ppxscal/embedding_network huggingface dataset:
On the characterization and analysis of system of systems architectures
Authors: Alexander H. Levis
Venue:  (2008)

A goal of an agile organization is the ability to adapt its structure to constantly changing operating environments so it can provide the multiple capabilities that enable mission accomplishment. A challenge for the system of systems (SOS) engineer is that while the SOS is being developed, the operating environment it was designed for changes. This situation causes significant uncertainty as to whether the SOS will meet the needs of the organization when finally deployed. To mitigate this uncertainty, SOS architectures should by assessed for their ability to deploy in more than one configuration. Past architecture assessments and performance characteristics are primarily system focused and do not address the dynamics of the interacting constituent systems of the SOS. This dissertation provides two measures, Adaptability and Agility, for assessing and comparing SOS architectures for their ability to adapt to the current operating environment and their ability to provide multiple capabilities concurrently. A SOS is defined as being composed of individual Elements that can be organized into Nodes. Each Element belongs to one and only one Node. Cohesion is a measure of the relatedness of the Elements within a Node. Coupling is a measure of the interdependence among the Nodes. Adaptability is defined as the ability of a SOS to respond to changes in the allocation of Elements to Nodes; it is computed using the concepts of Coupling and Cohesion. The Degree of Reuse measures the extent to which Elements support multiple capabilities. Agility measures the ability of the SOS to execute multiple processes concurrently and adapt to changing situations. Agility is a function of Adaptability and Degree of Reuse. The methodology provides the information required to assess the Adaptability and Agility of a proposed or actual SOS architecture. The process begins by identifying from the operational view of the architecture the capabilities that must be realized by the SOS alternatives. The SOS architecture describes how a particular subset of Elements organized into Nodes will realize the capabilities; it is the system view of the architecture. The SOS is transformed automatically into an executable model using Colored Petri Nets; invariant analysis and simulation are used to compute Coupling and Cohesion, while the Degree of Reuse is computed directly for each SOS. These three measures are then used to compute the Adaptability and Agility measures. Alternative architecture patterns are then compared in terms of their adaptability and agility. One advantage of the approach is that it can be applied early in the systems engineering process to help select preferred architecture alternatives. A case study is presented to illustrate the application of the assessment methodology and that different architecture types or patterns yield distinct values for the Adaptability and Agility measures that are consistent with the qualitative differences in the tested architectures.
Finite State Models for the Generation of Large Corpora of Natural Language Texts
Authors: Domenico Cantone, Salvatore Cristofaro, Simone Faro, Emanuele Giaquinta
Venue: Proceeding of the 2009 conference on Finite-State Methods and Natural Language Processing: Post-proceedings of the 7th International Workshop FSMNLP 2008 (2009)

Natural languages are probably one of the most common type of input for text processing algorithms. Therefore, it is often desirable to have a large training/testing set of input of this kind, especially when dealing with algorithms tuned for natural language texts. In many cases the problem due to the lack of big corpus of natural language texts can be solved by simply concatenating a set of collected texts, even with heterogeneous contexts and by different authors. In this note we present a preliminary study on a finite state model for text generation which maintains statistical and structural characteristics of natural language texts, i.e., Zipf's law and inverse-rank power law, thus providing a very good approximation for testing purposes.
Relationship-based change propagation: A case study
Authors: Marsha Chechik, Winnie Lai, Shiva Nejati, Jordi Cabot, Zinovy Diskin, Steve Easterbrook, Mehrdad Sabetzadeh, Rick Salay
Venue: Proceedings of the 2009 ICSE Workshop on Modeling in Software Engineering (2009)

Software development is an evolutionary process. Requirements of a system are often incomplete or inconsistent, and hence need to be extended or modified over time. Customers may demand new services or goals that often lead to changes in the design and implementation of the system. These changes are typically very expensive. Even if only local modifications are needed, manually applying them is time-consuming and and error-prone. Thus, it is essential to assist users in propagating changes across requirements, design, and implementation artifacts. In this paper, we take a model-based approach and provide an automated algorithm for propagating changes between requirements and design models. The key feature of our work is explicating relationships between models at the requirements and design levels. We provide conditions for checking validity of these relationships both syntactically and semantically. We show how our algorithm utilizes the relationships between models at different levels to localize the regions that should be modified. We use the IBM Trade 6 case study to demonstrate our approach.
Computationally efficient modeling and characterization of power semiconductor losses
Authors: Scott D. Sudhoff
Venue:  (2008)

