ppxscal/embedding_network huggingface dataset:
Using artificial neural networks to forecast the futures prices of crude oil
Authors: A. K. Mazouz
Venue:  (2008)

Crude oil is the commodity de jour and its pricing is of paramount importance to the layperson as well as to any responsible government. However, one of the main challenges facing econometric pricing models is the forecasting accuracy. Historically, linear and non-linear time series models were used. Although, a great success was achieved in that regard, yet there were no definite and universal conclusions drawn. The crude oil forecasting field is still wide open for improvement, especially when applying different forecasting models and alternative techniques. Toward this end, the proposed research implemented Artificial Neural Network models (ANN). The models will forecast the daily crude oil futures prices from 1996 to 2006, listed in NYMEX. Due to the nonlinearity presented by the test results of the crude oil pricing, it is expected that the ANN models will improve forecasting accuracy. An evaluation of the outcomes of the forecasts among different models was done to authenticate that this is undeniably the situation.
An Annotated Bibliography on the Origins of Digital Computers
Authors: Brian Randell
Venue: IEEE Annals of the History of Computing (1979)

The bibliography contains nearly 750 annotated and indexed citations to papers, books, and other items relating to the origins of the modern electronic computer. The topics covered range from early digital calculating devices and mechanical automata to the first stored program computers. New entries were added up to June 1979.
Modeling the interaction between objects and cartoon water
Authors: Jinhui Yu Jing Liao
Venue: Computer Animation and Virtual Worlds (2008)

In this paper, we describe a method for modeling the interaction between objects and the cartoon water which does not involve physics simulations. Our method involves the definition of flow path lines in the presence of obstacles, modeling of different types of water forms, and combinations of them in space and time. There are several notable features with our method: easy setting with little user intervention, modeling of complex water forms that represent more energetic water behavior than has been encompassed by semi-automatic means so far, and the adaptive change of animated water forms to the variation of obstacle object in number, size, and shape in the water path. A number of formulae for managing shape and time variance in these animations are given. We tested our method with both still and moving objects that have different shape and size in the water and relevant examples are given in the paper. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Epilogue
Authors: John Barnes
Venue: Ada 2005 Rationale: The Language, The Standard Libraries (2008)

This last chapter summarizes a small number of general issues of importance to the user such as compatibility between Ada 2005 and Ada 95. It also briefly considers a few potential changes that were considered for Ada 2005 but rejected for various reasons. It further mentions a few minor corrections to Ada 2005 that have been found to be necessary since the standard was approved. 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
Automatic MRI Brain Segmentation with Combined Atlas-Based Classification and Level-Set Approach
Authors: Sami Bourouis, Kamel Hamrouni, Nacim Betrouni
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

The task of manual brain segmentation from magnetic resonance imaging (MRI) is generally time-consuming and difficult. In a previous paper [1], we described a method for segmenting MR which is based on EM algorithm and a deformable level-set model. However, this method was not fully automatic. In this paper, we present an automated approach guided by digital anatomical atlas, which is an additional source of prior information. Our fully automatic method segments white matter, grey matter and cerebrospinal-fluid. The paper describes the main stages of the method, and presents preliminary results which are very encouraging for clinical practice.
How to Publicly Verifiably Expand a Member without Changing Old Shares in a Secret Sharing Scheme
Authors: Jia Yu, Fanyu Kong, Rong Hao, Xuliang Li
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Publicly verifiable secret sharing is a kind of special verifiable secret sharing, in which the shares of a secret can be verified by everyone, not only shareholders. Because of the property of public verifiability, it plays an important role in key-escrow, electronic voting, and so on. In this paper, we discuss a problem of how to publicly verifiably expand a member without changing old shares in a secret sharing scheme and present such a scheme. In the presented scheme, a new member can join a secret sharing scheme based on discrete logarithms to share the secret with the help of old shareholders. Furthermore, everyone besides the new member can verify the validity of the new member's share and any old shareholder doesn't need to change her old share. That means it is very convenient for key management.
Bookshelf
Authors: Fernando Berzal, Diomidis Spinellis
Venue: IEEE Software (2004)

"On Notations and Their Use" by Fernando Berzal: a review of Design Methods For Reactive Systems by Roel J. Wieringa and Morgan Kaufmann."Clichés Can Be Both Tiring and Helpful" by Diomidis Spinellis: a review of More Secrets of Consulting: The Consultant's Tool Kit by Gerald M. Weinberg.
GlossExtractor: A Web Application to Automatically Create a Domain Glossary
Authors: Roberto Navigli, Paola Velardi
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

