ppxscal/embedding_network huggingface dataset:
Integrating Multiple Data Sources for Stock Prediction
Authors: Di Wu, Gabriel Pui Fung, Jeffrey Xu Yu, Zheng Liu
Venue: Proceedings of the 9th international conference on Web Information Systems Engineering (2008)

In many real world applications, decisions are usually made by collecting and judging information from multiple different data sources. Let us take the stock market as an example. We never make our decision based on just one single piece of advice, but always rely on a collection of information, such as the stock price movements, exchange volumes, market index, as well as the information from the news articles, expert comments and special announcements (e.g., the increase of stamp duty). Yet, modeling the stock market is difficult because: (1) The process related to market states (up and down) is a stochastic process, which is hard to capture by using the deterministic approach; and (2) The market state is invisible but will be influenced by the visible market information, such as stock prices and news articles. In this paper, we try to model the stock market process by using a Non-homogeneous Hidden Markov Model (NHMM) which takes multiple sources of information into account when making a future prediction. Our model contains three major elements: (1) External event, which denotes the events happening within the stock market (e.g., the drop of US interest rate); (2) Observed market state, which denotes the current market status (e.g. the rise in the stock price); and (3) Hidden market state, which conceptually exists but is invisible to the market participants. Specifically, we model the external events by using the information contained in the news articles, and model the observed market state by using the historical stock prices. Base on these two pieces of observable information and the previous hidden market state, we aim to identify the current hidden market state, so as to predict the immediate market movement. Extensive experiments were conducted to evaluate our work. The encouraging results indicate that our proposed approach is practically sound and effective.
Graph Transformation for the Semantic Web: Queries and Inference Rules
Authors: Hong Qing Yu, Yi Hong
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Pervasive computing becomes an important characteristic of today's IT systems. In particular, context awareness is a core technology to enhance pervasive computing functionalities [1]. In recent years, Semantic Web (SW) is widely used in the development of mainstream software systems; it becomes increasingly important and feasible for improving conventional web data sharing process by providing machine-readable information and metadata expressed in various semantic web technologies such as Web Ontology Language (OWL) and Resource Description Framework (RDF). SW technology itself has already indicated the solutions to context modeling and sharing. However, the context querying and inferencing methodologies are still missing which leads to 2 major challenges.
Correlation Filters for Pattern Recognition Using a Noisy Reference
Authors: Pablo M. Aguilar-González, Vitaly Kober
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Correlation filters for recognition of a target in overlapping background noise are proposed. The object to be recognized is given implicitly; that is, it is placed in a noisy reference image at unknown coordinates. For the filters design two performance criteria are used: signal-to-noise ratio and peak-to-output energy. Computer simulations results obtained with the proposed filters are discussed and compared with those of classical correlation filters in terms of discrimination capability.
Localized Priors for the Precise Segmentation of Individual Vertebras from CT Volume Data
Authors: Hong Shen, Andrew Litvin, Christopher Alvino
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present algorithms for the automatic and precise segmentation of individual vertebras in CT Volume data. When a local surface evolution method such as the level set is applied to such a complex structure, global shape priors will not be sufficient to avoid the leakage and local minima problems, particularly if precise object boundary is desired. We propose a prior knowledge base that contains localized priors--a group of high-level features whose detection will augment the surface model and be the key to success. Base on this a set of context blockers are applied to prevent the leakages. Carefully designed initial surface when registered with the data helps avoid the local minimum problem. The results of segmentation well approximate the human delineated object boundaries. We also present the validation result of the segmentation of 150 vertebras.
Towards the Verification of Attributed Graph Transformation Systems
Authors: Barbara König, Vitali Kozioura
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

We describe an approach for the verification of attributed graph transformation systems (AGTS). AGTSs are graph transformation systems where graphs are labelled over an algebra. We base our verification procedure on so-called approximated unfoldings combined with counterexample-guided abstraction refinement. Both techniques were originally developed for non-attributed systems. With respect to refinement we focus especially on detecting whether the spurious counterexample is caused by structural over-approximation or by an abstraction of the attributes which is too coarse. The technique is implemented in the verification tool Augur 2 and a leader election protocol has been successfully verified.
How Useful Are Tags? -- An Empirical Analysis of Collaborative Tagging for Web Page Recommendation
Authors: Daniel Zeng, Huiqian Li
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

