ppxscal/embedding_network huggingface dataset:
A city-wide vehicular infrastructure for wide-area wireless experimentation
Authors: Justin Ormont, Jordan Walker, Suman Banerjee, Ashwin Sridharan, Mukund Seshadri, Sridhar Machiraju
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

We describe our experiences in building a city-wide infrastructure for wide-area wireless experimentation. Our infrastructure has two components -(i) a vehicular testbed consisting of wireless nodes, each equipped with both cellular (EV-DO) and WiFi interfaces, and mounted on city buses plying in Madison, Wisconsin, and (ii) a software platform to utilize these testbed nodes to continuously monitor and characterize performance of large scale wireless networks, such as city-wide mesh networks, unplanned deployments of WiFi hotspots, and cellular networks. Beyond our initial efforts in building and deploying this infrastructure, we have also utilized it to gain some initial understanding of the diversity of user experience in large-scale wireless networks, especially under various mobility scenarios. Since our vehicle-mounted testbed nodes have fairly deterministic mobility patterns, they provide us with much needed performance data on parameters such as RF coverage and available bandwidth, as well as quantify the impact of mobility on performance. We use our initial measurements from this testbed to showcase its ability to provide an efficient, low-cost, and robust method to monitor our target wireless networks. These initial measurements also highlight the challenges we face as we continue to expand this infrastructure. We discuss what these challenges are and how we intend to address them.
Towards a Semantology of Music
Authors: Rudolf Wille, Renate Wille-Henning
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

The aim of this paper is to approach a Semantology of Music which is understood as the theory and methodology of musical semantic structures. The analysis of music structures is based on a threefold semantics which is performed on the musical level, the abstract philosophic-logical level, and the hypothetical mathematical level. Basic music structures are discussed by examples, in particular: tone systems, chords, harmonies, scales, modulations, musical time flow, and music forms. A specific concern of this paper is to clarify how a Semantology of Music may support the understanding of music.
Evaluation of Reference Tissue Model for Serotonin Transporters Using [123I] ADAM Tracer
Authors: Bang-Hung Yang, Shyh-Jen Wang, Yuan-Hwa Chou, Tung-Ping Su, Shih-Pei Chen, Jih-Shian Lee, Jyh-Cheng Chen
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

The serotonin transporters are target-sites for commonly used antidepressants. [123I] ADAM is a novel radiotracer that selectively binds the serotonin transporters (SERTs) of the central nervous system. The aim for this study was to evaluate a non-invasive reference tissue model for SERTs quantification using the cerebellum as the indirect input function. The four-parameter model (FPM) was compared with the three-parameter model (TPM) using [123I] ADAM dynamic brain SPECT images. The binding potential values derived from both models were the same, but the ratio of delivery (R1) in TPM had a smaller standard deviation than the FPM model. In conclusion, the simplified reference tissue model (TPM) was the better choice because of its stability (small standard deviation) and convenient implementation for non-invasive quantification of brain SPECT studies.
A New Unsupervised Approach to Face Recognition
Authors: Zizhu Fan, Ergen Liu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A new unsupervised approach to face recognition is proposed in this paper. Shape and color entropy is presented to descript face features. Firstly, images are pre-processed including face normalization and image segmentation and so on. Secondly, by using the information entropy theory, the method defines the color and shape entropy of the face images, respectively. Finally, an integrated similarity measurement framework is presented by computing mutual information between images according to these entropies. Compared with other methods of feature description, experiments indicate that this approach is more effective and efficient.
Dilation and Erosion of Spatial Bipolar Fuzzy Sets
Authors: Isabelle Bloch
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Bipolarity has not been much exploited in the spatial domain yet, although it has many features to manage imprecise and incomplete information that could be interesting in this domain. This paper is a first step to address this issue, and we propose to define mathematical morphology operations on bipolar fuzzy sets (or equivalently interval valued fuzzy sets or intuitionistic fuzzy sets).
Mining Causal Knowledge from Diagnostic Knowledge
Authors: Xiangdong An, Nick Cercone
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Diagnostic knowledge is the basis of many non-Bayesian medical systems. To explore the advantages of their Bayesian counterparts, we need causal knowledge. This paper investigates how to mine causal knowledge from the diagnostic knowledge. Experiments indicate the proposed mining method works pretty well.
Conquering Fine-Grained Blends of Design Patterns
Authors: L. Sabatucci, A. Garcia, N. Cacho, M. Cossentino, S. Gaglio
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