Over the last forty years, advancements in semiconductor technology have led to their use in a variety of applications including motor drives, dc to dc converters, and uninterruptible power supplies. Considering their widespread use, the power loss modeling of power semiconductor switches and diodes is of great interest. Herein, a method to represent switching losses in a context of a system level time-domain simulation is proposed. This method set forth is a behavioral model that includes switching losses without attempting to represent the details of the switching event. Unlike physics-based models, this model accounts for switching losses without introducing fast dynamics into the simulation and can therefore take large time steps. Hence, the computational efficiency of conventional time-domain simulations for component/system studies is retained. In addition, a method for characterizing device losses as a function of temperature is developed. A new apparatus and procedure is set forth which will enable measurements to be taken rapidly, which, in turn, leads to superior device characterization.
A Database System of Buddhist Canons
Authors: Takehiko Tanaka, Yohei Nino, Rong Zhang, Martin Rolland, Masaru Nakagawa, Susumu Aoki, Keigo Utsunomiya, Toshinori Ochiai
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Buddhist scriptures written in Chinese several hundred ago are in the possession of temples in Japan. To make use of the contents for Buddhist study and archeology, we have ever made the comparative tables with acknowledged catalogues and taken shot images of the scripture using digital cameras. Those shot images are sometimes unreadable due to degradation, or one takes lots of trouble with combining the images. In this paper, we focus on the database for assisting the reading. Since the correspondence of the scriptures between Buddhist canons or the possessions in temples is available in the database, we can easily use well-maintained text files for our shot images. We also introduce the processors for eliminating redundant part of shot images and text data, together with the viewer which enables us to read the seamless image and its text simultaneously. It is possible for the database to accept enormous image and text files, interested people, and agents for the reading support.
Sequential spatial reasoning in images based on pre-attention mechanisms and fuzzy attribute graphs
Authors: Geoffroy Fouquier, Jamal Atif, Isabelle Bloch
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics, and graphs are well adapted to represent such information. Sequential methods for knowledgebased recognition of structures require to define in which order the structures have to be recognized, which can be expressed as the optimization of a path in the representation graph. We propose to integrate pre-attention mechanisms in the optimization criterion, in the form of a saliency map, by reasoning on the saliency of spatial area defined by spatial relations. Such mechanisms extract knowledge from an image without object recognition in advance and do not require any a priori knowledge on the image. Therefore, pre-attentional mechanisms provide useful knowledge for object segmentation and recognition. The derived algorithms are applied on brain image understanding.
Transforming data access through public visualization
Authors: Fernanda B. Viégas, Martin Wattenberg
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Data visualization has historically been accessible only to the elite in academia, business, and government. It was "serious" technology, created by experts for experts. In recent years, however, web-based visualizations--ranging from political art projects to news stories--have reached audiences of millions. Meanwhile, new initiatives in government, aimed at all citizens, point to an era of increased transparency. What will this new era of data transparency look like--and what are the implications for technologists who work with data? To help answer this question, we report on recent research into public data analysis and visualization. Many of our results come from Many Eyes, a "living laboratory" web site where people may upload their own data, create interactive visualizations, and carry on conversations. Political discussions, citizen activism, religious discussions, game playing, and educational exchanges all happen on the site. To further support these scenarios, and the users they represent, will require continued innovation in data presentation and interaction.
Efficient purely-dynamic information flow analysis
Authors: Thomas H. Austin, Cormac Flanagan
Venue: Proceedings of the ACM SIGPLAN Fourth Workshop on Programming Languages and Analysis for Security (2009)

We present a novel approach for efficiently tracking information flow in a dynamically-typed language such as JavaScript. Our approach is purely dynamic, and it detects problems with implicit paths via a dynamic check that avoids the need for an approximate static analyses while still guaranteeing non-interference. We incorporate this check into an efficient evaluation strategy based on sparse information labeling that leaves information flow labels implicit whenever possible, and introduces explicit labels only for values that migrate between security domains. We present experimental results showing that, on a range of small benchmark programs, sparse labeling provides a substantial (30%--50%) speed-up over universal labeling.
Architecture for address auto-configuration in MANET based on extended prime number address allocation (EPNA)
Authors: Harish Kumar, R. K. Singla
Venue: WSEAS Transactions on Computers (2009)

