ppxscal/embedding_network huggingface dataset:
Context-Aware Optimal Assignment of a Chain-Like Processing Task onto Chain-Like Resources in M-Health
Authors: Hailiang Mei, Ing Widya
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

This paper focuses on the optimal assignment of a chain-structured medical task onto a chain of networked devices, a need identified in context-aware mobile healthcare applications. We propose a graph-based method to compute the assignment which has the minimal end-to-end process and transfer delay. In essence, the method transforms the assignment problem to a shortest path problem in a graph representing all possible assignments. Compared to earlier work, our method relaxes a so-called contiguity constraint, which is a necessity in the earlier case but unnecessarily constraining in the healthcare applications. The proposed method reduces the time and space complexity in case it is adapted to include the contiguity constraint.
Versatile IPv6 mobility deployment with dual stack mobile IPv6
Authors: Romain Kuntz, Jean Lorchat
Venue: Proceedings of the 3rd international workshop on Mobility in the evolving internet architecture (2008)

In this paper, we show how Mobile IPv6 support for dual stack Hosts and Routers (DSMIPv6) can be used as a very efficient, automatic and autonomous way of network planning as well as a multipurpose mobility solution. Along with the details of the Linux-based implementation, we show the results of measurements made against a test scenario that heavily relies on DSMIPv6. We also discuss the next steps and remaining specification issues that should be tackled in order to ensure a rapid deployment of the protocol.
Semantic Querying of Business Process Models
Authors: Ahmed Awad, Artem Polyvyanyy, Mathias Weske
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

Determining similarity between business process models has recently gained interest in the business process management community. So far similarity was addressed separately either at semantic or structural aspect of process models. Also, most of the contributions that measure similarity of process models assume an ideal case when process models are enriched with semantics---a description of meaning of process model elements. However, in real life this results in a heavy human effort consuming pre-processing phase which is often not feasible. In this paper we propose an automated approach for querying a business process model repository for structurally and semantically relevant models. Similar to the search on the Internet, a user formulates a BPMN-Q query and as a result receives a list of process models ordered by relevance to the query. We provide a business process model search engine implementation for evaluation of the proposed approach.
Noise Reduction Using Thresholding-Based Algorithm and Homogeneous-Frame-Merged Approach for Wavelet-Packet Transform
Authors: Ching-Ta Lu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Improving speech quality for a corrupted signal is still an important task for voice communication. This investigation proposes to incorporate thresholding-based algorithm with homogeneous-frame-merged (HFM) approach to adapt a gain factor. In turn, we employ this gain factor to reduce the noise components for a corrupted signal. Firstly, a fixed-length frame is employed to calculate the power of noisy wavelet coefficient. Afterwards, merging homogeneous frames in a segment is performed to estimate the power of speech wavelet coefficient. Substituting this speech power in wavelet coefficient to the thresholding-based algorithm, enhanced speech signal is then obtained. Experimental results show that the proposed gain factors vary smoothly among homogeneous frames for each subband, enabling the residual noise to be reduced significantly.
Discovery of Genetic Networks Through Abduction and Qualitative Simulation
Authors: Blaž Zupan, Ivan Bratko, Janez Demšar, Peter Juvan, Adam Kuspa, John A. Halter, Gad Shaulsky
Venue: Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences (2007)

GenePath is an automated system for reasoning about genetic networks, wherein a set of genes have various influences on one another and on a biological outcome. It acts on a set of experiments in which genes are knocked-out or overexpressed, and the outcome of interest is evaluated. Implemented in Prolog, GenePath uses abductive inference to elucidate network constraints based on background knowledge and experimental results. Two uses of the system are demonstrated: synthesis of a consistent network from abduced constraints, and qualitative reasoning-based approach that generates a set of networks consistent with the data. In practice, as illustrated by an example on aggregation of a soil amoeba Dictyostelium discoideum, a combination of constraint satisfaction and qualitative reasoning produces a small set of plausible networks.
Web Customer Modeling for Automated Session Prioritization on High Traffic Sites
Authors: Nicolas Poggi, Toni Moreno, Josep Lluis Berral, Ricard Gavaldà, Jordi Torres
Venue: Proceedings of the 11th international conference on User Modeling (2007)