The reuse of design patterns in realistic software systems is often a result of blending multiple pattern elements together rather than instantiating them in an isolated manner. The explicit description of pattern compositions is the key for (i) documenting the structure and the behavior of blended patterns and, (ii) more importantly, supporting the reuse of composite patterns across different software projects. In this context, this paper proposes a fine-grained composition language for describing varying blends of design patterns based on their structural and behavioural semantics. The reusability and expressiveness of the proposed language are assessed through its application to 32 compositions of GoF patterns recurrently appearing in three different case studies: the OpenOrb middleware, the JHotDraw and JUnit frameworks.
A Proof of Security in O(2n) for the Xor of Two Random Permutations
Authors: Jacques Patarin
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

Xoring two permutations is a very simple way to construct pseudorandom functions from pseudorandom permutations. The aim of this paper is to get precise security results for this construction. Since such construction has many applications in cryptography (see [2,3,4,6] for example), this problem is interesting both from a theoretical and from a practical point of view. In [6], it was proved that Xoring two random permutations gives a secure pseudorandom function if $m \ll 2^{\frac {2n}{3}}$. By "secure" we mean here that the scheme will resist all adaptive chosen plaintext attacks limited to m queries (even with unlimited computing power). More generally in [6] it is also proved that with k Xor, instead of 2, we have security when $m \ll 2^{\frac {kn}{k+1}}$. In this paper we will prove that for k = 2, we have in fact already security when m ¿ O(2 n ). Therefore we will obtain a proof of a similar result claimed in [2] (security when m ¿ O(2 n /n 2/3)). Moreover our proof is very different from the proof strategy suggested in [2] (we do not use Azuma inequality and Chernoff bounds for example), and we will get precise and explicit O functions. Another interesting point of our proof is that we will show that this (cryptographic) problem of security is directly related to a very simple to describe and purely combinatorial problem. An extended version of this paper can be obtained on eprint [8].
Study on Implementation of High-Performance GIServices in Spatial Information Grid
Authors: Fang Huang, Dingsheng Liu, Guoqing Li, Yi Zeng, Yunxuan Yan
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Providing geo-spatial data services (GDS) and processing functionality services (PFS) are the key issues in spatial information grid (SIG). Especially, it's crucial for SIG to offer PFS related to Geographic Information Science (GIS), instead of just focused on Remote Sensing (RS) field. Furthermore, implementing high-performance GIServices is the main task of SIG to offer PFS for GIS. Lacking of high-performance GIServices mainly resulted from the limitations of architecture as well as the complexity for services implementation and encapsulation. Based on existing SIG platform, we propose the new architecture of SIG, upon which the constituted GIS nodes can provide GIServices. Within the improved architecture, some parallel GRASS GIS algorithms programs, which are built by different parallelization patterns and can run in cluster with better efficiency, are encapsulated to high-performance GIServices guiding by certain generic mode. Lastly, the analyses of the test demonstrate that the approach can reach our aims.
Are PHIGS and GKS Necessainly Incompatible?
Authors: Juergen Schoenhut
Venue: IEEE Computer Graphics and Applications (1986)

The compatiblility issues that are of concern through the graphics industry are particularly serious in the relationship of GKS, GKS-3D, and nowcomer PHICS. The point made in this article is that PHIGS can be brought more into line with the GKS standards, offering a broader range of applications to both sets of users.
A Script Driven Multimodal Embodied Conversational Agent Based on a Generic Framework
Authors: Hung-Hsuan Huang, Aleksandra Cerekovic, Igor S. Pandzic, Yukiko Nakano, Toyoaki Nishida
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

Embodied Conversational Agents (ECAs) are life-like CG characters that interact with human users in face-to-face conversations. To achieve natural conversations, they need to understand the inputs from human users, deliberate the responding behaviors and realize those behaviors in multiple modalities. They are sophisticated, require numbers of building assemblies and are thus difficult for individual research groups to develop. To facilitate result sharing and rapid prototyping of ECA researches, a Generic ECA Framework that is meant to integrate ECA assemblies seamlessly is being developed by our group. This framework is composed of a low-level communication platform (GECA Platform), a set of communication API libraries (GECA Plugs) and a high-level protocol (GECA Protocol, GECAP).
Dynamic Power Management with Scheduled Switching Modes
Authors: Paulo Sérgio Sausen, José Renato de Brito Sousa, Marco Aurélio Spohn, Angelo Perkusich, Antônio Marcus Nogueira Lima
Venue: Computer Communications (2008)

