ppxscal/embedding_network huggingface dataset:
SystemT: a system for declarative information extraction
Authors: Rajasekar Krishnamurthy, Yunyao Li, Sriram Raghavan, Frederick Reiss, Shivakumar Vaithyanathan, Huaiyu Zhu
Venue: ACM SIGMOD Record (2009)

As applications within and outside the enterprise encounter increasing volumes of unstructured data, there has been renewed interest in the area of information extraction (IE) -- the discipline concerned with extracting structured information from unstructured text. Classical IE techniques developed by the NLP community were based on cascading grammars and regular expressions. However, due to the inherent limitations of grammarbased extraction, these techniques are unable to: (i) scale to large data sets, and (ii) support the expressivity requirements of complex information tasks. At the IBM Almaden Research Center, we are developing SystemT, an IE system that addresses these limitations by adopting an algebraic approach. By leveraging well-understood database concepts such as declarative queries and costbased optimization, SystemT enables scalable execution of complex information extraction tasks. In this paper, we motivate the SystemT approach to information extraction. We describe our extraction algebra and demonstrate the effectiveness of our optimization techniques in providing orders of magnitude reduction in the running time of complex extraction tasks.
Fast communication: Joint time-delay and frequency estimation using parallel factor analysis
Authors: Yuntao Wu, H. C. So, Yunsong Tan
Venue: Signal Processing (2009)

In this paper, the problem of joint time-delay and frequency estimation of multiple sinusoidal signals received at two separated sensors is addressed. By formulating the estimation problem with the use of the parallel factor analysis framework, the corresponding state transition and observation matrices are updated in an iterative manner according to alternating least squares, from which the time-delay and frequencies are then estimated. Computer simulations are included to demonstrate the effectiveness of the proposed algorithm.
IRUS: Image Retrieval Using Shape
Authors: Meirav Adoram, Michael S. Lew
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

Finding shapes in image databases is a challenging topic in content based retrieval. In this paper the goal is to find database images which contain shapes similar to the query of the user. Unlike most solutions to this problem, the algorithm presented in this paper is meant to cope with changes in rotation, scale, translation, and lossy compression noise. A Java application was built which uses snakes and invariant moments. The GVF snake was used because it has two significant advantages over the traditional snake formulation. First, the GVF snake can fit into concavities, and second, the GVF snake can fit itself to objects using both expansion and contraction of the snake. The objects in the images were segmented with the active contours, and then invariant moments were calculated and compared with a minimum distance classifier. Retrieval quality of the system was measured with respect to original images, rotated images, scaled images, noisy images, and combinations of those distortions.
Vocal Gestures in Slovak: Emotions and Prosody
Authors: Štefan Beňuš, Milan Rusko
Venue: Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers (2009)

Hot-spot words are indicators of high emotional invovement of speakers in the conversation and contain cues to the emotional state of the speaker. Understanding and modeling of these cues may improve the effec-tiveness and naturalness of automated cross-modal dialogue systems. In this paper we investigate the relationship between prosody and emotions in a subgroup of hot-spot words: non-verbal vocal gestures with a problematic textual representation. We extracted these gestures from a recording of a puppet play and argue that this corpus is well suited for investigating emotional speech. We identify the expressive load of non-verbal vocal gestures in Slovak and report on multiple ambiguities in their emotional and discourse functions. The relationship between prosody and emotions in non-verbal hot-spot words is very complex and a ToBI-based framework of discrete representation of prosody is useful but not sufficient for modeling this relationship.
A Construction of Lossy Source Code Using LDPC Matrices
Authors: Shigeki Miyake, Jun Muramatsu
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

