ppxscal/embedding_network huggingface dataset:
Straightening Drawings of Clustered Hierarchical Graphs
Authors: Sergey Bereg, Markus Völker, Alexander Wolff, Yuanyi Zhang
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

In this paper we deal with making drawings of clustered hierarchical graphs nicer. Given a planar graph G = (V,E) with an assignment of the vertices to horizontal layers, a plane drawing of G (with y-monotone edges) can be specified by stating for each layer the order of the vertices lying on and the edges intersecting that layer. Given these orders and a recursive partition of the vertices into clusters, we want to draw G such that (i) edges are straight-line segments, (ii) clusters lie in disjoint convex regions, (iii) no edge intersects a cluster boundary twice.First we investigate fast algorithms that produce drawings of the above type if the clustering fulfills certain conditions. We give two fast algorithms with different preconditions. Second we give a linear programming (LP) formulation that always yields a drawing that fulfills the above three requirements--if such a drawing exists. The size of our LP formulation is linear in the size of the graph.
On the Internet: Turbulence and 1001 Nights of Networked Performance
Authors: Maria Miranda, Norie Neumark
Venue: IEEE MultiMedia (2007)

In this issue, Art Beat looks at networked performance, featuring Turbulence, a net art portal. Turbulence's Helen Thorington and Jo-Ann Green discuss their blog, Networked_Performance, which provides an extensive archive of networked performances. We also profile performance artist Barbara Campbell's 1,001 Nights Cast, a durational networked performance project. Multimedia researchers interested in Web 2.0 might want to help develop a template or standard that lets performance artists share and search their work on the Web. Such work could also ensure that certain software, when it fades away, is translatable or included in new versions of software so that viewing art isn't contingent on outdated file formats.
An Analytical Adaptive Single-Neuron Compensation Control Law for Nonlinear Process
Authors: Li Jia, Peng-Ye Tao, Guang-Bo Chen, Min-Sen Chiu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

To circumvent the drawbacks in nonlinear controller designing of chemical processes, an analytical adaptive single-neuron compensation control scheme is proposed in this paper. A class of nonlinear processes with modest nonlinearities is approximated by a composite model consisting a linear ARX model and a fuzzy neural network-based linearization error model. Motivated by the conventional feedforward control design technique in process industries, the output of FNNM can be viewed as measurable disturbance and a compensator can be designed to eliminate the disturbance influence. Simulation results show that the adaptive single-neuron compensation control plays a major role in improving the control performance, and the proposed adaptive control possesses better performance.
Integration of Knowledge in Disjunctive Structure on Semantic Level
Authors: Trong Hieu Tran, Ngoc Thanh Nguyen
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Knowledge integration is a very important task in Knowledge Management field. The aim of this paper is to present an algorithm for knowledge integration based on disjunctive structures. A distance function between disjunctions is analyzed and some postulates for knowledge integration in this logic structure are introduced. Key properties of these postulates and aspects of algorithm are also investigated.
Modelization and Simulation of Nano Devices in nano κ Calculus
Authors: Alberto Credi, Marco Garavelli, Cosimo Laneve, Sylvain Pradalier, Serena Silvi, Gianluigi Zavattaro
Venue: Proceedings of the international conference on Computational Methods in Systems Biology (2007)

We develop a process calculus --- the nano ¿ Calculus --- for modeling, analyzing and predicting the properties of molecular devices. The nano ¿ Calculus is equipped with a simple stochastic model, that we use to model and simulate the behaviour of a molecular shuttle, a basic nano device currently used for building more complex systems.
Extended Clustering Coefficients of Small-World Networks
Authors: Wenjun Xiao, Yong Qin, Behrooz Parhami
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The clustering coefficient C of a network, which is a measure of direct connectivity between neighbors of the various nodes, ranges from 0 (for no connectivity) to 1 (for full connectivity). We define extended clustering coefficients C(h) of a small-world network based on nodes that are at distance h from a source node, thus generalizing distance-1 neighborhoods employed in computing the ordinary clustering coefficient C = C(1). Based on known results about the distance distribution P ¿ (h) in a network, that is, the probability that a randomly chosen pair of vertices have distance h, we derive and experimentally validate the law P ¿ (h)C(h) ≤ c log N / N, where c is a small constant that seldom exceeds 1. This result is significant because it shows that the product P ¿ (h)C(h) is upper-bounded by a value that is considerably smaller than the product of maximum values for P ¿ (h) and C(h).
The Simplest Method for Constructing APN Polynomials EA-Inequivalent to Power Functions
Authors: Lilya Budaghyan
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