An efficient technique for IP address auto-configuration for nodes is an important component in the MANET setup. Previously proposed approaches either need a broadcast over complete network and / or need a duplicate address detection mechanism leading to an inefficient latency and overhead in assignment of addresses. In this paper, an Extended Prime Number Address Allocation (EPNA) technique has been proposed that is conflict free and distributed technique. EPNA does not require broadcast and address assignment can be completed with in maximum of four hop communications. In this technique a large number of nodes are empowered to act as proxies to assign the addresses and most of the time it is one-hop communication. Analytical results show that EPNA is capable of auto-configuring any node without much latency and overhead irrespective of address space. The proposed algorithm also gives even IP address distribution and low complexity for small as well large sized MANET.
Grouped graphical Granger modeling for gene expression regulatory networks discovery
Authors: Aurélie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset
Venue: Bioinformatics (2009)

We consider the problem of discovering gene regulatory networks from time-series microarray data. Recently, graphical Granger modeling has gained considerable attention as a promising direction for addressing this problem. These methods apply graphical modeling methods on time-series data and invoke the notion of ‘Granger causality’ to make assertions on causality through inference on time-lagged effects. Existing algorithms, however, have neglected an important aspect of the problem—the group structure among the lagged temporal variables naturally imposed by the time series they belong to. Specifically, existing methods in computational biology share this shortcoming, as well as additional computational limitations, prohibiting their effective applications to the large datasets including a large number of genes and many data points. In the present article, we propose a novel methodology which we term ‘grouped graphical Granger modeling method’, which overcomes the limitations mentioned above by applying a regression method suited for high-dimensional and large data, and by leveraging the group structure among the lagged temporal variables according to the time series they belong to. We demonstrate the effectiveness of the proposed methodology on both simulated and actual gene expression data, specifically the human cancer cell (HeLa S3) cycle data. The simulation results show that the proposed methodology generally exhibits higher accuracy in recovering the underlying causal structure. Those on the gene expression data demonstrate that it leads to improved accuracy with respect to prediction of known links, and also uncovers additional causal relationships uncaptured by earlier works. Contact: aclozano@us.ibm.com
Tailoring a model-driven Quality-of-Service DSL for various stakeholders
Authors: Ernst Oberortner, Uwe Zdun, Schahram Dustdar
Venue: Proceedings of the 2009 ICSE Workshop on Modeling in Software Engineering (2009)

Many service-oriented business systems have to comply to various contracts and agreements. Multiple technical and non-technical stakeholders with different background and knowledge are involved in modeling such business concerns. In many cases, these concerns are only encoded in the technical models and implementations of the systems, making it hard for non-technical stakeholders to get involved in the modeling process. In this paper we propose to tackle this problem by providing model-driven Domain-specific Languages (DSL) for specifying the contracts and agreements, as well as an approach to separate these DSLs into sub-languages at different abstraction levels, where each sub-language is tailored for the appropriate stakeholders. We exemplify our approach by describing a Quality-of-Service (QoS) DSL which can be used to describe Service Level Agreements (SLA). This work provides insights into how DSLs can be utilized to model and enrich service-oriented business systems with concerns defined in contracts and agreements.
An efficient optimisation scheme for scalable surveillance centric video communications
Authors: Naeem Ramzan, Toni Zgaljic, Ebroul Izquierdo
Venue: Image Communication (2009)

State-of-the-art coders have been optimised over years according to the needs of the broadcasting industry. There are however key applications of coding technology whose challenges and requirements substantially differ from broadcasting. One of these key applications is surveillance. In this paper an efficient approach for surveillance centric joint source and channel coding is proposed. Contrasting conventional coders, the proposed system has been developed according to the requirements of surveillance application scenarios. It aims at achieving bit-rate optimisation and adaptation of surveillance videos for storing and transmission purposes. In the proposed approach the encoder communicates with a video content analysis (VCA) module that detects events of interests in video captured by CCTV. Bit-rate optimisation and adaptation is achieved by exploiting the scalability properties of the employed codec. Temporal segments containing events relevant to surveillance application are encoded using high spatio-temporal resolution and quality while the portions irrelevant from the surveillance standpoint are encoded at low spatio-temporal resolution and/or quality. Furthermore, the approach jointly optimises the bit allocation between the wavelet-based scalable video coder and forward error correction codes. The forward error correction code is based on the product code constituting of LDPC codes and turbo codes. Turbo codes show good performance at high error rates region but LDPC outperforms turbo codes at low error rates. Therefore, the concatenation of LDPC and TC enhances the performance at both low and high signal-to-noise (SNR) ratios. The proposed approach minimises the distortion of reconstructed video, subject to constraint on the overall transmission bit-rate budget. Experimental results clearly demonstrate the efficiency and suitability of the proposed approach in surveillance applications.
Artificial neural network reduction through oracle learning
Authors: Joshua E. Menke, Tony R. Martinez
Venue: Intelligent Data Analysis (2009)

