ppxscal/embedding_network huggingface dataset:
Decentralized coordination of automated guided vehicles
Authors: D. Herrero-Perez, H. Martinez-Barbera
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This paper approaches the issue of coordination of highly autonomous Automated Guided Vehicles (AGVs) working on an automated factory. These vehicles are used for goods delivery tasks between different points of the production system. The coordination is based on a decentralized architecture where each vehicle broadcasts the information about its state in the working environment, and by combining all these states in a local way, each AGV decides which action to take. The heuristic that allows the decentralized traffic control is based on a priority system, based on the current task, and a set of dangerous zones which are defined to avoid possible deadlocks, where mutual exclusion should be ensured. The process is somehow similar to that used by humans when circulating in cars: a set of rules and a set of signals/places. The interaction of many vehicles working on the same area under different collision conditions has been tested in a real industrial warehouse environment.
Hopcroft's Minimization Technique: Queues or Stacks?
Authors: Andrei Păun, Mihaela Păun, Alfonso Rodríguez-Patón
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

We consider the absolute worst case time complexity for Hopcroft's minimization algorithm applied to unary languages (or a modification of this algorithm for cover automata minimization). We show that in this setting the worst case is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. We refine a previous result by showing that the Berstel/Carton example reported before is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also when considering the setting of cover automata and an algorithm based on the Hopcroft's method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list is desirable for the case of unary languages in the setting of deterministic finite automata.
Stabilizing Intelligent Route Control: Randomized Path Monitoring, Randomized Path Switching or History-Aware Path Switching?
Authors: Alexandre Fonte, José Martins, Marilia Curado, Edmundo Monteiro
Venue: Proceedings of the 11th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services: Management of Converged Multimedia Networks and Services (2008)

Multihoming Intelligent Route Control (IRC) plays a significant role in improving the performance of Internet accesses. However, in a competitive environment, IRC systems may introduce persistent route oscillations, causing significant performance degradation. In this study, three design alternatives to cope with this issue are investigated: Randomized Path Monitoring, Randomized Path Switching and History-aware Path Switching. The simulation results show that Randomized Path Monitoring is an effective alternative to Randomized Path switching when the sampling frequency is conservative. The results also indicate that the use of a sophisticated IRC algorithm, such as history-aware path switching, does not bring noteworthy benefits in terms of stability.
Towards a Community of Practice Toolkit Based on Semantically Marked Up Artifacts
Authors: Christine Müller, Michael Kohlhase
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

Almost all aspects of scientific research and communication are now supported by software systems. Even though most of these systems allow the user to specify interaction preferences or even employ user modeling techniques, every system is an island with this respect. In particular, different systems cannot share user models or predict in the absence of prior interactions. We use ideas from the theory of Communities of Practice to arrive at declarative models that predict prior knowledge, preferences, and learning paths of scientists. Our models build on collections of semantically marked up artifacts (CoPfolios) that inscribe scientific practice. Our vision is to provide a toolkit that encapsulates CoPfolios allowing scientific applications to share user data.
Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm
Authors: Eric Schwartz, Bjorn Merker
Venue: IEEE Computer Graphics and Applications (1986)

In a variety of species including monkeys and humans, the surface of the retina is mapped in an accurate manner to the surface of primary visual cortex. In a real sense there is an image, expressed in the firing density of neurons, impressed on the surface of the brain. The various images found in the brain have complicated natures: They are ``distorted'' by nonlinear map functions, and contain submodality information expressed spatially in the form of columnar systems representing stereo, orientation, motion, and other forms of data. The detailed study of such maps represents a difficult series of problems in the areas of computer graphics, image processing, numerical analysis, and neuroanatomy. This article describes some intial steps in the field of computer-aided neuroanatomy. An algorithm for unfolding and flattening cortical surfaces and a measurement of the differential geometric aspects of these surfaces are presented. Models of the structure of images as they would appear mapped to the surface of primate striate cortex are also shown.
Study of solvent penetration inside a porous low k material by neutron reflectometry - Influence of material surface modifications and of solvent properties
Authors: D. Rébiscoul, L. Broussous, W. Puyrenier, V. Rouessac, A. Ayral, R. Cubitt
Venue: Microelectronic Engineering (2008)