A Wireless Sensor Network (WSN) comprises many sensor nodes each one containing a processing unit, one or more sensors, a power unit, and a radio for data communication. Nodes are power constrained, because they run on batteries which usually cannot be replaced due to the nature of the applications. We present a novel dynamic power management approach, named Dynamic Power Management with Scheduled Switching Modes (DPM-SSM), derived from a more realistic analysis of the battery capacity recovery effect and the switching energy. This was only possible thanks to the application of a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). We also devised a Hybrid Differential Petri Nets formalism to evaluate our power management solution. Preliminary results showed the potential for improving the battery lifetime by taking advantage of the battery recovery effect when a node transitions to a sleeping state mostly after packet transmissions. DPM-SSM provides several DPM modes which are triggered depending on the battery remaining capacity. Simulations results show that, depending on the scheduling approach, DPM-SSM can provide real battery power recovery without compromising the timeliness of the applications running on the sensor network.
Correlation, Independance and Inverse Modeling
Authors: V. Vigneron
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

Learning from examples has a wide number of forms depending on what is to be learned from which available information. One of these form is y = f(x) where the input-output pair (x,y) is the available information and f represents the process mapping ${\bf x}\in\cal X$ to ${\bf y}\in\cal Y$. In general and for real world problems, it is not reasonnable to expect having the exact representation of f. A fortiori when the dimension of x is large and the number of examples is little. In this paper, we introduce a new model, capable to reduce the complexity of many ill-posed problems without loss of generality. The underlying Bayesian artifice is presented as an alternative to the currently used frequency approaches which does not offer a compelling criterion in the case of high dimensional problems.
Towards an Illumination-Based 3D Active Appearance Model for Fast Face Alignment
Authors: Salvador E. Ayala-Raggi, Leopoldo Altamirano-Robles, Janeth Cruz-Enriquez
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

A novel 3D active appearance model invariant to illumination is presented. 3D-IAAM (Tridimensional Illumination-based Active Appearance Model) is capable of representing human faces with any identity, pose and illumination condition and it was tested for face synthesis by creating faces with multiple identities, poses and illuminations. We also propose an illumination-invariant 3D face alignment algorithm based on our model which is suitable for fast estimation of 3D pose and structure of faces. In this work, we model the illumination to do the alignment, instead of eliminating its effects, with the possibility of obtaining additional information about the original lighting at the end of the fitting process.
Modeling team performance for coordination configurations of large multi-agent teams using stochastic neural networks
Authors: Jumpol Polvichai
Venue:  (2007)

Coordination of large numbers of agents to perform complex tasks in complex domains is a rapidly progressing area of research. Because of the high complexity of the problem, approximate and heuristic algorithms are typically used for key coordination tasks. Such algorithms usually require tuning algorithm parameters to yield the best performance under particular circumstances. Manually tuning parameters is sometimes difficult. In domains where characteristics of the environment can vary dramatically from scenario to scenario, it is desirable to have automated techniques for appropriately configuring the coordination. This research presents an approach to online reconfiguration of heuristic coordination algorithms. The approach uses an abstract simulation to produce a large data set to train a stochastic neural network that concisely models the complex, probabilistic relationship between configurations, environments and performance metrics. The final stochastic neural network, referred as the team performance model, is then used as the core of a tool that allows rapid online or offline configuration of coordination algorithms to particular scenarios and user preferences. The overall system allows rapid adaptation of coordination, leading to better performance in new scenarios. Results show that the team performance model captured key features of a very large configuration space and mostly captured the uncertainty in performance as well. The tool was shown to be often capable of reconfiguring the algorithms to meet user requests for increases or decreases in performance parameters. This work represents the first practical approach to quickly reconfiguring complex sets of algorithms for a specific application.
Exact Transcriptome Reconstruction from Short Sequence Reads
Authors: Vincent Lacroix, Michael Sammeth, Roderic Guigo, Anne Bergeron
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

