ppxscal/embedding_network huggingface dataset:
Managing Dynamic Evolution of Architectural Types
Authors: Cristóbal Costa-Soria, Jennifer Pérez, José Angel Carsí
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Software systems evolvability is more and more required in current software developments, in order to provide systems with enough flexibility to adapt to future requirements. The evolvability in the field of Software Architecture can be classified into two kinds: dynamic reconfiguration or dynamic architectural type evolution. The former enables an architecture to change its configuration at run-time, by creating or destroying architectural element instances and their links dynamically. The latter enables an architecture to change entirely its specification at run-time, by introducing new architectural element types and connections or by modifying the type and the running instances of its architectural elements. This paper presents an approach to address how to dynamically evolve the architectural types of a system from a platform-independent view. This approach identifies the different concerns involved in the adaptation process by encapsulating them into aspects, and makes use of reflection mechanisms to perform the type updating process.
SRPT optimally utilizes faster machines to minimize flow time
Authors: Eric Torng, Jason McCullough
Venue: ACM Transactions on Algorithms (TALG) (2008)

We analyze the shortest remaining processing time (SRPT) algorithm with respect to the problem of scheduling n jobs with release times on m identical machines to minimize total flow time. It is known that SRPT is optimal if m &equals; 1 but that SRPT has a worst-case approximation ratio of &Theta;(min(log n/m, log &Delta;)) for this problem, where &Delta; is the ratio of the length of the longest job divided by the length of the shortest job. It has previously been shown that SRPT is able to use faster machines to produce a schedule as good as an optimal algorithm using slower machines. We now show that SRPT optimally uses these faster machines with respect to the worst-case approximation ratio. That is, if SRPT is given machines that are s &ge; 2 &minus; 1/m times as fast as those used by an optimal algorithm, SRPT's flow time is at least s times smaller than the flow time incurred by the optimal algorithm. Clearly, no algorithm can offer a better worst-case guarantee, and we show that existing algorithms with similar performance guarantees to SRPT without resource augmentation do not optimally use extra resources.
Six-Element Linguistic Truth-Valued Intuitionistic Reasoning in Decision Making
Authors: Li Zou, Wenjiang Li, Yang Xu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

A kind of intuitionistic linguistic truth-valued reasoning approach for decision making with both comparable and incomparable truth values is proposed in this paper. By using the lattice implication algebra, an six-element linguistic truth-valued intuitionistic propositional logic system is established which can express both truth degree and falsity degree. The implication operation of linguistic truth-valued intuitionistic propositional logic can be deduced from four times implication of their truth values. Therefore, we can use more information in the process of reasoning and eventually improve the precision of reasoning. As reasoning and operation are directly acted by linguistic truth values in the decision process, the issue on how to obtain the weight for rational decision making results is discussed. An illustration example shows the proposed approach seems more effective for decision making under a linguistic information environment with both truth degree and falsity degree.
The 701 Project as Seen by Its Chief Architect
Authors: Nathaniel Rochester
Venue: IEEE Annals of the History of Computing (1983)

Editor's Note: The architecture of the 701 has been described in previously published papers and is mentioned by several authors in this issue. The references in the following paper by Nathaniel Rochester (especially Bashe et al., 1981, and Astrahan and Rochester, 1952) are recommended for readers who want further details. Rochester mentions assemblers and refers to William F. McClelland, so we asked McClelland to provide the accompanying remarks on assemblers. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Mood and Recommendations: On Non-cognitive Mood Inducers for High Quality Recommendation
Authors: Tiffany Y. Tang, Pinata Winoto
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

Watching a comedy can help a user escape from the negative mood, which in turn affect the user's feedback over the movie. In other words, a non-cognitive mood inducer (the movie) can affect a user's post-consumption evaluation over the inducer (the rating the user give) which is directly associated with users' assessment over consumed goods. If these goods are generated from a recommender system, they will then directly affect the performance of the system. As such, our study attempts to enrich our understanding of the inducers and their effects in the recommendation performance. In addition, this paper provides a preliminary exploration of a mood-based filter to enhance the interaction between human and the system.
Static Worst-Case Execution Time Analysis Tool for Embedded Operating Systems
Authors: H. H. Park, Jiman Hong, S. M. Yang
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

