ppxscal/embedding_network huggingface dataset:
A stratified traffic sampling methodology for seeing the big picture
Authors: Stênio Fernandes, Carlos Kamienski, Judith Kelner, Dênio Mariz, Djamel Sadok
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as powerful tools for deriving traffic properties at the flow level. Our results show that the adequate selection of samples leads to significant improvements allowing further important statistical analysis. Although stratified sampling is a well-known technique, the way we classify the data prior to sampling is innovative and deserves special attention. We evaluate two partitioning clustering methods, namely clustering large applications (CLARA) and K-means, and validate their outcomes by using them as thresholds for stratified sampling. We show that using flow sizes to divide the population we can obtain accurate estimates for both size and flow durations. The presented sampling and clustering classification techniques achieve data reduction levels higher than that of existing methods, on the order of 0.1% while maintaining good accuracy for the estimates of the sum, mean and variance for both flow duration and sizes.
Analysis of Alarm Sequences in a Chemical Plant
Authors: Savo Kordic, Peng Lam, Jitian Xiao, Huaizhong Li
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Oil and gas industries need secure and cost-effective alarm systems to meet safety requirements and to avoid problems that lead to plant shutdowns, production losses, accidents and associated lawsuit costs. Although most current distributed control systems (DCS) collect and archive alarm event logs, the extensive quantity and complexity of such data make identification of the problem a very labour-intensive and time-consuming task. This paper proposes a data mining approach that is designed to support alarm rationalization by discovering correlated sets of alarm tags. The proposed approach was initially evaluated using simulation data from a Vinyl Acetate model. Experimental results show that our novel approach, using an event segmentation and data filtering strategy based on a cross-effect test is significant because of its practicality. It has the potential to perform meaningful and efficient extraction of alarm patterns from a sequence of alarm events.
ODAM: An Optimized Distributed Association Rule Mining Algorithm
Authors: Mafruz Zaman Ashrafi, David Taniar, Kate Smith
Venue: IEEE Distributed Systems Online (2004)

Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, ODAM is a distributed algorithm for geographically distributed data sets that reduces communication costs.
Fitness Expectation Maximization
Authors: Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

We present Fitness Expectation Maximization (FEM), a novel method for performing `black box' function optimization. FEM searches the fitness landscape of an objective function using an instantiation of the well-known Expectation Maximization algorithm, producing search points to match the sample distribution weighted according to higher expected fitness. FEM updates both candidate solution parameters and the search policy, which is represented as a multinormal distribution. Inheriting EM's stability and strong guarantees, the method is both elegant and competitive with some of the best heuristic search methods in the field, and performs well on a number of unimodal and multimodal benchmark tasks. To illustrate the potential practical applications of the approach, we also show experiments on finding the parameters for a controller of the challenging non-Markovian double pole balancing task.
A Stratified Approach for Automatic Stellar Spectra Classification
Authors: J. N. Zhang, A. L. Luo, L. P. Tu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In this paper we present an automatic stellar spectra classification system to achieve two goals: one is the main-class and subclass classification, the other is luminosity type recognition. The system is composed of 3 functional units, namely main-class and subclass classification, continuum spectra normalization, luminosity type determination. This work's main novelties are 2 folds: 1) A stratified approach is proposed for classification. The main-class and subclass of star is firstly determined, and then according to the main-class type, luminosity type is recognized through luminosity type determination unit. The luminosity type determination unit is composed by seven models based on PLS method each corresponding one of the seven mainclass type. 2) We use the non-parameter regression method to robustly determine the main-class and subclass, and PLS regression method to determine the luminosity type. Experiments show that our system is feasible for the low-resolution spectra classification.
An Iterative Framework for Software Architecture Recovery: An Experience Report
Authors: Banani Roy, T. C. Graham
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Both architecture recovery and architecture evaluation play an important role in the area of software reverse-engineering. In this paper, we propose and evaluate a framework for incremental and iterative application of automated architecture recovery (using SWAG Kit) and architecture analysis (using SAAM.) We conclude that SWAG Kit helps in generating a low-level architecture that forms the basis of analysis, while SAAM helps in deriving from this a deeply understood conceptual architecture. The process is iterative, where SAAM analysis helps refine the parameters fed to SWAG Kit, in turn leading to a superior architecture for further analysis. We have applied this process to the extraction of the architectures of three open source compression tools, and we report on the strengths and weaknesses of the approach that this case study exposed. Over all, we conclude that the framework allowed us to understand the software architectures more deeply than would have been possible with the software architecture recovery process alone.
A Method for Automatic Text Categorization Using Word Sense Disambiguation
Authors: Azucena Montes Rendon, Rocio Vargas A., Hugo Estrada Esquivel, Juan G. Gonzalez Serna, Jose Ruiz Ascencio
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