We describe a web application, GlossExtractor, that receives in input the output of a terminology extraction web application, TermExtractor, or a user-provided terminology, and then searches several repositories (on-line glossaries, web documents, user-specified web pages) for sentences that are candidate definitions for each of the input terms. Candidate definitions are then filtered using statistical indicators and machine-learned regular patterns. Finally, the user can inspect the acquired definitions and perform an individual or group validation. The validated glossary is then downloaded in one of several formats.
Real and Modeled Spike Trains: Where Do They Meet?
Authors: Vasile V. Moca, Danko Nikolić, Raul C. Mureşan
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Spike train models are important for the development and calibration of data analysis methods and for the quantification of certain properties of the data. We study here the properties of a spike train model that can produce both oscillatory and non-oscillatory spike trains, faithfully reproducing the firing statistics of the original spiking data being modeled. Furthermore, using data recorded from cat visual cortex, we show that despite the fact that firing statistics are reproduced, the dynamics of the modeled spike trains are significantly different from their biological counterparts. We conclude that spike train models are difficult to use when studying collective dynamics of neurons and that there is no universal 'recipe' for modeling cortical firing, as the latter can be both very complex and highly variable.
A Novel Inter-LMD Handoff Mechanism for Network-Based Localized Mobility Management
Authors: Joong-Hee Lee, Jong-Hyouk Lee, Tai-Myoung Chung
Venue: Proceedings of the 7th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2007)

Network-based Localized Mobility Management (NetLMM) is an outstanding candidate solution for the mobility management controlled by the network. In NetLMM, mobile nodes (MNs) can be provided mobility services without any installation of mobility-support stack. However, there is a restriction that the MN is able to have the mobility only within a single localized mobility domain (LMD). In this paper, we propose a novel Inter-LMD handoff mechanism in order to eliminate the shortcoming of the current NetLMM protocol. The proposed Inter-LMD handoff mechanism enables that the MN hands off across LMDs, even if the MN does not have a functionality of Mobile IPv6 (MIPv6). According to the performance evaluation, the proposed Inter-LMD handoff mechanism has approximately 5.8% more overhead than the current Inter-LMD handoff of MIPv6-capable devices, while the current NetLMM protocol does not support the handoff of MIPv6-incapable devices.
A methodology for evaluation of web-based scholarship
Authors: David P. Dailey
Venue: Proceedings of the 9th ACM SIGITE conference on Information technology education (2008)

There is growing recognition that the paradigms of modern scholarship are shifting with the advent of the World Wide Web and other Internet-based forums. In some specialty areas within the discipline of Information Technology, one frequently hears folkloric wisdom suggesting that the turn-around time for print publication is greater than the useful longevity of the content. This situation increasing pushes the consumer of state-of-the art research toward the web rather than to the library. At some universities the problem of evaluating the quality of peer-reviewed literature has been approached through "citation" data. How often is a given work cited, for example, in Science Citation Abstracts? For evaluating web-based research, we suggest a related criterion for evaluating the "eminence" of scholarship. As of February 2003 [1], Google moved into first place as the most popular search engine in the United States. Google's immediate upsurge in popularity is generally attributed to the observation that its searches tend to reveal desired results. This is probably due to the nature of Google's page evaluation methodology. The relevance of a page to a given query is based on the number of other pages using those query terms that provide hyperlinks to the page in question. Since Google's emergence, other search engines have begun to utilize allied methodologies - essentially bootstrapping on existing works as relevance indicators in ways that, in fact, provide at least one form of "citation data." This paper will examine some related methodologies for evaluating quality of web-based academic work, and will examine some of the potential strengths and pitfalls associated with such methods.
High-Level Programs and Program Conditions
Authors: Karl Azab, Annegret Habel
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

High-level conditions are well-suited for expressing structural properties. They can describe the precondition and the postcondition for a high-level program, but they cannot describe the relationship between the input and the output of a program derivation. Therefore, we investigate program conditions, a generalized type of conditions expressing properties on program derivations. Program conditions look like nested rules with application conditions. We present a normal form result, a suitable graphical notation, and conditions under which a satisfying program can be constructed from a program condition. We define a sequential composition on program conditions and show that, for a suitable type of program conditions with a complete dependence relation we have that: Whenever the original programs satisfy the original program conditions, then the composed program satisfies the composed program condition.
Letters: Spike-based cross-entropy method for reconstruction
Authors: András Lrincz, Zsolt Palotai, Gábor Szirtes
Venue: Neurocomputing (2008)