Real-time support of embedded Operating Systems is essential for contemporary embedded systems. In order to achieve supporting real-time property, it is crucial that schedulability analysis for real-time task is finished before implementing the embedded systems. Acquiring Worst-Case Execution Time (WCET) of task is a core part of this schedulability analysis. In this paper, we design and implement WATERk, WCET analysis tool which deliberates on scheduling primitives of system using embedded Linux. WATERk can estimate WCET of both normal application tasks and corresponding primitives which influence the schedulability of embedded systems. Evaluation Results show that WATERk provides more reliable estimation results compared with traditional WCET tools.
The Layers of Logiweb
Authors: Klaus Grue
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

Logiweb is an open source, distributed system for publication of machine checked mathematics. It covers all aspects of electronic publishing: high typographical quality, archival, handling of references to previously published results, and publication of refereed volumes. The present paper is itself produced using Logiweb; and the paper is formally correct in the sense that it has been verified by Logiweb. The paper describes the implementation layers of the Logiweb system as seen by the user: the programming layer, the metalogic layer, the tactic layer, and the object proof layer.
Yi: an editor in haskell for haskell
Authors: Jean-Philippe Bernardy
Venue: ACM SIGPLAN Notices (2009)

Yi is a text editor written in Haskell and extensible in Haskell. We take advantage of Haskell's expressive power to define embedded DSLs that form the foundation of the editor. In turn, these DSLs provide a flexible mechanism to create extended versions of the editor. Yi also provides some support for editing Haskell code.
Design Tradeoffs for Improved Performance in MQCA-Based Systems
Authors: Michael Niemier, Aaron Dingler, X. Sharon Hu
Venue: Proceedings of the 2008 IEEE International Workshop on Design and Test of Nano Devices, Circuits and Systems (2008)

This paper looks at circuits and systems made from nanoscale magnets. We leverage physical level simulation to show how to extend initial experimental work – where wires and gates with nanometer feature sizes have been demonstrated at room temperature – to show how one might make design tradeoffs to improve both the performance and reliability of more complex systems.
A Perturbation Suppressing Segmentation Technique Based on Adaptive Diffusion
Authors: Wolfgang Middelmann, Alfons Ebert, Tobias Deißler, Ulrich Thoennessen
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Segmentation is a fundamental task in pattern recognition and basis for high level applications like scene reconstruction, change detection, or object classification. The performance of these tasks suffers from a distorted segmentation. In this contribution an adaptive diffusion-based segmentation method is proposed suppressing perturbations in the segmentation with focusing on small regions with high contrast to their surrounding. The algorithm determines in each step the diffusion tensor. It is re-weighted with respect to an assessment stage. A comparative study uses high-resolution remote sensing data.
Role assignment in wireless sensor networks: energy-efficient strategies and algorithms
Authors: Wendi B. Heinzelman
Venue:  (2008)

Wireless sensor networks are expected to consist of large numbers of nodes with redundant capabilities. This redundancy may exist in the abilities of the sensor nodes to sense the environment, route data from other sensors, and aggregate and code redundant data, among other tasks. In order to allow the network to operate at a high level of fidelity, or QoS, for an extended period of time, the assignment of roles and protocol-level settings to nodes should be carefully considered and chosen so that a node's energy is used most efficiently to meet the end goal of the sensor network application. Decisions concerning role assignment should be made based on such node properties as location in the environment (both absolute and relative to other nodes), sensing capabilities, energy supply, and processing capabilities. In this dissertation, I present a general middleware framework under which these optimizations can be made and I present several ways that role assignment can be optimized to extend network lifetime, including application-aware routing cost assignment, spatial resolution management, and transmission power control.
Behavioural Targeting in On-Line Advertising: An Empirical Study
Authors: Joanna Jaworska, Marcin Sydow
Venue: Proceedings of the 9th international conference on Web Information Systems Engineering (2008)