Research into applying LDPC code theory, which is used for channel coding, to source coding has received a lot of attention in several research fields such as distributed source coding. In this paper, a source coding problem with a fidelity criterion is considered. Matsunaga et al. and Martinian et al. constructed a lossy code under the conditions of a binary alphabet, a uniform distribution, and a Hamming measure of fidelity criterion. We extend their results and construct a lossy code under the extended conditions of a binary alphabet, a distribution that is not necessarily uniform, and a fidelity measure that is bounded and additive and show that the code can achieve the optimal rate, rate-distortion function. By applying a formula for the random walk on lattice to the analysis of LDPC matrices on Zq, where q is a prime number, we show that results similar to those for the binary alphabet condition hold for Zq, the multiple alphabet condition.
Microfluidics for Biological Applications, 1 edition
Authors: Wei-Cheng Tian, Erin Finehout
Venue:  (2008)

Microfluidics for Biological Applications provides researchers and scientists in the biotechnology, pharmaceutical, and life science industries with an introduction to the basics of microfluidics and also discusses how to link these technologies to various biological applications at the industrial and academic level. Readers will gain insight into a wide variety of biological applications for microfluidics. The material presented here is divided into four parts, Part I gives perspective on the history and development of microfluidic technologies, Part II presents overviews on how microfluidic systems have been used to study and manipulate specific classes of components, Part III focuses on specific biological applications of microfluidics: biodefense, diagnostics, high throughput screening, and tissue engineering and finally Part IV concludes with a discussion of emerging trends in the microfluidics field and the current challenges to the growth and continuing success of the field.
Mixture modeling with applications in schizophrenia research
Authors: Qiang Wu, Allan R. Sampson
Venue: Computational Statistics Data Analysis (2009)

Finite mixture modeling, together with the EM algorithm, have been widely used in clustering analysis. Under such methods, the unknown group membership is usually treated as missing data. When the ''complete data'' (log-)likelihood function does not have an explicit solution, the simplicity of the EM algorithm breaks down. Authors, including Rai and Matthews [Rai, S.N., Matthews, D.E., 1993. Improving the em algorithm. Biometrics 49, 587-591], Lange [Lange, K., 1995a. A gradient algorithm locally equivalent to the em algorithm. Journal of the Royal Statistical Society B 57(2) 425-437], and Titterington [Titterington, D.M., 1984. Recursive parameter estimation using incomplete data. Journal of the Royal Statistical Society B. 46, 257-267] developed modified algorithms therefore. As motivated by research in a large neurobiological project, we propose in this paper a new variant of such modifications and show that it is self-consistent. Moreover, simulations are conducted to demonstrate that the new variant converges faster than its predecessors.
Large-scale network intrusion detection based on distributed learning algorithm
Authors: Daxin Tian, Yanheng Liu, Yang Xiang
Venue: International Journal of Information Security (2009)

As network traffic bandwidth is increasing at an exponential rate, it&#x2019;s impossible to keep up with the speed of networks by just increasing the speed of processors. Besides, increasingly complex intrusion detection methods only add further to the pressure on network intrusion detection (NIDS) platforms, so the continuous increasing speed and throughput of network poses new challenges to NIDS. To make NIDS usable in Gigabit Ethernet, the ideal policy is using a load balancer to split the traffic data and forward those to different detection sensors, which can analyze the splitting data in parallel. In order to make each slice contains all the evidence necessary to detect a specific attack, the load balancer design must be complicated and it becomes a new bottleneck of NIDS. To simplify the load balancer this paper put forward a distributed neural network learning algorithm (DNNL). Using DNNL a large data set can be split randomly and each slice of data is presented to an independent neural network; these networks can be trained in distribution and each one in parallel. Completeness analysis shows that DNNL&#x2019;s learning algorithm is equivalent to training by one neural network which uses the technique of regularization. The experiments to check the completeness and efficiency of DNNL are performed on the KDD&#x2019;99 Data Set which is a standard intrusion detection benchmark. Compared with other approaches on the same benchmark, DNNL achieves a high detection rate and low false alarm rate.
Sensor self-localization with beacon position uncertainty
Authors: Mahesh Vemula, Mónica F. Bugallo, Petar M. Djurić
Venue: Signal Processing (2009)