Porous low k materials are used as insulator in integrated circuits interconnection levels. The impact of plasma post-treatments on such material was studied by neutron reflectometry coupled with deuterated solvents penetration. The porosity of the non-modified material determined by the CD"3CD"2OD adsorption isotherm is 28%. The CD"3CD"2OD and D"2O distributions inside the material modified by plasma were determined during their penetration. Whatever the plasma, even in steady state conditions, the modified materials are not completely filled by the solvents. For the sample modified by NH"3/N"2 plasma, whatever the solvent, the equilibrium is instantaneously reached. The CD"3CD"2OD diffused in all the material whereas the D"2O diffuse only in the modified zone due to its higher hydrophilic property compared to that of the zone located underneath. After fluorocarbon-based and oxidizing plasma the material shows a continuous penetration of the CD"3CD"2OD solvent with a saturation obtained after 150min whereas, the saturation is reached after 100min with D"2O. Moreover, D"2O penetrates the zone located underneath the modified surface of the sample which should be hydrophobic. This observation highlights a chemical modification of this zone by the plasma treatment.
State-Centric Programming for Sensor-Actuator Network Systems
Authors: Jie Liu, Maurice Chu, Juan Liu, James Reich, Feng Zhao
Venue: IEEE Pervasive Computing (2003)

Networked embedded systems such as wireless sensor and actuator networks require new programming models and software tools to support rapid design and prototyping. Unlike centralized platforms, these distributed sensor/actuator network (DSAN) systems are characterized by a massive number of failure-prone nodes, limited energy and bandwidth resources, and the need to rapidly respond to all kinds of sensing events.This article describes a state-centric, agent-based design methodology and the companion software environment PIECES, which mediate between a system developer's mental model of physical phenomena and the distributed DSAN platforms. The authors introduce the notion of collaboration groups, which abstracts common patterns in application-specific communication and resource allocation. An application developer specifies computations as the creation, aggregation, and transformation of states, which naturally map to the vocabulary used by signal processing and control engineers. More specifically, an application program is written as algorithms for state update and retrieval, with input supplied by dynamically created collaboration groups. As a result, programs written in the state-centric framework are more invariant to changes in system configuration, making the resulting software more modular and portable across multiple platforms. While this design methodology is widely applicable to many DSAN applications, the authors use a distributed tracking application with sensor networks to demonstrate how it can raise the abstraction level for application developers.
Resilience in the Aviation System
Authors: Antonio Chialastri, Simone Pozzi
Venue: Proceedings of the 27th international conference on Computer Safety, Reliability, and Security (2008)

This paper presents an overview of the main characteristics of the civil aviation domain and their relation with concepts coming from the approach of resilience engineering. Our objective is to first outline the structural properties of the aviation domain (i.e. regulations, standards, relationships among the various actors, system dynamics), to then present some example processes that bear an effect on the system resilience. We will in particular reason on training and on the role of automation, to discuss how and to what extent they impact on system resilience. We contend that, in a complex system like aviation, resilience engineering is not a matter of simple technical upgrades, rather is about facing contradictory tensions and dynamic system changes. This paper contains a pilot's first-hand reflections, so it aims to stimulate discussion on some issues that are still open, rather than providing solutions.
Susceptible Two-Party Quantum Computations
Authors: Andreas Jakoby, Maciej Liśkiewicz, Aleksander Mądry
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

In secure two-party function evaluation Alice holding initially a secret input x and Bob having a secret input y communicate to determine a prescribed function f(x, y) in such a way that after the computation Bob learns f(x, y) but nothing more about x other than he could deduce from y and f(x,y) alone, and Alice learns nothing. Unconditionally secure function evaluation is known to be essentially impossible even in the quantum world. In this paper we introduce a new, weakened, model for security in two-party quantum computations. In our model --- we call it susceptible function computation --- if one party learns something about the input of the other one with advantage ¿ then the probability that the correct value f(x,y) is computed, when the protocol completes, is at most 1 ¿ ¿(¿), for some function ¿ of ¿. Thus, this model allows to measure the trade-off between the advantage of a dishonest party and the error induced by its attack. Furthermore, we present a protocol for computing the one-out-of-two oblivious transfer function that achieves a quadratic trade-off i.e. ¿ = ¿(¿ 2).
Similarity Visualization for the Grouping of Forensic Speech Recordings
Authors: Klara A. Weiand, Jos S. Bouten, Cor J. Veenman
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