In the Web environment, user identification is becoming a major challenge for admission control systems on high traffic sites. When a web server is overloaded there is a significant loss of throughput when we compare finished sessions and the number of responses per second; longer sessions are usually the ones ending in sales but also the most sensitive to load failures. Session-based admission control systems maintain a high QoS for a limited number of sessions, but does not maximize revenue as it treats all non-logged sessions the same. We present a novel method for learning to assign priorities to sessions according to the revenue that will generate. For this, we use traditional machine learning techniques and Markov-chain models. We are able to train a system to estimate the probability of the user's purchasing intentions according to its early navigation clicks and other static information. The predictions can be used by admission control systems to prioritize sessions or deny them if no resources are available, thus improving sales throughput per unit of time for a given infrastructure. We test our approach on access logs obtained from a high-traffic online travel agency, with promising results.
Enculturating Conversational Agents Based on a Comparative Corpus Study
Authors: Afia Akhter Lipi, Yuji Yamaoka, Matthias Rehm, Yukiko I. Nakano
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

When encountering people who have a different cultural background from our own, many of us feel uncomfortable because gestures and facial expressions may not be familiar to us. Thus, to enhance the believability of conversational agents, culture-specific nonverbal behaviors should be implemented into the agents. In our previous study [1], with the goal of building a user interface that incorporates a user's cultural background, we have collected comparative conversation corpus in Germany and Japan, and investigated the differences in gestures and posture shifts between these two countries. Based on [1], this paper reports a more detailed analysis about posture shifts, and proposes a chat system with an embodied conversational agent (ECA) that can act as a language trainer.
Prediction of sand ripple geometry under waves using an artificial neural network
Authors: Bing Yan, Qing-He Zhang, Onyx W. H. Wai
Venue: Computers Geosciences (2008)

The length and height of a sand ripple in the seabed are the two basic parameters used to estimate the bottom shear stress and predict the transport of sand by wave action. These values are currently obtained with the help of many empirical equations. A different estimation method, in the form of an artificial neural network, is presented in this paper. The network is trained by measurements collected in the laboratory and in-situ under different forcing conditions. Validation of the present neural network results with different measurements shows that the new method can predict the ripple length and height much more accurately than the conventional empirical equations.
Research on Skeletonization of Palmprint Image
Authors: Yuanfang Liu, Yan Zheng, Guangshun Shi, Qingren Wang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Skeletonization is an important procedure of automated palmprint identification system based on the characteristic of minutiae. Skeleton acquired by traditional thinning algorithms will produce many spurious minutiae which are caused by spurs and misconnections between ridges. The excessive erosion is also a common problem in thinning algorithm. Moreover, unit skeleton cannot be produced by some of these algorithms. In this paper, we introduce a thinning algorithm, which is based on Rotation Invariant Thinning Algorithm introduced by Ahmed and Ward (A-W). The proposed method can solve the above problems. The experimental result shows some skeletons from local regions of palmprint images and running time of the algorithm, which shows that the proposed algorithm can achieve better performance without reducing efficiency.
The DoD Initiative in Integrated Circuits
Authors: R. M. Davis
Venue: Computer (1979)

The Department of Defense's Very High-Speed IC Program includes research in areas such as submicron fabrication technology and advanced signal processing. DoD foresees results beneficial to both commercial and military applications. 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
Periodic and antiperiodic eigenvalues for quasilinear differential equations
Authors: Gabriella Bognár
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

The nonlinear eigenvalue problem of the differential equation (|x′|p-2 x′)′ + (λ + c(t)) |x|p-2 x=0, p > 1, with respect to the periodic boundary conditions: x(0) = x(T), x′(0) = x′(T), or to the antiperiodic boundary conditions: x(0) = -x(T), x′(0) = -x′(T) are considered. Various results on the set of eigenvalues concerning both problems are presented. Some estimates are given for the periodic and antiperiodic eigenvalues.
Discrete Frequency Selection of Frame-Based Stochastic Real-Time Tasks
Authors: Vandy Berten, Chi-Ju Chang, Tei-Wei Kuo
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

Energy-efficient real-time task scheduling has been actively explored in the past decade. Different from the past work, this paper considers schedulability conditions for stochastic real-time tasks. A schedulability condition is first presented for frame-based stochastic real-time tasks, and several algorithms are also examined to check the schedulability of a given strategy. An approach is then proposed based on the schedulability condition to adapt a continuous-speed-based method to a discrete-speed system. The approach is able to stay as close as possible to the continuous-speed-based method, but still guaranteeing the schedulability. It is shown by simulations that the energy saving can be more than 20% for some system configurations.
Fuzzy Modelling Methodologies for Large Database
Authors: Virgilio López Morales, Julio Cesar Ramos Fernández, Gilles Enea, Jean Duplaix
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

