ppxscal/embedding_network huggingface dataset:
A Knowledge-Based Software Life-Cycle Framework for the Incorporation of Multicriteria Analysis in Intelligent User Interfaces
Authors: Katerina Kabassi Maria Virvou
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Decision-making theories aiming at solving decision problems that involve multiple criteria have often been incorporated in knowledge-based systems for the improvement of these systems' reasoning process. However, multicriteria analysis has not been used adequately in intelligent user interfaces, even though user-computer interaction is, by nature, multicriteria-based. The actual process of incorporating multicriteria analysis into an intelligent user interface is neither clearly defined nor adequately described in the literature. It involves many experimental studies throughout the software life-cycle. Moreover, each multicriteria decision-making theory requires different kinds of experiments for the criteria to be determined and then for the proper respective weight of each criterion to be specified. In our research, we address the complex issue of developing intelligent user interfaces that are based on multicriteria decision-making theories. In particular, we present and discuss a software life-cycle framework that is appropriate for the development of such user interfaces. The life-cycle framework is called MBIUI. Given the fact, that very little has been reported in the literature about the required experimental studies, their participants and the appropriate life-cycle phase during which the experimental studies should take place, MBIUI provides useful insight for future developments of intelligent user interfaces that incorporate multicriteria theories. One significant advantage of MBIUI is that it provides a unifying life-cycle framework that may be used for the application of many different multicriteria decision-making theories. In the paper, we discuss the incorporation features of four distinct multicriteria theories: TOPSIS, SAW, MAUT, and DEA. Furthermore, we give detailed specifications of the experiments that should take place and reveal their similarities and differences with respect to the theories.
Instantaneous frequency and time-frequency distributions
Authors: B. Tacer, P. J. Loughlin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

It is generally stated that the conditional mean frequency of a time-frequency distribution (TFD) should equal the instantaneous frequency of the signal. The commonly accepted definition of instantaneous frequency as the derivative of the phase of the analytic signal sometimes leads to curious results. Although it is commonly held that positivity of the TFD and satisfaction of the so-called "instantaneous frequency constraint" are generally incompatible, we show that one can always find a complex signal, the real part of which is the given signal, for which the derivative of the phase is consistent with the marginals and positivity. Furthermore, for the cases considered, the derivative of the phase of this signal, which by design equals the conditional mean frequency of a positive TFD, is a reasonable, readily interpretable choice for instantaneous frequency.
Coach planning with opponent models for distributed execution
Authors: Patrick F. Riley, Manuela M. Veloso
Venue: Autonomous Agents and Multi-Agent Systems (2006)

In multi-agent domains, the generation and coordinated execution of plans in the presence of adversaries is a significant challenge. In our research, a special "coach" agent works with a team of distributed agents. The coach has a global view of the world, but has no actions other than occasionally communicating with the team over a limited bandwidth channel. Our coach is given a set of predefined opponent models which predict future states of the world caused by the opponents' actions. The coach observes the world state changes resulting from the execution of its team and opponents and selects the best matched opponent model based on its observations. The coach uses the recognized opponent model to predict the behavior of the opponent. Upon opportunities to communicate, the coach generates a plan for the team, using the predictions of the opponent model. The centralized coach generates a plan for distributed execution. We introduce (i) the probabilistic representation and recognition algorithm for the opponent models; (ii) a multi-agent plan representation, Multi-Agent Simple Temporal Networks; and (iii) a plan execution algorithm that allows the robust distributed execution in the presence of noisy perception and actions. The complete approach is implemented in a complex simulated robot soccer environment. We present the contributions as developed in this domain, carefully highlighting their generality along with a series of experiments validating the effectiveness of our coach approach.
A Privacy-Aware Service-oriented Platform for Distributed Data Mining
Authors: Xiaofeng Zhang, Ho-fai Wong, William K. Cheung
Venue: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (2006)