On-line behavioural targeting is a dynamically evolving area of web mining concerning the applications of data analysis of on-line users' behaviour and machine learning in optimising web on-line advertising and constitutes a problem of high importance and complexity.The paper reports on experimental work concerning testing various benchmark machine-learning algorithms and attribute preprocessing techniques in the context of behavioural targeting.Our final goal is to build a system which automatically learns and subsequently decides which on-line advertisements to present to a user visiting a web page, based on his previous recorded behaviour, in order to maximise the revenue of the ad-network and the web site hosting the ad, and, at the same time, to minimise the user's annoyance caused by potentially inappropriate advertisements.We present a general adaptive model which makes it possible to test various machine-learning algorithms in a plug-in mode and its implementation.We also report our experimental work concerning comparison of the performance of various machine-learning algorithms and data preprocessing techniques on a real dataset.The performance of our experiments is evaluated by some objective metrics such as the click-through rate (CTR) or related.Our experimental results clearly indicate that the presented adaptive system can significantly increase the CTR metric by 40% for some settings.All the experiments are performed on a real industrial dataset concerning on-line ads emitted in the Polish Web during a 1-month period in 2007.Up to the authors' best knowledge this is the first and largest evaluation made on this kind of real industrial data in Poland, at the time of writing.
Computing the Greedy Spanner in Near-Quadratic Time
Authors: Prosenjit Bose, Paz Carmi, Mohammad Farshi, Anil Maheshwari, Michiel Smid
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

It is well-known that the greedy algorithm produces high quality spanners and therefore is used in several applications. However, for points in d-dimensional Euclidean space, the greedy algorithm has cubic running time. In this paper we present an algorithm that computes the greedy spanner (spanner computed by the greedy algorithm) for a set of n points from a metric space with bounded doubling dimension in time using space. Since the lower bound for computing such spanners is ¿(n 2), the time complexity of our algorithm is optimal to within a logarithmic factor.
Index Calculus in Class Groups of Non-hyperelliptic Curves of Genus Three
Authors: Claus Diem, Emmanuel Thom&#x00e9;
Venue: Journal of Cryptology (2008)

We study an index calculus algorithm to solve the discrete logarithm problem (DLP) in degree&#x00a0;0 class groups of non-hyperelliptic curves of genus&#x00a0;3 over finite fields. We present a heuristic analysis of the algorithm which indicates that the DLP in degree&#x00a0;0 class groups of non-hyperelliptic curves of genus&#x00a0;3 can be solved in an expected time of $\tilde{O}(q)$. This heuristic result relies on one heuristic assumption which is studied experimentally. We also present experimental data which show that a variant of the algorithm is faster than the Rho method even for small group sizes, and we address practical limitations of the algorithm.
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Venue: Applications, Technologies, Architectures, and Protocols for Computer Communication (2008)

It is our great pleasure to welcome you to Seattle, Washington for SIGCOMM 2008, the flagship conference of the ACM SIG on Data Communications! With great enthusiasm and pride we have put together for you a rich and varied technical program that includes thirty six full-length papers that will be presented over three days; a keynote talk by the SIGCOMM Award winner, Don Towsley; the announcement of the SIGCOMM Test-of-Time Award; five one-day workshops that range from emerging communities (MobiArch, NetEcon, NSDR) to new forums on programmable routers and online social networks (PRESTO, WOSN); tutorials on the NetFPGA platform and spectral algorithms, and a unique session with 33 posters and 20 demonstrations that highlight promising early-stage research. It's a packed program, full of intellectually stimulating forums, each of which has the potential of leading to new important discoveries and breakthroughs. We are very excited about introducing several new "firsts" at SIGCOMM 2008. We have expanded the poster session to include demonstrations. We have worked with the SIG to launch a SIGCOMM Best Paper award. We have modified the traditional Student Dinner to a Dinner with Students event, opening it up to anyone who desires to join the students for an informal dinner. We are videotaping all presentations professionally and will make them available to the community, and we are providing a "go green" registration option to allow attendees to opt out of printed proceedings and get a CDROM that contains all the conference proceedings. SIGCOMM 2008 is located in the heart of Seattle, a vibrant, bustling urban city set in the midst of beautiful natural surroundings. We encourage you to take-in the sights and sounds of our beautiful region and to get you started we invite you to attend our Welcome Reception at the Olympic Sculpture Park, which provides a spectacular view of Puget Sound and the Olympic mountains. Our banquet will be held aboard a spacious modern cruise ship giving you a view of Seattle from the water and a closer view of the Sound.
Provenance Tracking with Bit Vectors
Authors: Siddharta S. Gadang, Brajendra Panda, Joseph E. Hoag
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