In this paper we analyze two recent modelling methodologies: one based on a database preprocessing and then, the application of the fuzzy C-means to highlight useful characteristics used in target selection for direct marketing which is our first study case. The second one is based on fuzzy clustering and cubic splines in the rule consequents. Some examples are given in order to illustrate the advantages and drawbacks of these methods.
A Novel Frequency Offset Estimation Algorithm Using Differential Combining for OFDM-Based WLAN Systems
Authors: Sangho Ahn, Sanghun Kim, Hyoung-Kee Choi, Sun Yong Kim, Seokho Yoon
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The timing offset is one of the main error sources in estimating the frequency offset in orthogonal frequency division multiplexing (OFDM)-based wireless local area network (WLAN) systems. Although some works have been done to mitigate the effect of the timing offset on the frequency offset estimation, most of the investigations require the knowledge of the timing offset range, which is not generally available in practical systems. In this paper, we propose a new frequency offset estimation algorithm using differential combining between two successive correlation samples, which does not require the knowledge of the timing offset range, and thus, is robust to the timing offset variation. The simulation results show that the proposed algorithm is not only robust to the timing offset variation, but also generally performs better than the conventional algorithm, in the case of the timing offset range being not known exactly.
A Deeper Look at 3D Soccer Simulations
Authors: Amin Habibi Shahri, Ali Almasi Monfared, Mohammad Elahi
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Developing an intelligent agent requires more than an Integrated Development Environment (IDE). In multi agent environments or systems equipped with artificial intelligence it is often difficult to obtain the function or method which led to a particular behavior that is noticeable from outside. In addition to previous dilemma, the publicity that the RoboCup events get from the media provides an ideal opportunity to show the state of art of these systems during RoboCup World Cup.This paper describes the concept and the implementation of Team Assistant 2006 as the next generation of TA2002. The idea is to provide a tool that is able to assist developers to detect problems of their agents both in single and cooperation mode and also organizers to have better games.TA2006 won the second place in RoboCup 3D development competition 2006.
Adaptive video communication for an intelligent distributed system: Tuning sensors parameters for surveillance purposes
Authors: Christian Micheloni, Marco Lestuzzi, Gian Luca Foresti
Venue: Machine Vision and Applications (2008)

Surveillance systems include a large set of techniques for both low level and high level tasks. In particular, in the last decade the research community has witnessed a high proliferation of techniques that span from object detection and tracking to object recognition and event understanding. Although some techniques have been proved to be very effective, those tasks cannot be considered solved. Even less, we can consider concluded the research in the field of the analysis of the activities (event analysis). It is this topic together with the problem of the information sharing among different sensors that represents the core of this work. Here, a system architecture for a video surveillance system with distributed intelligence over multiple processing units and with distributed communication over multiple heterogeneous channels (wireless, satellite, local IP networks, etc.) is proposed. A new real-time technique for changing the video transmission parameters (e.g., frame rate, spatial/colour resolution, etc.) according to the available bandwidth (which depends on the number of the detected alarm situations, on the required video quality, etc.) will be presented.
Distance browsing in distributed multimedia databases
Authors: Fabrizio Falchi, Claudio Gennaro, Fausto Rabitti, Pavel Zezula
Venue: Future Generation Computer Systems (2009)

The state of the art of searching for non-text data (e.g., images) is to use extracted metadata annotations or text, which might be available as a related information. However, supporting real content-based audiovisual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, such search exhibits linear scalability with respect to the dataset size, so parallel query execution is needed. In this paper, we present a Distributed Incremental Nearest Neighbor algorithm (DINN) for finding closest objects in an incremental fashion over data distributed among computer nodes, each able to perform its local Incremental Nearest Neighbor (local-INN) algorithm. We prove that our algorithm is optimum with respect to both the number of involved nodes and the number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset. The proposed algorithm is being used in two running projects: SAPIR and NeP4B.
A New Robust Watermarking Scheme for Color Image in Spatial Domain
Authors: Ibrahim Nasir, Ying Weng, Jianmin Jiang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