Most neural optimization algorithms use either gradient tuning methods or complicated recurrent dynamics that may lead to suboptimal solutions or require huge number of iterations. Here we propose a framework based on the cross-entropy method (CEM). CEM is an efficient global optimization technique, but it requires batch access to many samples. We transcribed CEM to an online form and embedded it into a reconstruction network that finds optimal representations in a robust way as demonstrated by computer simulations. We argue that this framework allows for neural implementation and suggests a novel computational role for spikes in real neuronal systems.
Distribution Feeder Phase Balancing Using Newton-Raphson Algorithm-Based Controlled Active Filter
Authors: M. W. Siti, D. V. Nicolae, J. A. Jordaan, A. A. Jimoh
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

The distribution system problems, such as planning, loss minimization, and energy restoration, usually involve the phase balancing or network reconfiguration procedures. The determination of an optimal phase balance is, in general, a combinatorial optimization problem. This paper proposes a novel reconfiguration of the phase balancing using the active power filter control and the combinatorial optimization-based Newton-Raphson algorithm to solve the unbalance problem. By utilizing the load switches as state variable, a constant Jacobian matrix can be obtained. The model developed in this paper uses combinatorial optimization techniques to translate the change values (kVA) into a number of load points and then selects the specific load points. It also performs the inter-changing of the load points between the releasing and the receiving phases in an optimal fashion. Application results balancing a distribution feeder network in South Africa for domestic loads are presented in this paper.
A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow
Authors: Levi Valgaerts, Andrés Bruhn, Joachim Weickert
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

Traditional estimation methods for the fundamental matrix rely on a sparse set of point correspondences that have been established by matching salient image features between two images. Recovering the fundamental matrix from dense correspondences has not been extensively researched until now. In this paper we propose a new variational model that recovers the fundamental matrix from a pair of uncalibrated stereo images, and simultaneously estimates an optical flow field that is consistent with the corresponding epipolar geometry. The model extends the highly accurate optical flow technique of Brox et al. (2004) by taking the epipolar constraint into account. In experiments we demonstrate that our approach is able to produce excellent estimates for the fundamental matrix and that the optical flow computation is on par with the best techniques to date.
Challenges of Government Enterprise Architecture Work --- Stakeholders' Views
Authors: Hannakaisa Isomäki, Katja Liimatainen
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

At present, a vast transformation within government systems is executed towards electronic government. In some countries, this change is initiated as enterprise architecture work. This paper introduces results from an empirical study on different stakeholders' views on enterprise architecture development within Finnish state government. The data is gathered from 21 interviews accomplished during spring 2007 among participants of the Interoperability Programme of Finnish state administration. The interviewees represent different sectors and levels of Finnish government and IT companies. On the basis of qualitative data analysis we discuss challenges of enterprise architecture work in the context of state government. The key conclusion is that the governance level of enterprise architecture needs to be adequately adjusted and enforced as a tool for the development of business operations.
Identification of Different Sets of Biomarkers for Diagnostic Classification of Cancers
Authors: Yu-Shuen Tsai, I-Fang Chung, Chin-Teng Lin, Nikhil Ranjan Pal
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Accurate diagnosis of neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma, is often difficult because these cancers appear similar in routine histology. Finding a few useful biomarkers (not all related genes) that can discriminate between the subgroups will help designing better diagnostic systems. In an earlier study we reported a set of seven genes having excellent discrimination power. In this investigation we extend that study and find other distinct sets of genes with strong class specific signatures. This is achieved analyzing the correlation between genes. This led us to find another set of seven genes with better discriminating power. Our original gene selection method used a neural network whose output may significantly depend on initialization of the network, network size as well as the training data set. To address these issues we propose a scheme based on re-sampling. This method can also reduce the effect wide variation in number of data points in the training set from different classes. This method led us to find a set of five genes with good discriminating power. The genes identified by the proposed methods have roles in cancer biology.
Evaluation Ranges of Functions using Balanced Random Interval Arithmetic
Authors: Julius Žilinskas_thauth, Ian David Lockhart Bogle
Venue: Informatica (2003)