In 2005 Budaghyan, Carlet and Pott constructed the first APN polynomials EA-inequivalent to power functions by applying CCZ-equivalence to the Gold APN functions. It is a natural question whether it is possible to construct APN polynomials EA-inequivalent to power functions by using only EA-equivalence and inverse transformation on a power APN mapping: this would be the simplest method to construct APN polynomials EA-inequivalent to power functions. In the present paper we prove that the answer to this question is positive. By this method we construct a class of APN polynomials EA-inequivalent to power functions. On the other hand it is shown that the APN polynomials constructed by Budaghyan, Carlet and Pott cannot be obtained by the introduced method.
Distributed Algorithms for Cooperative Control
Authors: Eric Klavins, Richard M. Murray
Venue: IEEE Pervasive Computing (2004)

A combination of tools from control theory and distributed computation is required to naturally express what a cooperative control system is. Several formalisms exist that motivated the development of the Computation and Control Language. This article introduces modeling and verification in CCL, and an example cooperative tracking task illustrates the formalism's main features.
Homeotaxis: Coordination with Persistent Time-Loops
Authors: Mikhail Prokopenko, Astrid Zeman, Rongxin Li
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

We present a novel approach to self-organisation of coordinated behaviour among multiple resource-sharing agents. We consider a hierarchical multi-agent system comprising multiple energy-dependent agents split into local neighbourhoods, each with a dedicated controller, and a centralised coordinator dealing only with the controllers. The coordinated behaviour is required in order to achieve a balance between the overall resource consumption by the multi-agent collective and the stress on the community. Minimising the resource consumption increases the stress, while reducing the stress may lead to unrestricted and highly unpredictable demand, harming the individual agents in the long-run. We identify underlying forces in the system's dynamics, suggest a number of quantitative measures used to contrast different strategies, and introduce a novel strategy based on persistent sensorimotor time-loops: homeotaxis. Homeotaxis subsumes the homeokinetic principle, extending it both in terms of scope (multi-agent self-organisation) and the state-space, and allows to select the best adaptive strategy for the considered system.
Asynchronous Exceptions as an Effect
Authors: William L. Harrison, Gerard Allwein, Andy Gill, Adam Procter
Venue: Proceedings of the 9th international conference on Mathematics of Program Construction (2008)

Asynchronous interrupts abound in computing systems, yet they remain a thorny concept for both programming and verification practice. The ubiquity of interrupts underscores the importance of developing programming models to aid the development and verification of interrupt-driven programs. The research reported here recognizes asynchronous interrupts as a computational effect and encapsulates them as a building block in modular monadic semantics. The resulting modular semantic model can serve as both a guide for functional programming with interrupts and as a formal basis for reasoning about interrupt-driven computation as well.
Generating a Production compiler from an Attribute Grammar
Authors: R. Farrow
Venue: IEEE Software (1984)

Must automatically generated compilers use inordinate amounts of memory? Here is evidence that AG-based systems hold the potential for efficient commercial operation.
Integrating Document Features for Entity Ranking
Authors: Jianhan Zhu, Dawei Song, Stefan Rüger
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

The Knowledge Media Institute of the Open University participated in the entity ranking and entity list completion tasks of the Entity Ranking Track in INEX 2007. In both the entity ranking and entity list completion tasks, we have considered document features in addition to a basic document content based relevance model. These document features include categorizations of documents, relevance of category names to the query, and hierarchical relations between categories. Furthermore, based on our TREC2006 and 2007 expert search approach, we applied a co-occurrence based entity association discovery model to the two tasks based on the assumption that relevant entities often co-occur with query terms or given relevant entities in documents. Our initial experimental results show that, by considering the predefined category, its children and grandchildren in the document content based relevance model, the performance of our entity ranking approach can be significantly improved. Consideration of the predefined category's parents, a category name based relevance model, and the co-occurrence model is not shown to be helpful in entity ranking and list completion, respectively.
Progressive Optimisation of Organised Colonies of Ants for Robot Navigation: An Inspiration from Nature
Authors: Tatiana Tambouratzis
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