This paper presents a new robust watermarking scheme for color image based on a block probability inspatial domain. A binary watermark image is permutated using sequence numbers generated by a secret key and Gray code, and then embedded four times in different positions by a secret key. Each bit of the binary encoded watermark is embedded by modifying the intensities of anon-overlapping block of 8*8 of the blue component ofthe host image. The extraction of the watermark is bycomparing the intensities of a block of 8*8 of the watermarked and the original images and calculating the probability of detecting '0' or '1'. Tested by benchmark Stirmark 4.0, the experimental results show that the proposed scheme is robust and secure against a widerange of image processing operations.
The gait analysis for modular walking robot MERO walks on the slope
Authors: Ion Ion, Luige Vladareanu, Ion Simionescu, Aurelian Vasile
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

The performance of a legged system is closely related to the adopted gait. The main characteristic of the modular walking robots is that they are able to move away on not arranged, horizontal and rough terrain. The performance of walking robots is closely related to the adopted gait. The movement of the walking robots can be divided in two modes: - condition of the static stability; - condition of the dynamic stability. During walking, the legs move according to the wave gait and two forelegs are adjusted to avoid forbidden areas. Different methods of leg adjustments and body adjustments are integrated into the strategy. In the work are analyzed the possibilities of determination of the limit conditions for the stable displacement of the walking robots. Finally, this strategy is verified by using computer graphics simulations.
Pleiades: Subspace Clustering and Evaluation
Authors: Ira Assent, Emmanuel Müller, Ralph Krieger, Timm Jansen, Thomas Seidl
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Subspace clustering mines the clusters present in locally relevant subsets of the attributes. In the literature, several approaches have been suggested along with different measures for quality assessment.Pleiades provides the means for easy comparison and evaluation of different subspace clustering approaches, along with several quality measures specific for subspace clustering as well as extensibility to further application areas and algorithms. It extends the popular WEKA mining tools, allowing for contrasting results with existing algorithms and data sets.
Better external memory suffix array construction
Authors: Roman Dementiev, Juha Kärkkäinen, Jens Mehnert, Peter Sanders
Venue: Journal of Experimental Algorithmics (JEA) (2008)

Suffix arrays are a simple and powerful data structure for text processing that can be used for full text indexes, data compression, and many other applications, in particular, in bioinformatics. However, so far, it has appeared prohibitive to build suffix arrays for huge inputs that do not fit into main memory. This paper presents design, analysis, implementation, and experimental evaluation of several new and improved algorithms for suffix array construction. The algorithms are asymptotically optimal in the worst case or on average. Our implementation can construct suffix arrays for inputs of up to 4-GB in hours on a low-cost machine. As a tool of possible independent interest, we present a systematic way to design, analyze, and implement pipelined algorithms.
Detection of Sprague Dawley Sperm Using Matching Method
Authors: Mohd Fauzi Alias, Nor Ashidi Mat Isa, Siti Amrah Sulaiman, Kamal Zuhairi Zamli
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Cross correlation algorithm is the common method for image matching technique. In this paper, an expert system based on cross correlation is designed to reduce the workload of pathologist and improve the screening technology in medical field. The system is proposed to detect, locate and classify between normal and abnormal sperm head by evaluating the similarity between two images. Using cross correlation, the highest value near to one is defined as the best matching value. When this condition is obeyed, the system shows the matched image at the output together with the matching indicator. Such result indicates this system is very helpful to pathologist.
Tuning Constrained Objects
Authors: Ricardo Soto, Laurent Granvilliers
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

Constrained objects provide a suitable object-oriented style for modeling systems under constraints. A set of classes is defined to represent a problem, whose state is then controlled by a constraint satisfaction engine. This engine is commonly a black-box based on a predefined and non-customizable search strategy. This system rigidity, of course, does not allow users to tune models in order to improve the search process. In this paper we target this issue by presenting an extensible formalism to define a wide range of search options so as to customize, improve and/or analyze the search process of constrained object models.
New Error Function for Single Hidden Layer Feedforward Neural Networks
Authors: Leong Kwan Li, Richard Chak Hong Lee
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Feedforward neural networks (FNN) are most heavily used to identify the relation between a given set of input and desired output patterns. By the universal approximation theorem, it is clear that a single-hidden layer FNN is suffcient for the outputs to approximate the corresponding desired outputs arbitrarily close and so we consider a single-hidden layer FNN. In practice, we set up an error function so as to measure the performance of the FNN. As the error function is nonlinear, we define an iterative process, learning algorithm, to obtain the optimal choice of the connection weights and thus set up a numerical optimization problem. In this paper, we consider a new error function defined on the hidden layer We propose a new learning algorithm based on the least square methods converges rapidly. We discuss our method with the classic learning algorithms and the convergence for these algorithms.