venue: Proceedings of the 10th International Symposium on Smart Graphics (2009)

This paper introduces a gestural perceptual-based approach to select objects, i.e., nodes and/or edges along paths. Based on known results from perception research, we propose a model to detect perceptually salient paths formed by the Gestalt principles of good continuity and closure. Then we introduce gestural interaction techniques that enable users to select single or multiple perceptual paths, as well as resolving ambiguities in selection. The result of a user study shows that our system outperforms current techniques for path selection.
Imitation Versus Communication: Testing for Human-Like Intelligence
Authors: Jamie Cullen
Venue: Minds and Machines (2009)

Turing's Imitation Game is often viewed as a test for theorised machines that could `think' and/or demonstrate `intelligence'. However, contrary to Turing's apparent intent, it can be shown that Turing's Test is essentially a test for humans only. Such a test does not provide for theorised artificial intellects with human-like, but not human-exact, intellectual capabilities. As an attempt to bypass this limitation, I explore the notion of shifting the goal posts of the Turing Test, and related tests such as the Total Turing Test, away from the exact imitation of human capabilities, and towards communication with humans instead. While the continued philosophical relevance of such tests is open to debate, the outcome is a different class of tests which are, unlike the Turing Test, immune to failure by means of sub-cognitive questioning techniques. I suggest that attempting to instantiate such tests could potentially be more scientifically and pragmatically relevant to some Artificial Intelligence researchers, than instantiating a Turing Test, due to the focus on producing a variety of goal directed outcomes through communicative methods, as opposed to the Turing Test's emphasis on `fooling' an Examiner.
Searching bifurcations in high-dimensional parameter space via a feedback loop breaking approach
Authors: Steffen Waldherr, Frank Allgower
Venue: International Journal of Systems Science (2009)

Bifurcations leading to complex dynamical behaviour of non-linear systems are often encountered when the characteristics of feedback circuits in the system are varied. In systems with many unknown or varying parameters, it is an interesting, but difficult problem to find parameter values for which specific bifurcations occur. In this article, we develop a loop breaking approach to evaluate the influence of parameter values on feedback circuit characteristics. This approach allows a theoretical classification of feedback circuit characteristics related to possible bifurcations in the system. Based on the theoretical results, a numerical algorithm for bifurcation search in a possibly high-dimensional parameter space is developed. The application of the proposed algorithm is illustrated by searching for a Hopf bifurcation in a model of the mitogen activated protein kinase cascade, which is a classical example for biochemical signal transduction.
Extrapolation of Vector Fields Using the Infinity Laplacian and with Applications to Image Segmentation
Authors: Laurence Guillot, Carole Guyader
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

In this paper, we investigate a new Gradient-Vector-Flow (GVF)([38])-inspired static external force field for active contour models, deriving from the edge map of a given image and allowing to increase the capture range. Contrary to prior related works, we reduce the number of unknowns to a single one v by assuming that the expected vector field is the gradient field of a scalar function. The model is phrased in terms of a functional minimization problem comprising a data fidelity term and a regularizer based on the super norm of Dv. The minimization is achieved by solving a second order singular degenerate parabolic equation. A comparison principle as well as the existence/uniqueness of a viscosity solution together with regularity results are established. Experimental results for image segmentation with details of the algorithm are also presented.
MCP: An Energy-Efficient Code Distribution Protocol for Multi-Application WSNs
Authors: Weijia Li, Youtao Zhang, Bruce Childers
Venue: Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems (2009)

In this paper, we study the code distribution problem in multi-application wireless sensor networks (MA-WSNs), i.e., sensor networks that can support multiple applications. While MA-WSNs have many advantages over traditional WSNs, they tend to require frequent code movements in the network, and thus here new challenges for designing energy efficient code dissemination protocols.We propose MCP, a stateful Multicast based Code redistribution Protocol for achieving energy efficiency. Each node in MCP maintains a small table to record the interesting information of known applications. The table enables sending out multicast-based code dissemination requests such that only a subset of neighboring sensors contribute to code dissemination. Compared to broadcasting based schemes, MCP greatly reduces signal collision and saves both the dissemination time and reduces the number of dissemination messages. Our experiments results show that MCP can reduce dissemination time by 25% and message overhead by 20% under various network settings.
ParaDisE: parallel discovery engine for enterprise datacenters
Authors: Sandip Agarwala, Luis A. Bathen, Divyesh Jadav, Ramani Routray
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

Automatic discovery and monitoring of IT resources is a critical part of enterprise systems management. In addition to ascertaining internal device configurations, this discovery process may also need to capture the capabilities, usage, connectivity, availability, and other information related to various IT components. Systems resource management (SRM) tools typically implement this discovery process using device specific APIs, custom agents and/or some standard-based solution (like WBEM and CIM). The discovery actions need to be systematically planned; an inefficient implementation or scheduling may easily take from a few minutes to several hours to complete in a large heterogeneous enterprise datacenter. This paper discusses the various challenges associated in discovering a datacenter environment and presents an autonomic monitoring framework called 'ParaDisE' that builds upon well-known industry standards and reduces the overall discovery time by more than 50%.
Network Intrusion Detection with Workflow Feature Definition Using BP Neural Network
Authors: Yong Wang, Dawu Gu, Wei Li, Hongjiao Li, Jing Li
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