In this paper we address the problem of characterizing the RNA complement of a given cell type, that is, the set of RNA species and their relative copy number, from a large set of short sequence reads which have been randomly sampled from the cell's RNA sequences through a sequencing experiment. We refer to this problem as the transcriptome reconstruction problem, and we specifically investigate, both theoretically and practically, the conditions under which the problem can be solved. We demonstrate that, even under the assumption of exact information, neither single read nor paired-end read sequences guarantee theoretically that the reconstruction problem has a unique solution. However, by investigating the behavior of the best annotated human gene set, we also show that, in practice, paired-end reads --- but not single reads --- may be sufficient to solve the vast majority of the transcript variants species and abundances. We finally show that, when we assume that the RNA species existing in the cell are known, single read sequences can effectively be used to infer transcript variant abundances.
Security Aspects for Secure Download of Regulated Software
Authors: Sibylle Hick, Christoph Ruland
Venue: Proceedings of the 4th international conference on Trust, Privacy and Security in Digital Business (2007)

Software can be found in a lot of different infrastructures in our daily life e.g. mobile phones, cars, or ticket machines. Due to always increasing requirements or failures in programs, updates are needed at all times and mean a great cost and time advantage. Not always can the technical possibility to download software components be realized right away because various security issues or legal restraints have to be taken into account. This paper introduces a security architecture for regulated software download that is performed in the area of measuring instruments but can also be applied for other infrastructures. Therefore at first the legal requirements in which the software download is performed --- here the liberalized energy market - is introduced. Furthermore different security requirements that are necessary to connect the technical and legal needs are presented. The analysis of the legal situation, the participants, resources, and threads draws a total picture of the system. Starting from these conclusions an infrastructure that supports the different security aspects will be presented.
Behavior Preservation in Model Refactoring Using DPO Transformations with Borrowed Contexts
Authors: Guilherme Rangel, Leen Lambers, Barbara König, Hartmut Ehrig, Paolo Baldan
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Behavior preservation, namely the fact that the behavior of a model is not altered by the transformations, is a crucial property in refactoring. The most common approaches to behavior preservation rely basically on checking given models and their refactored versions. In this paper we introduce a more general technique for checking behavior preservation of refactorings defined by graph transformation rules. We use double pushout (DPO) rewriting with borrowed contexts, and, exploiting the fact that observational equivalence is a congruence, we show how to check refactoring rules for behavior preservation. When rules are behavior-preserving, their application will never change behavior, i.e., every model and its refactored version will have the same behavior. However, often there are refactoring rules describing intermediate steps of the transformation, which are not behavior-preserving, although the full refactoring does preserve the behavior. For these cases we present a procedure to combine refactoring rules to behavior-preserving concurrent productions in order to ensure behavior preservation. An example of refactoring for finite automata is given to illustrate the theory.
Automatic Learning of Conceptual Knowledge in Image Sequences for Human Behavior Interpretation
Authors: Pau Baiget, Carles Fernández, Xavier Roca, Jordi Gonzàlez
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

This work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source is the geometrical data obtained by applying tracking algorithms to an image sequence, which is used to generate conceptual data. The spatial characteristics of the scene are automatically extracted from the resuling tracking trajectories obtained during a training period. Interpretation is achieved by means of a rule-based inference engine called Fuzzy Metric Temporal Horn Logic and a behavior modeling tool called Situation Graph Tree. These tools are used to generate conceptual descriptions which semantically describe observed behaviors.
Parameter determination of support vector machine and feature selection using simulated annealing approach
Authors: Shih-Wei Lin, Zne-Jung Lee, Shih-Chieh Chen, Tsung-Yuan Tseng
Venue: Applied Soft Computing (2008)

Support vector machine (SVM) is a novel pattern classification method that is valuable in many applications. Kernel parameter setting in the SVM training process, along with the feature selection, significantly affects classification accuracy. The objective of this study is to obtain the better parameter values while also finding a subset of features that does not degrade the SVM classification accuracy. This study develops a simulated annealing (SA) approach for parameter determination and feature selection in the SVM, termed SA-SVM. To measure the proposed SA-SVM approach, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate. The proposed approach was compared with grid search which is a conventional method of performing parameter setting, and various other methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of grid search and other approaches. The SA-SVM is thus useful for parameter determination and feature selection in the SVM.
Optimal Control of Switched System Based on Neural Network Optimization
Authors: Rong Long, Jinming Fu, Liyan Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

The optimal control problem of switched system is to find both the optimal control input and optimal switching signal and is a mixed integer problem. High computational burden in solving this problem is a major obstacle. To solve this problem, this paper presented hybrid neural network combining continuous neurons and discrete neurons and designed lyapunov function to guarantee the convergency of proposed hybrid neural network. This new solution method is more suitable to parallel implementation than the mathematical programming. Simulation results show that this approach can utilize fast converge property and the parallel computation ability of neural network and apply to real-time control.