Customer data privacy is known to be a factor which makes just-in-time data sharing and mining among enterprises challenging. Learning-from-abstraction is a recently proposed paradigm for privacy preserving distributed data mining where distributed local data sources are protected by probabilistic data abstraction. In this paper, we investigate the use of a normalized negative log likelihood together with the paradigm for quantifying the level of privacy protection, and studied theoretically the change of the privacy levels of the local data abstractions after being aggregated for global data analysis. Experiments on distributed data clustering with a synthetic data set were conducted on a service-oriented BPEL platform. The promising results obtained demonstrates the effectiveness of the adopted privacy measure.
Unbalanced Exponent Modular Reduction over Binary Field and Its Implementation
Authors: Haibin Shen, Yier Jin, Rongquan You
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Modular reduction is the basic operation of cryptographic systems. The Barrett's Algorithm and Montgomery's Algorithm are widely used nowadays and they are both based on pre-computation. In the field of Elliptic Curve Cryptosystem (ECC) over GF(2^m), the reduction polynomials recommended by SEC have few items and the degree of second item is much less than that of the first one. Making use of this characteristic, the paper presents a new method to accelerate modular reduction without precomputation which speeds up modular reduction by 10-30 times over GF(2^m) and speeds up ECC point multiplication by 40%-50%. This algorithm has been implemented in a high-speed public-key cipher accelerator.
Introducing Smartcard Enabled RADIUS Server
Authors: Pascal Urien, Mesmin Dandjinou
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

This paper introduces an innovative concept of smartcard enabled RADIUS server. We design RADIUS servers in which EAP messages are fully processed by smartcards, called EAP-Servers. When the well known TLS protocol is used as authentication method, this architecture becomes scalable. In that case, concurrent authentication sessions are simultaneously handled by different EAP-Servers, each of them securely embeds an unique X509 certificate and its associated private key. We presents experimental results obtained with commercial components, and demonstrate that system performances, about 5 seconds per RADIUS session, are compatible with today network constraints.
Parameterized complexity and improved inapproximability for computing the largest j-simplex in a V-polytope
Authors: Ioannis Koutis
Venue: Information Processing Letters (2006)

We consider the problem of computing the squared volume of the largest j-simplex contained in an n-dimensional polytope presented by its vertices (a V-polytope). We show that the related decision problem is W [1]-complete, with respect to the parameter j. We also improve the constant inapproximability factor given in [A. Packer, Polynomial-time approximation of largest simplices in V-polytopes, Discrete Appl. Math. 134 (1-3) (2004) 213-237], by showing that there are constants µ < 1, c > 1 such that it is NP-hard to approximate within a factor of cµn the volume of the largest ⌊µn⌋-simplex contained in an n-dimensional polytope with O(n) vertices.
Adaptive beamforming of cyclic signal and fast implementation
Authors: Qiang Wu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Recently, it has been proposed to apply array beamforming in digital mobile communication systems, such as mobile cellular communication systems and mobile-satellite communication systems, in order to increase channel capacity and suppress co-channel interference. However, the conventional beamforming methods are not suitable for such use, since these methods were mainly developed for signal detection and DOA estimation in radar and sonar. In this paper, utilizing the cyclostationarities of communication signals, we propose three blind cyclic adaptive algorithms (CAB's) and associated fast implementation schemes. We also investigate the characteristics of the new beamforming methods. 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
Adaptive Query Optimization Method for Multiple Continuous Queries
Authors: Yousuke Watanabe, Hiroyuki Kitagawa
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Continuous query is widely recognized as a scheme for processing queries over data streams, and efficient methods for processing multiple continuous queries are needed. Our research group has proposed a multiple query optimization method for continuous queries. In our method, the system forms clusters of queries with similar execution patterns, and derives query plans sharing the result of common operators. Our previous experiments have shown that a parameter value in the clustering phase controls divisions of clusters and has a great impact on query processing effi- ciency. However, the optimal parameter value must be decided by trial and error. This paper extends our previous work. The proposed method automatically estimates the optimal value and iteratively adjusts it even if properties of underlying data streams dramatically change.
Convergence
Authors: Daniel E. Geer Jr.
Venue: IEEE Security and Privacy (2006)

Convergence is the idea of merging the duties and responsibilities of physical security with that of digital security to make them part of a common reporting structure--to employ tools and techniques that are parallel if not collinear.
Sliding simulation for adhesion problems in micro gear trains based on an atomistic simplified model
Authors: Yang Ping, Liao Ning Bo, Yang Daoguo, L. J. Ernst
Venue: Microsystem Technologies (2006)

The objective of this research work is to provide a systematic method to perform molecular dynamics simulation or evaluation for adhesion of micro/nano gear train during sliding friction in MEMS. In this paper, molecular dynamics simulations of adhesion problems in micro gear train are proposed. The perfect MEMS gear train model is very complicated by considering the computing time. A simplified model to simulate surface sliding between metals by molecular dynamics (MD) is proposed because the surface property is a dominant factor for the performance of gear systems. Based on analysis of sliding friction and the transmitting characteristics of micro gear train, a model is established by utilizing the Morse potential function. The Verlet&#x00a0;algorithm is employed to solve atom trajectories. The simulation results show that adhesion tends to occur between two micro gears after certain cycles and such adhesion accounts for the friction force and the temperature increase. The simulation results are in consistence with the experimental results in the literature. The model is meaningful to prolong the lifetime of micro gear train by selecting proper parameters.
XJ technologies: AnyLogic 6
Authors: Andrei Borshchev
Venue: Proceedings of the 37th conference on Winter simulation (2005)