At present time, Information plays a relevant role in current societies. In this context, Internet is one of the most extended mechanisms to communicate and distribute information around the word. Today, due to the extremely large number of information sources, automatic mechanisms are needed to filter the information that could be useful for each user. However, one of the problems that the usual techniques of automatic text categorization have not been able to handle is polysemy (words with two o more senses). In this paper, we have faced this problem by proposing a semantic analyzer for the automatic categorization of texts in Spanish. Context exploration techniques were used as a key mechanism for guiding the disambiguation process. A specific lexical database and its existing semantic relations fulfilled the objective of appropriately categorizing the analyzed text. To validate this analyzer, a tool was developed that classifies web pages by semantic sense. We present performance results for this classifier. Finally, a comparison with four other classification tools is reported.
Semiring-Based Soft Constraints
Authors: Stefano Bistarelli, Francesca Rossi
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

The semiring-based formalism to model soft constraint has been introduced in 1995 by Ugo Montanari and the authors of this paper. The idea was to make constraint programming more flexible and widely applicable. We also wanted to define the extension via a general formalism, so that all its instances could inherit its properties and be easily compared. Since then, much work has been done to study, extend, and apply this formalism. This papers gives a brief summary of some of these research activities.
Developing, implementing and evaluating computer-based instruction
Authors: Susan Kiger
Venue:  (2008)

In today's mobile world, society needs mobile education. The conventional system of education was designed in the industrial age, but needs are changing. To meet the needs of this generation, the present system of education must be renovated. This study suggests computer-based instruction as a solution. The study aims to investigate if there are any significant differences in the final learning outcomes between those students who participated in a computer-based instruction model and those students who participated in a traditional instruction model for a course at the College of Education of Indiana State University in the fall of 2007. There are three important phases in this study: the development, implementation and evaluation of computer-based instruction. The 'Analysis Design Develop Implement Evaluate' (ADDIE) model was used to develop the computer-based model. The developed instruction was implemented in the fall of 2007 for the students enrolled in the course CIMT 272, Introduction to Classroom Computer Use, Section 001. Evaluation of the participants indicated that there were no significant differences in the final learning outcomes between those students instructed via computer and those students instructed through traditional classes. A program evaluation indicated that, though students demanded freedom to access instruction as per their own schedules, they preferred to complement their studies with traditional lectures. It might be advantageous to consider a mixed model which combines both the computer-based instruction model and traditional instruction model, instead of simply relying exclusively on one or the other.
Real-Time String Filtering of Large Databases Implemented Via a Combination of Artificial Neural Networks
Authors: Tatiana Tambouratzis
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

A novel approach to real-time string filtering of large databases is presented. The proposed approach is based on a combination of artificial neural networks and operates in two stages. The first stage employs a self-organizing map for performing approximate string matching and retrieving those strings of the database which are similar to (i.e. assigned to the same SOM node as) the query string. The second stage employs a harmony theory network for comparing the previously retrieved strings in parallel with the query string and determining whether an exact match exists. The experimental results demonstrate accurate, fast and database-size independent string filtering which is robust to database modifications. The proposed approach is put forward for general-purpose (directory, catalogue and glossary search) and Internet (e-mail blocking, intrusion detection systems, URL and username classification) applications.
Eighty-Color-Channel Lighting
Authors: Zoltán Márton, Cecília Sik Lányi
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Lighting simulation programs nowadays still use the CPU using global illumination. On the other hand computer games still use three channel color calculations. The modern GPUs (Graphics Processing Units) have enough performance to use more channels. Using more color (spectral) channels can create a more realistic virtual world. In this paper, we introduce a method to provide a better lighting for future's computer games and a possible replacement in some cases for those software render programs.
Checking the Integrity Constraints of Mobile Databases with Three-Level Model
Authors: Hamidah Ibrahim, Zarina Dzolkhifli, Praveen Madiraju
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