Data provenance (information about the origin of data items and the transformations that they have gone through) can be a useful security tool, particularly for forensic investigation. Provenance information can also be used to enforce information assurance concepts like integrity and authenticity. The current techniques for finding data source and lineage information are annotations and query inversion. Annotations lack scalability and require additional space for storing and querying provenance information, while query inversion incurs more time and processing overhead. In this paper, we offer fast and scalable models for computing source information, each of which are based on associating bit vectors with data sources.
An Application of Component-Wise Iterative Optimization to Feed-Forward Neural Networks
Authors: Yachen Lin
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Component-wise Iterative Optimization (CIO) is a method of dealing with a large data in the OLAP applications, which can be treated as the enhancement of the traditional batch version methods such as least squares. The salient feature of the method is to process transactions one by one, optimizes estimates iteratively for each parameter over the given objective function, and update models on the fly. A new learning algorithm can be proposed when applying CIO to feed-forward neural networks with a single hidden layer. It incorporates the internal structure of feed-forward neural networks with a single hidden layer by applying the algorithm CIO in closed-form expressions to update weights between the output layer and the hidden layer. Its optimally computational property is a natural consequence inherited from the property of the algorithm CIO and is also demonstrated in an illustrative example. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Language Acquisition: The Emergence of Words from Multimodal Input
Authors: Louis Bosch, Lou Boves
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

Young infants learn words by detecting patterns in the speech signal and by associating these patterns to stimuli provided by non-speech modalities (such as vision). In this paper, we discuss a computational model that is able to detect and build word-like representations on the basis of multimodal input data. Learning of words (and word-like entities) takes place within a communicative loop between a `carer' and the `learner'. Experiments carried out on three different European languages (Finnish, Swedish, and Dutch) show that a robust word representation can be learned in using approximately 50 acoustic tokens (examples) of that word. The model is inspired by the memory structure that is assumed functional for human speech processing.
Unity in Diversity: An Analysis of Inter-governmental Cooperation in the Field of geoICT
Authors: Walter T. Vries
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

Despite consecutive policies towards Joined-up government in the Netherlands, cooperation in the public sector with ICT is still considered problematic. The effects are often considered insufficiently visible or even considered absent. The domain of geoICT has various examples of cooperative activities, often intertwined with E-government programmes. The gap between policies and practice is investigated in this domain of geoICT. An exploratory, hermeneutic approach, supported by a quantitative survey is employed to research this gap. This approach has provided an insight in the dynamics and in which factors play a role. Not the technology in the cooperation or the structures in which the organizations work are important in how the cooperation with geoICT is shaping and evolving, but the degree to which the actors can maintain their own role. Finally, there is a disconnect between societal cooperation and cooperation with technology.
Automatically Making Origami Diagrams
Authors: Jien Kato, Hiroshi Shimanuki, Toyohide Watanabe
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

A traditional way to explain the folding process of origami works is usually using a sequence of diagrams (called origami illustrations). Since making origami illustrations is a heavy burden for origami designers, new original works are difficult to be published in time. To solve this problem, we propose a unique framework for automatically making origami illustrations based on 2-D crease patterns, and moreover give the key techniques to fully support proposed framework.
The digital signal processing of EMI measurements
Authors: Eleonora Darie, Emanuel Darie
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This work analyzes the advantages of broad-band time-domain the electrical measurement applied to electromagnetic interference (EMI) problems. The digital signal processing of EMI measurements allows to emulate in real-time the various modes of conventional analogous equipment. Since time-domain techniques allow processing the amplitude and phasing information of the whole signal spectrum in parallel, the measurement time may be reduced by at least one order of magnitude. On details the signal processing algorithms and the measurement results obtained with the time-domain electromagnetic interference system.
Neural Networks for Predicting the Behavior of Preconditioned Iterative Solvers
Authors: America Holloway, Tzu-Yi Chen
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

We evaluate the effectiveness of neural networks as a tool for predicting whether a particular combination of preconditioner and iterative method will correctly solve a given sparse linear system Ax = b. We consider several scenarios corresponding to different assumptions about the relationship between the systems used to train the neural network and those for which the neural network is expected to predict behavior. Greater similarity between those two sets leads to better accuracy, but even when the two sets are very different prediction accuracy can be improved by using additional computation.