XJ Technologies presents AnyLogic version 6, the major step forward in simulation technology. While inheriting all recognized features of AnyLogic 5 (multi-paradigm modeling with system dynamics, discrete event and agent based approaches, object-orientedness and open architecture), version 6 is totally Java solution based on IBM Eclipse technology. It has a much more intuitive user interface with a lot of services speeding up the model development and offers even more flexibility for developing custom solutions and toolkits in various application areas.
Dynamics of human neocortex that optimizes its stability and flexibility: Research Articles
Authors: Walter J. Freeman, Mark D. Holmes, G. Alexander West, Sampsa Vanhatalo
Venue: International Journal of Intelligent Systems (2006)

The electroencephalogram (EEG) in states of awake, sleep, and seizure in a patient with intractable partial complex seizures was recorded through a 1- &times; 1-cm microgrid of 64 electrodes on the right inferior temporal gyrus during a week-long neurosurgical evaluation. Comparisons with a normal intracranial EEG were perforce from animals. Analytic phase and amplitude from the Hilbert transform gave the temporal resolution needed to resolve EEG spatiotemporal structure. The rest state revealed multiple overlapping patterns of high-frequency coherent oscillations resembling bubbles in boiling water. Bubble diameters gave estimates of the distances across the cortex over which the cortical oscillations were synchronized. Superimposed on these bubbles were large-sized epochs of phase locking with briefly constant frequency and high amplitude. These coordinated analytic phase differences occurred between short periods of high phase variance. The variance gave evidence for state transitions between transiently stable states with constant phase gradients. In sleep these phase patterns persisted with reduced amplitude, occasionally interrupted by long-lasting (&sim;1 s) epochs with no spatial textures in phase and amplitude despite a large increase in amplitude. Seizures had high amplitude 3&#x002F;s spikes with steep spatial gradients. Onset occurred after pre-ictal reduction in bubble diameters as evidence for large-scale cortical disintegration preceding loss of stability. &copy; 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 881&ndash;901, 2006.
Music Motive Extraction Through Hanson Intervallic Analysis
Authors: Johnny F. Serrano, Jose M. Inesta
Venue: Proceedings of the 15th International Conference on Computing (2006)

Music motive extraction is an important concept to consider in music information retrieval. Among the possible applications are the creation of music databases that need of indexing tools and access in a dynamic way, copyright management and plagiarism detection, computer-aided composition, etc. This paper present an unsupervised method for automatic music motive extraction from symbolic sources, using an intervallic analysis. The results are evaluated quantitatively using a melodic similarity technique.
Optimal design of hybrid FEC/ARQ schemes for real-time applications in wireless networks
Authors: R. El Azouzi, T. Peyre, A. Benslimane
Venue: Proceedings of the 2nd ACM international workshop on Wireless multimedia networking and performance modeling (2006)

Multimedia data transmission over wireless networks often suffers from delay, jitter and packet loss. The main problem to implement a wireless network is the high and variable bit error rate in the radio link, making it necessary to use an additional error control mechanism. The traditional techniques for error control are ARQ (Automatic Repeat Request) and FEC (Forward Error Correction). The ARQ technique works better than FEC, if the bit error rate in the channel is low, and worse, if the bit error rate is high. Thus, hybrid ARQ/FEC techniques can improve the performance. In this paper, a novel hybrid ARQ/FEC scheme is analyzed in an environment of real-time applications. We focus in a simple FEC scheme which has been standardized by IETF [11]. It consists in adding a low quality copy of the original packet n to the packet n + ø. If packet n is lost in the network, it can be correctly recovered if packet n +ø is correctly received. The effect of link layer (LL) parameters like the number of LL transmission attempts, offset ø , LL packet size, and FEC code rate on the TFRC (TCP Friendly Rate Control)and UDP performance is evaluated. We show that the combination of FEC and ARQ reduces the number of retransmissions and the time spent by a packet in the buffer at the output of the wireless link. We validate our analytical results using ns-2 [9]simulation
Visual Localization Ability Influences Cross-Modal Bias
Authors: W. D. Hairston, M. T. Wallace, J. W. Vaughan, B. E. Stein, J. L. Norris, J. A. Schirillo
Venue: Journal of Cognitive Neuroscience (2003)