In a mobile environment, due to the various constraints inherited from limitations of wireless communication and mobile devices, checking for integrity constraints to maintain the consistent state of mobile databases is an important issue that needs to be addressed. Hence, in this paper we propose Three-Level (3-L) model, wherein the process of constraint checking is realized at three different levels. Here, we use sufficient and complete tests together with the idea of caching relevant data items during the relocation period for checking the integrity constraints. This has improved the checking mechanism by preventing delays during the process of checking constraints and performing the update. Also, the 3-L model reduces the amount of data accessed given that much of the tasks are performed at the mobile host. Hence, our model speeds up the checking process.
Simultaneous Presentation of Tactile and Auditory Motion on the Abdomen to Realize the Experience of "Being Cut by a Sword"
Authors: Sayaka Ooshima, Yuki Hashimoto, Hideyuki Ando, Junji Watanabe, Hiroyuki Kajimoto
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

We propose a multimodal interface on the abdomen to realize the experience of "being cut by a sword", for gaming applications. Tactile and auditory sensations were simultaneously presented on the abdomen by using sparsely located tactors and densely located speakers. We compared motion of the two modalities, and compared tactile apparent movement with auditory motion, focusing on the position and speed. Subjectively equivalent position and velocity of the two modalities matched well.
Semantics for a domain-specific language for the digital forensics domain
Authors: Phillip G. Bradford, Daniel A. Ray
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

This paper reviews details around the motivation for creating a domain-specific language that allows the easy design of software tools that support digital investigation. These tools will enable the specification of security requirements, support the activities of various investigations, certify security properties, and formulate security claims. Additionally, the main purpose of this paper is to introduce a proposed syntax for a language that is appropriate to the specific needs of the digital investigation domain.
Preservation of Proof Obligations from Java to the Java Virtual Machine
Authors: Gilles Barthe, Benjamin Grégoire, Mariela Pavlova
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

While program verification environments typically target source programs, there is an increasing need to provide strong guarantees for executable programs.We establish that it is possible to reuse the proof that a source Java program meets its specification to show that the corresponding JVM program, obtained by non-optimizing compilation, meets the same specification. More concretely, we show that verification condition generators for Java and JVM programs generate the same set of proof obligations, when applied to a program p and its compilation [[p]] respectively.Preservation of proof obligations extends the applicability of Proof Carrying Code, by allowing certificate generation to rely on existing verification technology.
Analysis-by-Synthesis by Learning to Invert Generative Black Boxes
Authors: Vinod Nair, Josh Susskind, Geoffrey E. Hinton
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

For learning meaningful representations of data, a rich source of prior knowledge may come in the form of a generative black box, e.g. a graphics program that generates realistic facial images. We consider the problem of learning the inverse of a given generative model from data. The problem is non-trivial because it is difficult to create labelled training cases by hand, and the generative mapping is a black box in the sense that there is no analytic expression for its gradient. We describe a way of training a feedforward neural network that starts with just one labelled training example and uses the generative black box to "breed" more training data. As learning proceeds, the training set evolves and the labels that the network assigns to unlabelled training data converge to their correct values. We demonstrate our approach by learning to invert a generative model of eyes and an active appearance model of faces.
Intensity Gradient Self-organizing Map for Cerebral Cortex Reconstruction
Authors: Cheng-Hung Chuang, Jiun-Wei Liou, Philip E. Cheng, Michelle Liou, Cheng-Yuan Liou
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper presents an application of a self-organizing map (SOM) model based on the image intensity gradient for the reconstruction of cerebral cortex from MR images. The cerebral cortex reconstruction is important for many brain science or medicine related researches. However, it is difficult to extract deep cortical folds. In our method, we apply the SOM model based on the image intensity gradient to deform the easily extracted white matter surface and extract the cortical surface. The intensity gradient vectors are calculated according to the intensities of image data. Thus the proper cortical surface can be extracted from the image information itself but not artificial features. The simulations on T1-weighted MR images show that the proposed method is robust to reconstruct the cerebral cortex.
Fixed Point and Aperiodic Tilings
Authors: Bruno Durand, Andrei Romashchenko, Alexander Shen
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