Often the best model to solve a real-world problem is relatively complex. This paper presents oracle learning, a method using a larger model as an oracle to train a smaller model on unlabeled data in order to obtain (1) a smaller acceptable model and (2) improved results over standard training methods on a similarly sized smaller model. In particular, this paper looks at oracle learning as applied to multi-layer perceptrons trained using standard backpropagation. Using multi-layer perceptrons for both the larger and smaller models, oracle learning obtains a 15.16% average decrease in error over direct training while retaining 99.64% of the initial oracle accuracy on automatic spoken digit recognition with networks on average only 7% of the original size. For optical character recognition, oracle learning results in neural networks 6% of the original size that yield a 11.40% average decrease in error over direct training while maintaining 98.95% of the initial oracle accuracy. Analysis of the results suggest oracle learning is especially appropriate when either the size of the final model is relatively small or when the amount of available labeled data is small.
Asymptotic behavior of solutions for a Lotka-Volterra mutualism reaction-diffusion system with time delays
Authors: Yuan-Ming Wang
Venue: Computers Mathematics with Applications (2009)

This paper is to investigate the asymptotic behavior of solutions for a time-delayed Lotka-Volterra N-species mutualism reaction-diffusion system with homogeneous Neumann boundary condition. It is shown, under a simple condition on the reaction rates, that the system has a unique bounded time-dependent solution and a unique constant positive steady-state solution, and for any nontrivial nonnegative initial function the corresponding time-dependent solution converges to the constant positive steady-state solution as time tends to infinity. This convergence result implies that the trivial steady-state solution and all forms of semitrivial steady-state solutions are unstable, and moreover, the system has no nonconstant positive steady-state solution. A condition ensuring the convergence of the time-dependent solution to one of nonnegative semitrivial steady-state solutions is also given.
Research of multi-population agent genetic algorithm for feature selection
Authors: Yongming Li, Sujuan Zhang, Xiaoping Zeng
Venue: Expert Systems with Applications: An International Journal (2009)

Search algorithm is an essential part of feature selection algorithm. In this paper, through constructing double chain-like agent structure and with improved genetic operators, the authors propose one novel agent genetic algorithm-multi-population agent genetic algorithm (MPAGAFS) for feature selection. The double chain-like agent structure is more like local environment in real world, the introduction of this structure is good to keep the diversity of population. Moreover, the structure can help to construct multi-population agent GA, thereby realizing parallel searching for optimal feature subset. In order to evaluate the performance of MPAGAFS, several groups of experiments are conducted. The experimental results show that the MPAGAFS cannot only be used for serial feature selection but also for parallel feature selection with satisfying precision and number of features.
Proceedings of the 6th international conference on Autonomic computing
Venue: International Conference on Autonomic Computing (2009)

On behalf of the steering and program committees, it is our pleasure to welcome you to the Sixth International Conference on Autonomic Computing and Communications, being held on the lovely campus of the Universitat Politècnica de Catalunya, Barcelona, Spain. By the standards of the field, ICAC is an established conference. Nonetheless over the last six years the landscape of autonomic systems research has changed, and we have changed the format of the conference to match. The most obvious change is the explicit recognition of autonomic communications in our title. The potential for autonomic techniques in networking was first recognized in Europe, and so it is fitting that ICAC has included it explicitly at what is only the conference's second visit to Europe (after Dublin in 2006). The European theme is continued by our inclusion of a special session showcasing some of the large-scale research and development projects in autonomic systems being conducted across the continent, which we hope will act as a way to build trans-Atlantic (and indeed trans-Pacific) collaborations as we move on to tackle larger problems with autonomic systems. We have, of course, retained -- and indeed strengthened -- ICAC's focus on presenting strong papers on exciting science. This year we accepted 15 full papers from an exceptionally strong field of 97 reviewed full paper submissions. An additional 16 papers were accepted as short presentations and posters to highlight new ideas, and four industrial demonstrations of working tools that are finding industrial acceptance. We are delighted to welcome three keynote speakers from academia and industry, who have kindly given up their time to share their visions for the future of the area. We are equally delighted to host six satellite workshops covering a range of specialized topics including network management, cloud and green computing, all of which are increasingly critical in the modern enterprise world.