The ability of a visual signal to influence the localization of an auditory target (i.e., "cross-modal bias") was examined as a function of the spatial disparity between the two stimuli and their absolute locations in space. Three experimental issues were examined: (a) the effect of a spatially disparate visual stimulus on auditory localization judgments; (b) how the ability to localize visual, auditory, and spatially aligned multisensory (visual - auditory) targets is related to cross-modal bias, and (c) the relationship between the magnitude of cross-modal bias and the perception that the two stimuli are spatially "unified" (i.e., originate from the same location). Whereas variability in localization of auditory targets was large and fairly uniform for all tested locations, variability in localizing visual or spatially aligned multisensory targets was much smaller, and increased with increasing distance from the midline. This trend proved to be strongly correlated with biasing effectiveness, for although visual&ndash;auditory bias was unexpectedly large in all conditions tested, it decreased progressively (as localization variability increased) with increasing distance from the midline. Thus, central visual stimuli had a substantially greater biasing effect on auditory target localization than did more peripheral visual stimuli. It was also apparent that cross-modal bias decreased as the degree of visual&ndash;auditory disparity increased. Consequently, the greatest visual&ndash;auditory biases were obtained with small disparities at central locations. In all cases, the magnitude of these biases covaried with judgments of spatial unity. The results suggest that functional properties of the visual system play the predominant role in determining these visual&ndash;auditory interactions and that cross-modal biases can be substantially greater than previously noted.
Waste collection vehicle routing problem with time windows
Authors: Byung-In Kim, Seongbae Kim, Surya Sahoo
Venue: Computers and Operations Research (2006)

In this paper, we address a real life waste collection vehicle routing problem with time windows (VRPTW) with consideration of multiple disposal trips and drivers' lunch breaks. Solomon's well-known insertion algorithm is extended for the problem. While minimizing the number of vehicles and total traveling time is the major objective of vehicle routing problems in the literature, here we also consider the route compactness and workload balancing of a solution since they are very important aspects in practical applications. In order to improve the route compactness and workload balancing, a capacitated clustering-based waste collection VRPTW algorithm is developed. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems at Waste Management, Inc. A set of waste collection VRPTW benchmark problems is also presented in this paper.Waste collection problems are frequently considered as arc routing problems without time windows. However, that point of view can be applied only to residential waste collection problems. In the waste collection industry, there are three major areas: commercial waste collection, residential waste collection and roll-on-roll-off. In this paper, we mainly focus on the commercial waste collection problem. The problem can be characterized as a variant of VRPTW since commercial waste collection stops may have time windows. The major variation from a standard VRPTW is due to disposal operations and driver's lunch break. When a vehicle is full, it needs to go to one of the disposal facilities (landfill or transfer station). Each vehicle can, and typically does, make multiple disposal trips per day. The purpose of this paper is to introduce the waste collection VRPTW, benchmark problem sets, and a solution approach for the problem. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems of Waste Management, the leading provider of comprehensive waste management services in North America with nearly 26,000 collection and transfer vehicles.
Supplementing Markov Chains with Additional Features for Behavioural Analysis
Authors: Nicholas Carter, David Young, James Ferryman
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

The combination of decision structures has been proposed by numerous researchers in the behavioural analysis domain, and been shown to improve accuracy over network structures tested in isolation; however, the vast majority of researchers use a simplistic combination strategy, amounting to little more than bridging of the network structures. This paper introduces a fusion mechanism between Bayesian and Markovian networks, which provides the Markov states with additional low-level features. This hybrid approach affords users a simplified network structure and provides the basis for an automatic technique, which allows the transitional probabilities in the network to be learned during online running of the system without the need for a training phase. The hybrid technique is validated using two very different datasets and is shown to outperform a standard network approach tested.
Approximation algorithms for the bi-criteria weighted MAX-CUT problem
Authors: Eric Angel, Evripidis Bampis, Laurent Gourvès
Venue: Discrete Applied Mathematics (2006)

We consider a generalization of the classical MAX-CUT problem where two objective functions are simultaneously considered. We derive some theorems on the existence and the non-existence of feasible cuts that are at the same time near optimal for both criteria. Furthermore, two approximation algorithms with performance guarantee are presented. The first one is deterministic while the second one is randomized. A generalization of these results is given for the bi-criteria MAX-k-CUT problem.