As a representative Web 2.0 application, collaborative tagging has been widely adopted and inspires significant interest from academies. Roughly, two lines of research have been pursued: (a) studying the structure of tags, and (b) using tag to promote Web search. However, both of them remain preliminary. Research reported in this paper is aimed at addressing some of these research gaps. First, we apply complex network theory to analyze various structural properties of collaborative tagging activities to gain a detailed understanding of user tagging behavior and also try to capture the mechanism that can help explain such tagging behavior. Second, we conduct a preliminary computational study to utilize tagging information to help improve the quality of Web page recommendation. The results indicate that under the user-based recommendation framework, tags can be fruitfully exploited as they facilitate better user similarity calculation and help reduce sparsity related to past user-Web page interactions.
Toward a property based requirements theory: System requirements structured as a semilattice
Authors: Patrice Micouin
Venue: Systems Engineering (2008)

In this paper, we outline a property-based requirement (PBR) theory. After introducing the mathematical notion of semilattice, we express the ontological and epistemological assumptions on which our theory is built. We provide a definition of a &ldquo;well formed (wf-)requirement,&rdquo; based on the property concept, distinguished from that of an &ldquo;expectation.&rdquo; Then, we introduce two relationships between wf-requirements called respectively &ldquo;conjunction&rdquo; operation and &ldquo;stringency&rdquo; relationship. So, we state that a set of wf-requirements, assigned to a system, is structured as a semilattice and that the maximum element of this semilattice matches the system specification. The network including all the expectations and wf-requirements related to a system are linked together through two very unlike categories of relationships. &ldquo;De dicto&rdquo; relationships are linguistic dependencies while &ldquo;de re&rdquo; relationships among requirements are extralinguistic dependencies among material properties refereed by wf-requirements. We highlight two types of &ldquo;de re&rdquo; relationship among wf-requirements. The first one is the well known &ldquo;derivation&rdquo; relationship that links together a &ldquo;parent&rdquo; requirement with its &ldquo;child&rdquo; requirements during the system design process. We introduce a second one, called &ldquo;coupling&rdquo; relationship. Wf-requirements are coupled when the change of one of them collides with others. We claim that our PBR theory belongs to the same paradigm as the model-based systems engineering (MBSE) approaches whereas TBR belongs to the same field as empirical design approaches. Then, we relate our requirements formulation to features of the OMG SysMLTM language. We conclude on our prospects for research, which connect our requirement theory with reflections carried out on the bodies of knowledge and their specification, i.e. ontologies. &copy; 2008 Wiley Periodicals, Inc. Syst Eng
Computer Representation of Molecular Surfaces
Authors: Nelson Max
Venue: IEEE Computer Graphics and Applications (1983)

The recent proliferation of algorithms that produce vector or raster drawings of space-filling models has advanced our understanding of the 3-D structure of molecules.
Theory of Evolutionary Algorithm: A View from Thermodynamics
Authors: Yuanxiang Li, Weiwu Wang, Xianjun Shen, Weiqin Ying, Bojin Zheng
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

It is recognized that evolutionary algorithms are inspired from evolutionary biology. In this paper, we set up a thermodynamic model of evolutionary algorithm. This model is intuitive and has a solid foundation in thermodynamics. It is our first step towards a unified theory of evolutionary algorithms.
Influence of NH3 plasma treatment on chemical bonding and water adsorption of low-k SiCOH film
Authors: Hao-Wen Guo, Lian Zhu, Lei Zhang, Shi-Jin Ding, David Wei Zhang, Ran Liu
Venue: Microelectronic Engineering (2008)

Carbon-doped silicon oxide (SiCOH) dielectrics are one of the most suitable candidates for advanced low-dielectric-constant (low-k) interlayer material. To improve water adsorption resistance, the plasma-enhanced chemical vapor deposited SiCOH films have been post-treated by the NH"3 plasma for various times, and the resulting SiCOH films are thus examined by water adsorption experiments. The results indicate that the SiCOH films treated by the NH"3 plasma exhibit enhanced resistance against water adsorption. Further, Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy are used to characterize the chemical composition and bonding states of the pristine and NH"3 plasma treated SiCOH films. It is revealed that the plasma surface treatment leads to the formation of Si-N, C(sp^3)-N, C(sp^2)?N, (N-)"nSi-C (n=1-3) configurations, and loss of carbon atoms.
ANFIS modeling and feed forward control of shape memory alloy actuators
Authors: Ayyoub Rezaeeian, Behrouz Shasti, Alireza Doosthoseini, Aghil Yousefi-Koma
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