This piece of research introduces POOCA (Progressive Optimisation of Organised Colonies of Ants) as an appealing variant of the established ACO (Ant Colony Optimisation) algorithm. The novelty of POOCA lies on the combination of the co-operation inherent in ACO with the spread of activation around the winner node during SOM (Self-Organising Map) training. The principles and operation of POOCA are demonstrated on examples from robot navigation in unknown environments cluttered with obstacles: efficient navigation and obstacle avoidance are demonstrated via the construction of short and --- at the same time - smooth paths (i.e. optimal, or near-optimal solutions); furthermore, path convergence is speedily accomplished with restricted numbers of ants in the colony. The aim of this presentation is to put forward the application of POOCA to combinatorial optimisation problems such as the traveling salesman, scheduling etc.
Efficient Computation of Recursive Principal Component Analysis for Structured Input
Authors: Alessandro Sperduti
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Recently, a successful extension of Principal Component Analysis for structured input, such as sequences, trees, and graphs, has been proposed. This allows the embedding of discrete structures into vectorial spaces, where all the classical pattern recognition and machine learning methods can be applied. The proposed approach is based on eigenanalysis of extended vectorial representations of the input structures and substructures. One problem with the approach is that eigenanalysis can be computationally quite demanding when considering large datasets of structured objects. In this paper we propose a general approach for reducing the computational burden. Experimental results show a significant speed-up of the computation.
The Complexity of Distinguishing Distributions (Invited Talk)
Authors: Thomas Baignères, Serge Vaudenay
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

Cryptography often meets the problem of distinguishing distributions. In this paper we review techniques from hypothesis testing to express the advantage of the best distinguisher limited to a given number of samples. We link it with the Chernoff information and provide a useful approximation based on the squared Euclidean distance. We use it to extend linear cryptanalysis to groups with order larger than 2.
Constraint Selection by Committee: An Ensemble Approach to Identifying Informative Constraints for Semi-supervised Clustering
Authors: Derek Greene, Pádraig Cunningham
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

A number of clustering algorithms have been proposed for use in tasks where a limited degree of supervision is available. This prior knowledge is frequently provided in the form of pairwise must-link and cannot-link constraints. While the incorporation of pairwise supervision has the potential to improve clustering accuracy, the composition and cardinality of the constraint sets can significantly impact upon the level of improvement. We demonstrate that it is often possible to correctly "guess" a large number of constraints without supervision from the co-associations between pairs of objects in an ensemble of clusterings. Along the same lines, we establish that constraints based on pairs with uncertain co-associations are particularly informative, if known. An evaluation on text data shows that this provides an effective criterion for identifying constraints, leading to a reduction in the level of supervision required to direct a clustering algorithm to an accurate solution.
Chaotic Motif Sampler for Motif Discovery Using Statistical Values of Spike Time-Series
Authors: Takafumi Matsuura, Tohru Ikeguchi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

One of the most important issues in bioinformatics is to discover a common and conserved pattern, which is called a motif, from biological sequences. We have already proposed a motif extraction method called Chaotic Motif Sampler (CMS) by using chaotic dynamics. Exploring a searching space with avoiding undesirable local minima, the CMS discovers the motifs very effectively. During a searching process, chaotic neurons generate very complicated spike time-series. In the present paper, we analyzed the complexity of the spike time-series observed from each chaotic neuron by using a statistical measure, such as a coefficient of variation and a local variation of interspike intervals, which are frequently used in the field of neuroscience. As a result, if a motif is embedded in a sequence, corresponding spike time-series show characteristic behavior. If we use these characteristics, multiple motifs can be identified.
Professional MBA programmes: New directions and challenges
Authors: Owen P. Hall Jr., Terry W. Young
Venue: International Journal of Technology Enhanced Learning (2008)

After several years in the doldrums, the number of working adults enrolling in Fully Employed MBA (FEMBA) programs worldwide is growing. This growth is being fuelled, in part, by globalisation, technology, and changing demographics. To meet these challenges, the traditional classroom model for delivering non-residential business education is giving way to a more holistic learning paradigm. The purpose of this paper is to analyse the characteristics of and to outline a process for designing world-class FEMBA programs. The analysis shows that curriculum age and selectivity are inversely related to ranking.
Jakstab: A Static Analysis Platform for Binaries
Authors: Johannes Kinder, Helmut Veith
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

For processing compiled code, model checkers require accurate model extraction from binaries. We present our fully configurable binary analysis platform Jakstab, which resolves indirect branches by multiple rounds of disassembly interleaved with dataflow analysis. We demonstrate that this iterative disassembling strategy achieves better results than the state-of-the-art tool IDA Pro.
Adding planned design to xp might help novices' productivity (or might not): two controlled experiments
Authors: René Noël, Gonzalo Valdes, Marcello Visconti, Hernán Astudillo
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Extreme Programming (XP) suggests using Evolutionary design, always implementing the simplest solution that satisfies the current iteration's requirements, instead of Planned (or Traditional) up-front design. Some developers have questioned the usefulness of Evolutionary approach's enabling practices (e.g., refactoring, test-driven development) arguing for the naturalness of, and need for, Planned design. Two controlled experiments were conducted to compare both approaches regarding product quality and programmer productivity. Results from both studies show that (1) there is no significant difference in the product quality, independently of experience, but (2) novices are more productive using the Planned approach.
The General-Purpose Interface Bus
Authors: Richard Gilbert
Venue: IEEE Micro (1982)