The results of experimental testing of balanced random interval arithmetic with typical mathematical test functions and practical problem are presented and discussed. The possibility of evaluation ranges of functions using balanced random interval arithmetic is investigated. The influence of the predefined probabilities of standard and inner interval operations to the ranges of functions is experimentally investigated. The author wishes to acknowledge the financial support through the Royal Society/NATO Postdoctoral Fellowship for the research &ldquo;Stochastic Interval Methods for Process Optimisation&rdquo;.
System for automatic audio video service creation for mobile TV and mobile web applications
Authors: G. Alberico, P. Casagranda, A. Messina, F. Russo
Venue: Proceedings of the 2008 Ambi-Sys workshop on Ambient media delivery and interactive television (2008)

This paper describes an innovative prototype system created to build up multimedia services addressed to mobile users, starting from automatically retrieved and processed archive contents or from User Generated Contents. The system targets both broadcasting Mobile TV on DVB-H and interactive mobile web over WiFi or 3G networks, both usable from handheld devices. Two pilot services based on the prototype system, available for experimental purposes over the area of Torino, are also described. The first pilot service is based on the automatic creation of a thematic news channel fed with contents from the Regional News, the second one allows to seamlessly distribute User Generated Contents.
Prediction of Compression Ratio of Extruded Cottonseed and Castor Bean under Mechanical Pressing Using Improved Neural Network
Authors: Xiao Zheng, Jingzhou Wang, Guoxiang Lin, Nong Wan, Yaxin Zhang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

A prediction model of compression ratio for extruded oilseeds was developed based on improved BP neural networks. As an applied example, the predicted curves were successfully used to predict critical pressing pressures. Results indicated that the predicted values of compression ratios conformed to the measured values well for extruded cottonseed and castor been. There was a limiting compression for extruded oilseeds under given conditions. The compression ratios for extruded cottonseed had more rapid increase from 0 to 40 MPa of applied pressure, less increase from 40 to 80 MPa and insignificant increase over 80 MPa, and for extruded castor bean had more rapid increase from 0 to 60 MPa of applied pressure, less increase from 60 to 100 MPa and insignificant increase over 100 MPa. 80 and 100 MPa of applied pressure were identified as the critical pressing pressure for extruded cottonseed and castor bean respectively.
Situation-Aware Based Self-adaptive Architecture for Mission Critical Systems
Authors: Sangsoo Kim, Jiyong Park, Heeseo Chae, Hoh Peter In
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

Conventional mission-critical systems cannot prevent mission failure in dynamic battlefield environments in which the execution situations or missions change abruptly. To solve this problem, self-adaptive systems have been proposed in the literature. However, the previous studies do not offer specifics on how to identify changes in a system situation or to transform situation information into the actions the systems must take in dynamic environments. This paper proposes a situation-awareness based self-adaptive system architecture (SASA) to support more efficient adaptation and, hence, achieve more accurate and successful missions, even in dynamic execution environments. A case study for air defense systems (ADS) using tests in a HLA/TRI-based real-time distributed simulation environment was implemented.
On the Modeling Timing Behavior of the System with UML(VR)
Authors: Leszek Kotulski, Dariusz Dymek
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

UML notation is assumed to be independent from any software modeling methodology. The existing methodologies support the creation of the final system model, but they do not care about the formal documentation of the reasoning process; the associations between the elements belonging to different types of UML diagrams are remembered either as informal documentation out-side the UML model or are forgotten. Described in the paper Vertical Relations try to fill this gap, and allow to look at the use of timing diagrams from the new, more complex, perspective. Usefulness of Virtual Relations in evaluation of the timing properties of the Data Warehouse Reporting systems is presented.
A Constraint Programming Approach to the Hospitals / Residents Problem
Authors: David F. Manlove, Gregg O'Malley, Patrick Prosser, Chris Unsworth
Venue: Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2007)

An instance I of the Hospitals / Residents problem (HR) involves a set of residents (graduating medical students) and a set of hospitals, where each hospital has a given capacity. The residents have preferences for the hospitals, as do hospitals for residents. A solution of I is a stable matching, which is an assignment of residents to hospitals that respects the capacity conditions and preference lists in a precise way. In this paper we present constraint encodings for HR that give rise to important structural properties. We also present a computational study using both randomly-generated and real-world instances. We provide additional motivation for our models by indicating how side constraints can be added easily in order to solve hard variants of HR.