We propose algorithms for distributed sensor self-localization using beacon nodes. These beacon nodes broadcast some information which describes their positions. The sensor nodes with unknown location information utilize these descriptions along with the characteristics of received signals to obtain estimates of their positions. Sensors with resolved positions, in the successive stages of the algorithm also broadcast their location information to other sensors so that they can resolve their own positions. Conditional upon the availability of probabilistic distributions of noise processes, we propose iterative and Monte Carlo sampling-based methods for obtaining sensor location descriptions. We also provide approximate hybrid Cramer-Rao bounds for distributed sensor self-localization and compare them with the proposed algorithms. We demonstrate the performance of the proposed algorithms through extensive computer simulations.
VideoTalk: A Collaborative Environment for Video Content Discussion
Authors: Shih-Ping Liou, Candemir Toklu, Kilian Heckrodt
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

This paper discusses VideoTalk, a new system for permitting different people from different places to share their views about video content. Several unique features of this application include the shared video player with multi-point VCR control, dynamic speed adjustment, and ability to show dynamic object markers. The video player window of the VideoTalk acts as a shared whiteboard with tele-pointer support. We also propose a new method for automatically computing the dynamic object markers given the shape of the object in the starting and ending frames.
Spectral-Lagrangian methods for collisional models of non-equilibrium statistical states
Authors: Irene M. Gamba, Sri Harsha Tharkabhushanam
Venue: Journal of Computational Physics (2009)

We propose a new spectral Lagrangian based deterministic solver for the non-linear Boltzmann transport equation (BTE) in d-dimensions for variable hard sphere (VHS) collision kernels with conservative or non-conservative binary interactions. The method is based on symmetries of the Fourier transform of the collision integral, where the complexity in its computation is reduced to a separate integral over the unit sphere S^d^-^1. The conservation of moments is enforced by Lagrangian constraints. The resulting scheme, implemented in free space, is very versatile and adjusts in a very simple manner to several cases that involve energy dissipation due to local micro-reversibility (inelastic interactions) or elastic models of slowing down process. Our simulations are benchmarked with available exact self-similar solutions, exact moment equations and analytical estimates for the homogeneous Boltzmann equation, both for elastic and inelastic VHS interactions. Benchmarking of the simulations involves the selection of a time self-similar rescaling of the numerical distribution function which is performed using the continuous spectrum of the equation for Maxwell molecules as studied first in Bobylev et al. [A.V. Bobylev, C. Cercignani, G. Toscani, Proof of an asymptotic property of self-similar solutions of the Boltzmann equation for granular materials, Journal of Statistical Physics 111 (2003) 403-417] and generalized to a wide range of related models in Bobylev et al. [A.V. Bobylev, C. Cercignani, I.M. Gamba, On the self-similar asymptotics for generalized non-linear kinetic Maxwell models, Communication in Mathematical Physics, in press. URL: ]. The method also produces accurate results in the case of inelastic diffusive Boltzmann equations for hard spheres (inelastic collisions under thermal bath), where overpopulated non-Gaussian exponential tails have been conjectured in computations by stochastic methods [T.V. Noije, M. Ernst, Velocity distributions in homogeneously cooling and heated granular fluids, Granular Matter 1(57) (1998); M.H. Ernst, R. Brito, Scaling solutions of inelastic Boltzmann equations with over-populated high energy tails, Journal of Statistical Physics 109 (2002) 407-432; S.J. Moon, M.D. Shattuck, J. Swift, Velocity distributions and correlations in homogeneously heated granular media, Physical Review E 64 (2001) 031303; I.M. Gamba, S. Rjasanow, W. Wagner, Direct simulation of the uniformly heated granular Boltzmann equation, Mathematical and Computer Modelling 42 (2005) 683-700] and rigorously proven in Gamba et al. [I.M. Gamba, V. Panferov, C. Villani, On the Boltzmann equation for diffusively excited granular media, Communications in Mathematical Physics 246 (2004) 503-541(39)] and [A.V. Bobylev, I.M. Gamba, V. Panferov, Moment inequalities and high-energy tails for Boltzmann equations with inelastic interactions, Journal of Statistical Physics 116 (2004) 1651-1682].
Optimizing Markov Model Parameters for Asynchronous Impulsive Noise over Broadband Power Line Communication Network
Authors: Tan-Hsu Tan, San-Yuan Huang, Ching-Su Chang, Yung-Fa Huang
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