An aperiodic tile set was first constructed by R. Berger while proving the undecidability of the domino problem. It turned out that aperiodic tile sets appear in many topics ranging from logic (the Entscheidungsproblem) to physics (quasicrystals)We present a new construction of an aperiodic tile set that is based on Kleene's fixed-point construction instead of geometric arguments. This construction is similar to J. von Neumann self-reproducing automata; similar ideas were also used by P. Gács in the context of error-correcting computations.The flexibility of this construction allows us to construct a "robust" aperiodic tile set that does not have periodic (or close to periodic) tilings even if we allow some (sparse enough) tiling errors. This property was not known for any of the existing aperiodic tile sets.
Toward Unsupervised Classification of Calcified Arterial Lesions
Authors: Gerd Brunner, Uday Kurkure, Deepak R. Chittajallu, Raja P. Yalamanchili, Ioannis A. Kakadiaris
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

There is growing evidence that calcified arterial deposits play a crucial role in the pathogenesis of cardiovascular disease. This paper investigates the challenging problem of unsupervised calcified lesion classification. We propose an algorithm, US-CALC (UnSupervised Calcified Arterial Lesion Classification), that discriminates arterial lesions from non-arterial lesions. The proposed method first mines the characteristics of calcified lesions using a novel optimization criterion and then identifies a subset of lesion features which is optimal for classification. Second, a two stage clustering is deployed to discriminate between arterial and non-arterial lesions. A histogram intersection distance measure is incorporated to determine cluster proximity. The clustering hierarchies are carefully validated and the final clusters are determined by a new intra-cluster compactness measure. Experimental results indicate an average accuracy of approximately 80% on a database of electron beam CT heart scans.
Efficient Interference Calculation by Tight Bounding Volumes
Authors: Masatake Higashi, Yasuyuki Suzuki, Takeshi Nogawa, Yoichi Sano, Masakazu Kobayashi
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

We propose a method for efficient calculation of proximity queries for a moving object. The proposed method performs continuous collision detection between two given configurations according to the exact collision checking (ECC) approach which performs distance calculation between two objects. This method obtains efficient results as it employs the concept of clearance bounds and performs approximate distance calculations with a tight fit of bounding volumes. The high efficiency of the method, when applied to robot path planning, is demonstrated through some experiments.
Mobile Computing at the Beach
Authors: Justin Mazzola Paluska, Angela Dalton, Prasad Boddupalli, Amit Saha, Athanasios E. Papathanasiou, Santashil Palchaudhuri
Venue: IEEE Pervasive Computing (2004)

The Fifth IEEE Workshop on Mobile Computing Systems and Applications descended on the Beach Resort in Monterey, California, for a series of technical discussions of new research in pervasive and mobile computing.
Performance optimization of TCP/IP over 10 gigabit ethernet by precise instrumentation
Authors: Takeshi Yoshino, Yutaka Sugawara, Katsushi Inagami, Junji Tamatsukuri, Mary Inaba, Kei Hiraki
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

End-to-end communications on 10 Gigabit Ethernet (10GbE) WAN became popular. However, there are difficulties that need to be solved before utilizing Long Fat-pipe Networks (LFNs) by using TCP. We observed that the followings caused performance depression: short-term bursty data transfer, mismatch between TCP and hardware support, and excess CPU load. In this research, we have established systematic methodologies to optimize TCP on LFNs. In order to pinpoint causes of performance depression, we analyzed real networks precisely by using our hardware-based wire-rate analyzer with 100-ns time-resolution. We took the following actions on the basis of the observations: (1) utilizing hardware-based pacing to avoid unnecessary packet losses due to collisions at bottlenecks, (2) modifying TCP to adapt packet coalescing mechanism, (3) modifying programs to reduce memory copies. We have achieved a constant through-put of 9.08Gbps on a 500ms RTT network for 5h. Our approach has overcome the difficulties on single-end 10GbE LFNs.
Ontology Matching in Communication and Web Services Composition for Agent Community
Authors: Adam Łuszpaj, Edward Nawarecki, Anna Zygmunt, Jarosław Koźlak, Grzegorz Dobrowolski
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

Ontology matching plays a vital role in a number of areas, such as knowledge integration, services composition or system interoperability. In this paper we present an architectural overview of an ontological service, wrapped up as an Ontology Agent, supporting automated ontology matching and facilitating inter-agent communication.