Inadequate documentation by instrument manufacturers is the source of most GPIB difficulties. A wise purchasing strategy may be the best solution to these problems.
Non-metal Slice Image Overlay Display System Used Inside the Open Type MRI
Authors: Ken Masamune, Ikuma Sato, Hongen Liao, Takeyoshi Dohi
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

MRI is now utilized not only for diagnosis but also for intraoperative surgical treatment. In the MRI environment, the surgeon imagines the position of target region by observing pre-acquired images and patient body during the operation, therefore the spatial position of the diseased part depends on the surgeon's knowledge and experience. Thus information from the MRI image is not fully utilized. In order to solve this problem, we developed the prototypes of slice image overlay system for open-type MRI, which comprises the MRI compatible display device, image communication, registration system and visualization software, which is adopted to clinical 0.2T Open MRI. Phantom experiments were performed and the TRE of the overlay device was less than 1.0mm at the center of the display.
Encoding-Based Tamper-Resistant Algorithm for Mobile Device Security
Authors: Seok Min Yoon, Seung Wook Lee, Hong Moon Wang, Jong Tae Kim
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Due to the advance in development technology for mobile systems, the attacks on the embedded systems become sophiscated. Especially, tampering with the infomation of mobile devices by software or hardware attack may lead to a serious problem like leaking personal information. In order to protect the tampering attack, encryption technique for embedded information is proposed. However, when the specification of encryption algorithm is known, the system is easily tampered. In this paper, we propose a novel tamper-resistant algorithm by encoding program instructions, which can detect the tampering attack. In this algorithm, when a malicious attacker try to tamper with a part of the system, the logical interdepency of program instrutions make it impossible unless he gets the access authorization of whole system.
The Three Platonic Models of Divergence-Strict CSP
Authors: A. W. Roscoe
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

In an earlier paper [13], the author proved that there were three models of CSP that play a special role amongst the ones based on finite observations: the traces $({\cal T})$, stable failures $({\cal F})$ and stable revivals $({\cal R})$ models are successively more refined, but all further models refine ${\cal R}$. In the present paper we prove the corresponding result for the divergence-strict models: ones that treat any process that can diverge immediately as the least in the refinement order. We define what it is to be a divergence-strict model, both for general and finitely nondeterministic CSP, and find that in order to get our result we need to add a new but natural operator into the language.
Feature generation and analysis applied to sequence classification for splice-site prediction
Authors: Lise Getoor
Venue:  (2007)

Sequence classification is an important problem in many real-world applications. Sequence data often contain no explicit "signals," or features, to enable the construction of classification algorithms. Extracting and interpreting the most useful features is challenging, and hand construction of good features is the basis of many classification algorithms. In this thesis, I address this problem by developing a feature-generation algorithm (FGA). FGA is a scalable method for automatic feature generation for sequences; it identifies sequence components and uses domain knowledge, systematically constructs features, explores the space of possible features, and identifies the most useful ones. In the domain of biological sequences, splice-sites are locations in DNA sequences that signal the boundaries between genetic information and intervening non-coding regions. Only when splice-sites are identified with nucleotide precision can the genetic information be translated to produce functional proteins. In this thesis, I address this fundamental process by developing a highly accurate splice-site prediction model that employs our sequence feature-generation framework. The FGA model shows statistically significant improvements over state-of-the-art splice-site prediction methods. So that biologists can understand and interpret the features FGA constructs, I developed SplicePort, a web-based tool for splice-site prediction and analysis. With SplicePort the user can explore the relevant features for splicing, and can obtain splice-site predictions for the sequences based on these features. For an experimental biologist trying to identify the critical sequence elements of splicing, SplicePort offers flexibility and a rich motif exploration functionality, which may help to significantly reduce the amount of experimentation needed. In this thesis, I present examples of the observed feature groups and describe efforts to detect biological signals that may be important for the splicing process. Naturally, FGA can be generalized to other biologically inspired classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, as well as other sequence classification problems, provided we have sufficient knowledge of the new domain.