A statistical model based on a partitioned Markov-chains model has previously been developed to represent time domain behavior of the asynchronous impulsive noise over a broadband power line communication (PLC) network. However, the estimation of its model parameters using the Simplex method can easily trap the final solution at a local optimum. This study proposes an estimation scheme based on the genetic algorithm (GA) to overcome this difficulty. Experimental results show that the proposed scheme yields estimates that more closely match the experimental data statistics.
Securing Critical IT Infrastructure
Authors: James A. Scholz
Venue: Information Security Journal: A Global Perspective (2009)

By now most everyone has some form of a plan in place for the security of their infrastructure. Unfortunately, the plan may not be complete, omit critical processes, or is based on someone's idea of what is acceptable. Regardless of what is incorporated into the infrastructure, the plan hopefully includes a systemic and methodical process of beginning, maintaining, and changing throughout the lifecycle. No matter how you are structured, you must have management buy in or you have nothing! Although most “security professionals” have either just begun, are in an intermediate stage, or have years of experience with the common bodies of knowledge (CBK), most forget the basics or are unable to incorporate them due to client misunderstanding of them or the process of developing a secure infrastructure. Information Technology Infrastructure Library (ITIL) took the industry standards of business and built the processes to follow to build a structured environment. When you evaluate the requirements of ITIL and then evaluate what the National Institute of Standards and Technology (NIST) have developed over the years, in conjunction with the Rainbow Series, you have it all. NIST takes you a little further because they build the infrastructure from a secure foundation, whereas ITIL relates two paragraphs to the discipline. A secure environment starts with your foundation of security; every process thereafter falls into place as you develop your baseline security requirements (BLSR). Asset Management, Configuration Management, Change Management, Incident Management, Capacity Management, and Financial Management become a by-product of your foundation.
Soft Decision Directed Channel Estimation with Interference Cancellation for a MIMO System Using Iterative Equalization and Decoding
Authors: Masatsugu Higashinaka, Hiroshi Kubo, Akihiro Okazaki, Yasutaka Ogawa, Takeo Ohgane, Toshihiko Nishimura
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This paper proposes a novel channel estimation method for iterative equalization in MIMO systems. The proposed method incorporates co-channel interference (CCI) cancellation in the channel estimator and the channel estimation is successively performed with respect to each stream. Accuracy of channel estimation holds the key to be successfully converged the iterative equalization and decoding process. Although the channel estimates can be re-estimated by means of LS (Least Square) channel estimation using tentative decisions obtained in the iterative process, its performance is severely limited in a MIMO system because of erroneous decisions and ill-conditioned channel estimation matrix. The proposed method can suppress the above effects by means of CCI cancellation and successive channel estimation. Computer simulation confirms that the proposed channel estimation method can accurately estimate the channel, and the receiver with iterative equalization and the proposed method achieves excellent decoding performance in a MIMO-SM system.
Robust stability analysis of generalized neural networks with multiple discrete delays and multiple distributed delays
Authors: Xiaoyang Liu, Nan Jiang
Venue: Neurocomputing (2009)