The major problem of existing intrusion detection using neural network models is recognition of new attacks and low accuracy. The paper describes an intrusion detection method based on workflow feature definition according to KDD cup 99 types with feed forward BP neural network. The workflow can define new attacks sequence to help BP neural network recognize new attacks. The method takes network traffic data to analyze and classify the behaviors of the authorized users and recognize the possible attacks. The experiment results show that the design is effective.
Effects of a metacognitive support device in learning environments
Authors: Maria Bannert, Melanie Hildebrand, Christoph Mengelkamp
Venue: Computers in Human Behavior (2009)

Successful learning is mainly based on metacognitive activities which have to be performed and constantly monitored during learning. Research reveals that many learners have difficulties in performing such metacognitive activities spontaneously, which most probably results in lower learning outcomes. The aim of this study is to experimentally analyse the effects of a metacognitive support device combined with a paper-based prompting scheme. With this support device, students are instructed to activate their repertoire of metacognitive knowledge and skills which should further enhance learning and transfer. University students of the experimental group (n=29) were instructed by means of a metacognitive support device why metacognitive activities are useful and how to apply them during learning. In addition, during learning, they were prompted to apply the metacognitive activities they just had learned. Students of the control group (n=27) were not instructed why and how to use metacognitive activities, and furthermore, they were not prompted during learning to apply these metacognitive activities. Rather, they were instructed by a computer device how to organise a work place for their studies so all groups were treated in a similar way. The students' learning task was to learn about ''psychological theories of using pictures in multimedia learning environments'' within 60min. Immediately afterwards, learning outcome was measured with a test. Altogether, 56 university students participated, counterbalanced according to their prior knowledge as well as metacognitive knowledge. As expected, students of the experimental group showed better transfer performance compared with the control group. In addition, training did increase metacognitive behavior measured by subjective ratings.
A method for the perceptual optimization of complex visualizations
Authors: Donald House, Colin Ware
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

A common problem in visualization applications is the display of one surface overlying another. Unfortunately, it is extremely difficult to do this clearly and effectively. Stereoscopic viewing can help, but in order for us to be able to see both surfaces simultaneously, they must be textured, and the top surface must be made partially transparent. There is also abundant evidence that all textures are not equal in helping to reveal surface shape, but there are no general guidelines describing the best set of textures to be used in this way. What makes the problem difficult to perceptually optimize is that there are a great many variables involved. Both foreground and background textures must be specified in terms of their component colors, texture element shapes, distributions, and sizes. Also to be specified is the degree of transparency for the foreground texture components. Here we report on a novel approach to creating perceptually optimal solutions to complex visualization problems and we apply it to the overlapping surface problem as a test case. Our approach is a three-stage process. In the first stage we create a parameterized method for specifying a foreground and background pair of textures. In the second stage a genetic algorithm is applied to a population of texture pairs using subject judgments as a selection criterion. Over many trials effective texture pairs evolve. The third stage involves characterizing and generalizing the examples of effective textures. We detail this process and present some early results.
A self-organizing neural network architecture for intentional planning agents
Authors: Budhitama Subagdja, Ah-Hwee Tan
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can be accommodated through multi-directional activations accross different modalities of patterns. The network seamlessly interleaves planning and learning processes towards achieving the goal. Case studies and experiments shows that the model can be used to execute, plan, and capture plans as recipes through experiences.
Germanium surface and interfaces (Invited Paper)
Authors: A. Dimoulas, P. Tsipas
Venue: Microelectronic Engineering (2009)

Germanium surface and interfaces are modeled based on the requirement that surface charge neutrality is satisfied. It is found that Ge interfaces have remarkable electronic properties stemming from the fact that the energy gap is low and the CNL is located very low in the gap close to the valence band. Because of this, acceptor defects (probably dangling bonds) are easily filled building a negative charge at the interface which easily inverts the surface of n-type Ge at no gate bias and for low doping N"D and moderate to high interface state density D"i"t. This has important consequence in the electrical characteristics of Ge transistors. In p-channel FETs, an undesired positive threshold voltage V"T of +0.2 to +0.5V is predicted depending on N"D, D"i"t and the equivalent oxide thickness. In n-channel FETs, inversion is inhibited and V"T could become higher than 1V if the D"i"t is well in excess of 10^1^3eV^-^1cm^-^2.
Correctness proof of a database replication protocol under the perspective of the I/O automaton model
Authors: Jos&#x00e9; Enrique Armend&#x00e1;riz-I&#x00f1;igo, Jos&#x00e9; Ram&#x00f3;n Gonz&#x00e1;lez de Mend&#x00ed;vil, Jos&#x00e9; Ram&#x00f3;n Garitagoitia, Francesc D. Mu&#x00f1;oz-Esco&#x00ed;
Venue: Acta Informatica (2009)