In a forensic phone wiretapping investigation, a major problem is to get the full picture of the speakers involved. Typically, the wiretapped speech recordings are grouped using a clustering tool. The main disadvantage of such an approach is that in a bootstrapped scenario grouping errors accumulate. In this paper, we propose a visual approach to find similar speech recordings that probably stem from the same speaker. We first model the speech recordings and define suitable similarity measures between recordings. Then, through an approximate 2-D visualization of the inter-speech, similarities the investigator can identify clear groups of recordings and recordings that are harder to differentiate. We did extensive experiments on phone data of 50 speakers with 2 recordings per speaker. We tested quality of the 2-D visualization in relation to original high dimensional similarities. It turned out that for the original high dimensional similarity measure the nearest recording is almost always the one from the same speaker. In the 2-D visualization, we achieved that on average for all speech recordings a recording of the same speaker is among the 10 nearest recordings.
A Novel Hand-Based Personal Identification Approach
Authors: Miao Qi, Yinghua Lu, Hongzhi Li, Rujuan Wang, Jun Kong
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Hand-based personal identification is a stable and reliable biometrically technique in the field of personal identity recognition. In this paper, both hand shape and palmprint texture features are extracted to facilitate a coarse-to-fine dynamic identification task. The wavelet zero-crossing method is first used to extract hand shape features to guide the fast selection of a small set of similar candidates from the database. Then, a circular Gabor filter, which is robust against brightness, and modified Zernike moments methods are used to extract the features of palmprint. And one-class-one-network (Back-Propagation Neural Network (BPNN) classification structure is employed for final classification. The experimental results show the effectiveness and accuracy of the proposed approach.
Diagnosability of Two-Matching Composition Networks
Authors: Sun-Yuan Hsieh, Chia-Wei Lee
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

Diagnosability is an important metric for measuring the reliability of multiprocessor systems. In this paper, we study the diagnosability of a class of networks, called Two-Matching Composition Networks (2-MCNs), each of which is constructed by connecting two graphs via two perfect matchings. By applying our result to multiprocessor systems, we also compute the diagnosability of folded hypercubes and augmented cubes, both of which belong to two-matching composition networks.
Using Data Mining Methods to Predict Personally Identifiable Information in Emails
Authors: Liqiang Geng, Larry Korba, Xin Wang, Yunli Wang, Hongyu Liu, Yonghua You
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Private information management and compliance are important issues nowadays for most of organizations. As a major communication tool for organizations, email is one of the many potential sources for privacy leaks. Information extraction methods have been applied to detect private information in text files. However, since email messages usually consist of low quality text, information extraction methods for private information detection may not achieve good performance. In this paper, we address the problem of predicting the presence of private information in email using data mining and text mining methods. Two prediction models are proposed. The first model is based on association rules that predict one type of private information based on other types of private information identified in emails. The second model is based on classification models that predict private information according to the content of the emails. Experiments on the Enron email dataset show promising results.
Expansion and implementation of the wave variable method in multiple degree-of-freedom systems
Authors: Marc T. Alise
Venue:  (2007)

Adding force feedback to a teleoperation system can greatly improve a user&rsquo;s ability to complete tasks. However, operating in the presence of time delay can cause serious problems for bilateral teleoperation systems. Even a small amount of time delay in a bilateral teleoperation system will generally degrade the system&rsquo;s performance and can cause instability. An important approach that guarantees stability for any fixed time delay is the wave variable method. In this thesis some recent material dealing with teleoperation systems using wave variables is presented. In particular, we describe a wave variable scheme based on a family of scaling matrices for a multiple degree-of-freedom bilateral teleoperation system. We include a derivation of a larger and more complete family of scaling matrices that will guarantee the system remains stable for a fixed time delay. The validity of the complete family of scaling matrices is verified through simulations and experiments. A multiple degree-of-freedom bilateral teleoperation system using the new wave variable method is simulated using a SIMULINK model. In addition, the new derivation was implemented in hardware using two different systems: an Immersion joystick with a C++ program and a PHANToM Omni haptic device with a virtual environment. Finally, an experiment was constructed using the PHANToM Omni haptic device as both the master and slave of the teleoperation system. Using Matlab and SIMULINK we added time delay to the communication channel and implemented the wave variable method with the complete family of scaling matrices. Human subjects were used to determine the best set of parameters for the system.
An Investigation on Testing of Parallelized Code with OpenMP
Authors: Robert Barnhart, Christian Trefftz, Paul Jorgensen, Yonglei Tao
Venue: Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era (2007)