This paper focuses on the application of ANFIS in modeling the nonlinear behavior of the shape memory alloy actuators. Although, SMA actuators have attracted much attention for applications in many fields such as miniature robots they have not been widely utilized for motion control applications due to their nonlinear behaviors and control difficulties. Because of their ability in the nonlinear learning and adaptation, ANFIS architectures are suitable tools for obtaining model and controller in nonlinear systems. A set of experiments are conducted to generate the data. The test bed includes a SMA wire, a force sensor, a data acquisition terminal and a power amplifier. The reported results demonstrate the ability of ANFIS for modeling of SMA behavior and force control of the SMA wire.
Prediction of Chaotic Time Series Using LS-SVM with Simulated Annealing Algorithms
Authors: Meiying Ye
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Least squares support vector machine (LS-SVM) is a popular tool for the analysis of time series data sets. Choosing optimal hyperparameter values for LS-SVM is an important step in time series analysis. In this paper, we combine LS-SVM with simulated annealing (SA) algorithms for nonlinear time series analysis. The LS-SVM is used to predict chaotic time series, and its parameters are automatically tuned using the SA and generalization performance is estimated by minimizing the k-fold cross-validation error. A benchmark problem, Mackey-Glass time series, has been used as example for demonstration. It is showed this approach can escape from the blindness of man-made choice of the LS-SVM parameters. It enhances the prediction capability of chaotic time series. 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
Engineering Support System User Requirements
Authors: Llewellyn Bezanson, Louis Fields, Donald Knight, Michael Merritt, Bruce Millard, Donald Miller, Peter Rony
Venue: IEEE Micro (1985)

Further successful use of engineering workstations depends on greater standardization of workstation components, a greater effort to make systems extensible, and better on-line training and help facilities.
Design of information landscapes for cultural heritage content
Authors: Emanuele Ruffaldi, Chiara Evangelista, Veronica Neri, Marcello Carrozzino, Massimo Bergamasco
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The presentation of cultural heritage information is typically addressed with the use of web pages eventually integrated with specific visualization of 3d models that complete the textual information. The problem with this type of information is its extent, its complexity and the connection between the various concepts. This paper presents an Information Landscape system for the fruition of this type of information through a virtual environment, available both for desktop and immersive visualizations.
ORGs for Scalable, Robust, Privacy-Friendly Client Cloud Computing
Authors: Carl Hewitt
Venue: IEEE Internet Computing (2008)

Organizations of restricted generality (ORGs) provide foundations for the development of more scalable, robust, and privacy-friendly Internet applications by incorporating multicore cloud computing into the client (desktops, entertainment centers, table computers, notebooks, wall computers, handhelds, and so forth).
Reinforcement learning of recurrent neural network for temporal coding
Authors: Daichi Kimura, Yoshinori Hayakawa
Venue: Neurocomputing (2008)

We study a reinforcement learning for temporal coding with neural network consisting of stochastic spiking neurons. In neural networks, information can be coded by characteristics of the timing of each neuronal firing, including the order of firing or the relative phase differences of firing. We derive the learning rule for this network and show that the network consisting of Hodgkin-Huxley neurons with the dynamical synaptic kinetics can learn the appropriate timing of each neuronal firing. We also investigate the system size dependence of learning efficiency.
Smooth Linear Approximation of Non-overlap Constraints
Authors: Graeme Gange, Kim Marriott, Peter J. Stuckey
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

Constraint-based placement tools and their use in diagramming tools has been investigated for decades. One of the most important and natural placement constraints in diagrams is that their graphic elements do not overlap. However, non-overlap of objects, especially non-convex objects, is difficult to solve and, in particular, to solve sufficiently rapidly for direct manipulation. Here we present the first practical approach for solving non-overlap of possibly non-convex objects in conjunction with other placement constraints such as alignment and distribution. Our methods are based on approximating the non-overlap constraint by a smoothly changing linear approximation. We have found that this in combination with techniques for lazy addition of constraints, is rapid enough to support direct manipulation in reasonably sized diagrams.
A 3D Virtual Model of the Knee Driven by EMG Signals
Authors: Massimo Sartori, Gaetano Chemello, Enrico Pagello
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

A 3D virtual model of the human lower extremity has been developed for the purpose of examining how the neuromuscular system controls the muscles and generates the desired movement. Our virtual knee currently incorporates the major muscles spanning the knee joint and it is used to estimate the knee joint moment. Beside that we developed a graphical interface that allows the user to visualize the skeletal geometry and the movements imparted to it. The purpose of this paper is to describe the design objectives and the implementation of our EMG-driven virtual knee. We finally compared the virtual knee behavior with the torque performed by the test subject in order to obtain a qualitative validation of our model. Within the next future our aim is to develop a real-time EMG-driven exoskeleton for knee rehabilitation.
FPGA implementation of high performance elliptic curve cryptographic processor over GF(2163)
Authors: Chang Hoon Kim, Soonhak Kwon, Chun Pyo Hong
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