Correctness of recent database replication protocols has been justified in a rather informal way focusing only in safety properties and without using any rigorous formalism. Since a database replication protocol must ensure some degree of replica consistency and that transactions follow a given isolation level, previous proofs only focused in these two issues. This paper proposes a formalization using the I/O automaton model, identifying several components in the distributed system that are involved in the replication support (replication protocol, group communication system, database replicas) and specifying clearly their actions in the global replicated system architecture. Then, a general certification-based replication protocol guaranteeing the snapshot isolation level is proven correct. To this end, different safety and liveness properties are identified, checked and proved. Our work shows that some details of the replication protocols that were ignored in previous correctness justifications are indeed needed in order to guarantee our proposed correctness criteria.
Active learning for anaphora resolution
Authors: Caroline Gasperin
Venue: Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing (2009)

In this paper we present our experiments with active learning to improve the performance of our probabilistic anaphora resolution system. We have adopted entropy-based uncertainty measures to select new instances to be added to our training data. The actively selected instances, however, were not more successful in improving the performance of the system than the same amount of randomly selected instances. The uncertainty measures we used behave differently from each other when selecting new instances, but none of them achieved remarkable performance. Further studies on active sample selection for anaphora resolution are necessary.
Digital Performer 5 Power!, 1st edition
Authors: Don Barrett
Venue:  (2007)

Digital Performer is one of the leading digital audio workstation programs for the Apple Mac. It allows you to sequence MIDI, record multiple channels of audio, mix them down, synch them to video, and utilize plug-in software synthesizers and software studios. Digital Performer 5 Power!: The Comprehensive Guide provides a versatile guide to setting up and using the newest version of MOTUs Digital Performer 5 audio/MIDI sequencing, editing, and recording software. The books approach is one that will simplify and demystify the technical aspects of setting up and using Digital Performer 5, while also supplying useful engineering tips and shortcuts to help you get the most out of the program. Chapters and sections progress naturally through the music production process, from navigating the interface, setting up projects, and recording, to working with MIDI, editing, arranging, mixing, mastering, handling music notation, and scoring to picture. This setup allows new users to work through the book from start to finish and learn Digital Performer quickly, while intermediate and advanced users can flip to specific areas of interest to learn new tricks and increase their mastery. Regardless of your skill level, this is the only guide to Digital Performer you will ever need to take your music to the next 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
On spatial electro-hydrodynamic instability of a jet
Authors: D. N. Riahi
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

The problem of spatial instability of a jet, which is driven by a uniform electric field, is investigated. The investigation is based on the relevant approximated versions of the equations of the electro-hydrodynamics for an electrically forced jet flow. We found, in particular, one instability mode, which is the spatial and electrical counterpart of the well known surface tension driven Rayleigh instability mode, while another instability mode is detected to be a spatial electric instability mode, which is enhanced with increasing the strength of the electric field.
State-coupled replicator dynamics
Authors: Daniel Hennes, Karl Tuyls, Matthias Rauterberg
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate games. More precisely, it extends and improves previous work on piecewise replicator dynamics, a combination of replicators and piecewise models. The contributions of the paper are twofold. One, we identify and explain the major shortcomings of piecewise replicators, i.e. discontinuities and occurrences of qualitative anomalies. Two, this analysis leads to the proposal of the new model for learning dynamics in stochastic games, named state-coupled replicator dynamics. The preceding formalization of piecewise replicators - general in the number of agents and states - is factored into the new approach. Finally, we deliver a comparative study of finite action-set learning automata to piecewise and state-coupled replicator dynamics. Results show that state-coupled replicators model learning dynamics in stochastic games more accurately than their predecessor, the piecewise approach.
Link-quality measurement enhancement for routing in wireless mesh networks
Authors: Golnaz Karbaschi, Anne Fladenmuller, Bernd E. Wolfinger
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

In this paper we introduce a novel distributed and robust link-quality measurement framework, called QualRoute. It exploits the existing traffic in the network in order to estimate accurately the quality of the links. Different from existing methods, our proposed scheme takes advantage of the broadcast nature of the wireless medium, and sets up an asynchronous cooperation between neighbors without any extra signaling between the node pairs. The simulation results suggest that the route derived from QualRoute yields to noticeably better performance than the traditional shortest path routes. Moreover, a comparison with a similar link-quality metric which is measured differently confirms the significant impact of the measurement scheme on the over-all performance.
A few remarks on minimal realizations
Authors: Tiberiu Vasilache
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

A few algorithms to find minimal realizations starting from various situations (already known realizations, transfer matrices, sequences of Markov parameters) are presented, arguments related to transfer matrices are used and highlighted in the proofs, being preferred in this paper to some classical state-space arguments. A few results and remarks are given related to some recurrence formulae that allow purely algebraic calculations for Markov parameters.