Using the Lyapunov-Krasovskii functional method and the linear matrix inequality (LMI) technique, this paper is concerned with the robust stability of generalized neural networks with multiple discrete delays and multiple distributed delays. The global stability of the equilibrium point is proved under mild conditions, where the activation function is neither differentiable nor strictly monotone. For the considered system, a novel robust stability criterion of the system is derived, which can be easily solved by efficient convex optimization algorithms. And two numerical examples are given to justify the obtained results.
A study of the observability of multidimensional hybrid linear systems
Authors: Valeriu Prepelita
Venue: WSEAS Transactions on Systems and Control (2008)

A class of multidimensional hybrid linear systems is presented, with the time vector composed by q continuous-time real components and by r discrete-time integer ones, q, r ≥ 1. The state equation is of multidimensional partial differential-difference type. A generalized variation-of-parameters formula is provided and it is used to obtain the state and the general response of the system. The fundamental concept of observability is studied for these systems. An observability Gramian is introduced, which is a generalization of the Gramians corresponding to the classical 1D continuous-time and 1D discrete-time systems. In the case of completely observable systems this Gramian is used to obtain a formula which provides the initial state of the system for any input-output pair. A list of observability criteria is given for time-invariant systems and the duality between the concepts of observability and reachability is emphasized.
First International Workshop on Software Engineering for Computational Science & Engineering
Authors: Jeffrey C. Carver
Venue: Computing in Science and Engineering (2009)

In recognition of the general lack of exposure scientists have to software engineering and vice versa, a workshop was held during the 2008 International Conference on Software Engineering in Leipzig, Germany. The workshop's goal was to bring together researchers and practitioners from the software engineering and computational science and engineering (CS E) communities to build a common understanding of the issues involved in the complex process of CS E software development and identify common themes to pursue in future research.
'Pretty Lights' and Maths! Increasing student engagement and enhancing learning through the use of electronic voting systems
Authors: Samuel O. King, Carol L. Robinson
Venue: Computers Education (2009)

University classes in Mathematics are traditionally perceived to be uninspiring and devoid of active student-lecturer communication. Large undergraduate classes further compound the difficulty of engaging students and enabling viable student-lecturer feedback. At the Mathematics Education Centre, Loughborough University, some staff members have been using electronic voting systems (EVS) to enliven the classroom and enable large numbers of students to respond to questions in real time during class. In this paper, we present an evaluation case study, based on student perceptions, of the impact of EVS use on student learning and engagement. The results show that majority of students are hugely positive about the usefulness and overall advantageousness of EVS use in classes. Results also show that EVS use does increase the likelihood of students participating and engaging in class, as even students who do not view EVS as being particularly useful stated that they are more likely to participate in classes where EVS are used than otherwise. However, there seems to be no correlation between EVS use and improvement (or otherwise) in student grades.
Hierarchical mobile router support in nested mobile networks
Authors: Jun-Hong Lu, Ren-Hung Hwang
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

With the rapid development from mobile computing toward ubiquitous computing, more and more users access to wireless network service at anytime anywhere with various kinds of portable mobile devices. To effectively support a group of mobile devices move together, the network mobility basic support protocol (NEMO-BSP) has been proposed. It defines a mobile network as one or more mobile router (MR) with one or more IP subnets each with some mobile network nodes (MNN). Each MNN acquires its network prefix from the MR and accesses the Internet through MR. Mobile network could be nested as one mobile network moves into the scope of another mobile network. However, routing path becomes very long as the nested level increases. As a consequence, it also increases the overhead of the IP tunneling. In this paper, we propose a Hierarchical Mobile Router architecture, called HMR-NEMO, to improve the routing performance as well as reduce the IP tunneling overhead of NEMO for nested mobile networks. In HMR-NEMO, the top level MR acts as a MAP such that packets from Home Agent (HA) or Corresponding Node (CN) of MNN could be directly tunneled to the top level MR and then tunneled to MR. Furthermore, binding update could also be suppressed at top level MR. Our simulation results show that HMR-NEMO significantly reduces the IP tunneling overhead and binding update overhead while improves the routing efficiency.