In this paper, we propose a high performance elliptic curve cryptographic processor over GF(2^1^6^3), one of the five binary fields recommended by National Institute of Standards and Technology (NIST) for Elliptic Curve Digital Signature Algorithm (ECDSA). The proposed architecture is based on the Lopez-Dahab elliptic curve point multiplication algorithm and uses Gaussian normal basis for GF(2^1^6^3) field arithmetic. To achieve high throughput rates, we design two new word-level arithmetic units over GF(2^1^6^3) and derive parallelized elliptic curve point doubling and point addition algorithms with uniform addressing based on the Lopez-Dahab method. We implement our design using Xilinx XC4VLX80 FPGA device which uses 24,263 slices and has a maximum frequency of 143MHz. Our design is roughly 4.8 times faster with two times increased hardware complexity compared with the previous hardware implementation proposed by Shu et al. Therefore, the proposed elliptic curve cryptographic processor is well suited to elliptic curve cryptosystems requiring high throughput rates such as network processors and web servers.
A descriptive reference framework for the personalisation of e-business applications
Authors: Panayiotis Koutsabasis, Modestos Stavrakis, Nikos Viorres, Jenny S. Darzentas, Thomas Spyrou, John Darzentas
Venue: Electronic Commerce Research (2008)

Personalisation is widely considered as a critical element of contemporary electronic businesses. However, despite the wealth of scientific work on personalisation, the definition of the term remains blurred with as consequence a lack of clarity as to what to design or evaluate when it comes to this area of an e-business. E-business stakeholders, including designers, managers and customers, need to understand the significance of personalisation features for many reasons including: guidance for design and evaluation, user appeal and implications for e-business functionality. The paper introduces a descriptive framework for personalisation aspects of e-businesses, in business-to-consumer (B2C) situations, that is related to typical e-business functionality. The proposed framework classifies previous research and extends it to provide e-commerce stakeholders with a vocabulary for analysing e-businesses, for comparing personalisation features, and for explaining e-business commerce evaluation results. The framework is applied to the evaluation of the personalisation features of contemporary clothing e-businesses, and conclusions are drawn for the readiness of this sector to adopt personalisation requirements.
Approximate dynamic programming for complex storage problems
Authors: Juliana M. Nascimento
Venue:  (2008)

Managing an asset in the presence of exogenous information that evolves over time can be a challenging task, especially if the information is a multi-dimensional stochastic process. Nevertheless, several of these problems have structural properties that can and should be exploited when developing a strategy to solve them. We focus on a class of such problems, namely complex storage problems, for which the optimal value function is a family of piecewise linear concave functions. We propose an approximate dynamic programming algorithm to handle these problems. The idea is to construct, iteratively, piecewise linear and concave value function approximations. The algorithm is a combination of Monte-Carlo simulation and stochastic approximation. It employs a pure exploitation scheme, where the states we visit depend on the decisions produced by solving the approximate problem. A projection operation guarantees that the approximations are concave over the iterations. We prove that our algorithm converges to an optimal policy, learning the optimal value functions for important regions of the state space, which is determined by the algorithm itself. It is a rare proof of convergence for a multistage setting where not all states have to be visited infinitely often by the algorithm. The proof relies on the problem class structural property. We proceed to study a practical application that fits into our framework: the mutual fund cash holding problem. We show that our solution closely matches the optimal one (in considerably less time), and outperform two static models. It is a simple policy that describes when money should be moved into and out of cash based on market performance. Next, we consider a subclass of storage problems called lagged acquisition, where assets are purchased over time to satisfy a random demand in the future. We provide an specialized proof and compare the rate of convergence of our algorithm to other approximation methods. Finally, we take on jet fuel hedging, proposing a novel trading strategy, which is optimal with respect to a utility that considers risk, return and prospective hedging effectiveness. We show for certain risk aversion levels that our approach dominates well established policies.
Revisiting Computer Image Analysis and Art
Authors: David Stork, Marco Duarte
Venue: IEEE MultiMedia (2007)

The authors comment on and refute several points made in Charles Falco's article regarding computer image analysis and art.
An integrating view on DNA computing and membrane computing
Authors: Rudolf Freund
Venue: Proceedings of the 9th WSEAS International Conference on Evolutionary Computing (2008)

In the area of molecular computing, the two fields of DNA computing and membrane computing are dealing with different operations and objects, yet both based on biological processes. In this paper, the similarities between these two approaches are considered from a theoretical point of view, and the possibilities to transfer theoretical results from one area to the other one are exhibited.