Testing is a crucial element of software development. As OpenMP becomes more widely used, a relevant question for developers is: How will programs, that have been parallelized with OpenMP, be tested for correctness? OpenMP programs are concurrent programs and as such all the risks of concurrent programming are present as well. This paper presents some observations about testing parallelized loops using OpenMP.
Semi-supervised Classification from Discriminative Random Walks
Authors: Jérôme Callut, Kevin Françoisse, Marco Saerens, Pierre Dupont
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

This paper describes a novel technique, called $\mathcal{D}$-walks, to tackle semi-supervised classification problems in large graphs. We introduce here a betweenness measure based on passage times during random walks of bounded lengths. Such walks are further constrained to start and end in nodes within the same class, defining a distinct betweenness for each class. Unlabeled nodes are classified according to the class showing the highest betweenness. Forward and backward recurrences are derived to efficiently compute the passage times. $\mathcal{D}$-walks can deal with directed or undirected graphs with a linear time complexity with respect to the number of edges, the maximum walk length considered and the number of classes. Experiments on various real-life databases show that $\mathcal{D}$-walks outperforms NetKit [5], the approach of Zhou and Schölkopf [15] and the regularized laplacian kernel [2]. The benefit of $\mathcal{D}$-walks is particularly noticeable when few labeled nodes are available. The computation time of $\mathcal{D}$-walks is also substantially lower in all cases.
Payroll accounting with Elecom 120 computer
Authors: Robert F. Shaw
Venue: Proceedings of the February 4-6, 1953, western computer conference (1953)

The Elecom is a magnetic drum computer of the same general type as the Elecom 100, which was described in detail by Mr. Auerbach of this company at the meeting of the Association for Computing Machinery in Pittsburgh last May, and published in the Proceedings of that meeting. It differs from the 100 in two important respects; operation is decimal throughout, and the memory capacity has been increased from 512 to 1000 words. The change from binary to decimal operation results in a machine which is well adapted to commercial applications as well as purely mathematical computations. 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
Simulation of Winter Air Pollution Dispersion Mechanism of Kathmandu Valley by Water-Tank Experiment
Authors: M. L. Shrestha, A. Kaga, A. Kondo, Y. Inoue, M. Sugisawa, B. Sapkota
Venue: Journal of Visualization (2004)

The air pollution concentration in Kathmandu valley in the winter season was found to be higher than in the summer season due to the formation of the inversion layer. This mechanism was simulated in the water-tank experiment by measuring the temperature and flow field using liquid crystal thermometry and particle image velocimetry. Thermal stratification was made at the beginning of the experiment and the surface temperature of the valley model was changed with 12 minutes period matching the diurnal field temperature pattern of the Kathmandu valley. The updraft wind and Bernard convection occurred during daytime and downdraft wind and inversion layer were realized during nighttime. The temperature, flow field and mass dispersion characteristics obtained in the water-tank experiment explained clearly the mechanism of air pollution in Kathmandu valley.
Brief paper: Control design with arbitrary information structure constraints
Authors: A. I. Zečević, D. D. Šiljak
Venue: Automatica (Journal of IFAC) (2008)

In this paper, a new method is proposed for designing robust control laws that are subject to arbitrary information structure constraints. The computation of the gain matrix is formulated in terms of a static output feedback problem, which can be efficiently solved using linear matrix inequalities. The resulting control laws ensure stability with respect to a broad class of additive nonlinear uncertainties in the system.
Study on STAP Algorithm for Radar Target Detection in Heterogeneous Environments
Authors: Qing-yong Gong, Zhao-da Zhu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In heterogeneous environments, due to the lack of the independently and identically distributed (IID) samples, the performance of traditional STAP is degraded severely. The maximum likelihood amplitude and phase estimation of a sinusoid (APES) algorithm can operate directly on data of range cell-under-test. However, this algorithm is based on space domain adaptive processing, which is insensitive to weak target, and mistaking the interference as the true target for the identical Doppler frequency. In this paper, an improved algorithm is proposed, which applies space-time two-dimension APES algorithm to estimate the target’s amplitude, then detecting the moving target according to the output signal-to-noise ration, overcoming the original algorithm’s shortcoming effectively. Simulation results are presented to demonstrate the validity of this improved method.