ppxscal/embedding_network huggingface dataset:
Extended study of the classification of dopamine receptor agonists and antagonists using a TFS-based support vector machine
Authors: Satoshi Fujishima, Yoshimasa Takahashi, Katsumi Nishikori, Hiroaki Kato, Takashi Okada
Venue: New Generation Computing (2007)

We previously investigated the classification and prediction of dopamine D1 receptor agonists and antagonists using a topological fragment spectra (TFS)-based support vector machine (SVM), in which the dataset contained noise compounds that had no D1 receptor activity. This work extended the dataset to seven activity classes (dopamine D1, D2, and auto-receptor agonists, and D1, D2, D3, and D4 antagonists) and increased the noise ratio to ten times that of active compounds. In total, this study used 16,008 compounds for training and 1,779 compounds for prediction. The TFS-based SVM gave good, stable results for both classification and prediction, even in the case that included ten times the noise data. The resulting model correctly predicted 97.6% of the prediction set of 1,779 compounds.
Approximate max flow on small depth networks
Authors: E. Cohen
Venue: Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (1992)

The author considers the maximum flow problem on directed acyclic networks with m edges and depth r (length of the longest s-t path). The main result is a new deterministic algorithm for solving the relaxed problem of computing an s-t flow of value at least (1- epsilon ) of the maximum flow. For instances where r and epsilon /sup -1/ are small (i.e., O(polylog(m))), this algorithm is in NC and uses only O(m) processors, which is a significant improvement over existing parallel algorithms. As one consequence, he obtains an NC O(m) processor algorithm to find a bipartite matching of cardinality (1- epsilon ) of the maximum (for epsilon /sup -1/ = O(polylog(m))). The parallel bounds are based on a novel approach to the blocking flow problem that produces fractional valued flow augmentations even when capacities are integral. She shows that a fractional flow on any network with integral capacities can be rounded in polylogarithmic time to an integral flow of no smaller value using O(m) processors. Hence, within the same resource bounds, an integral flow can be obtained when desired.
Optimal 2-D recursive digital filter design using particle swarm optimization
Authors: Morris Abraham Gnanamuthu Ezra, K. Ramar, C. Eswaran
Venue: Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing (2006)

In the process of designing digital recursive filter to satisfy a given magnitude response, the designer may end up with an unstable filter. This unstable filter can be stabilized using methods such as Planar Least Square Inverse (PLSI) technique, Complex Ceptrum Method etc. The Planar Least Square Inverse technique is supposed to preserve the desired magnitude response which is found to be not true in all cases. Hence a new method of designing stable recursive filters using PLSI technique and particle swarm optimization algorithm is presented in this paper. The optimally designed filter will have a magnitude response almost similar to the desired magnitude response.
Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday, 1 edition
Authors: Pierpaolo Degano, Rocco De Nicola, Jos Meseguer
Venue: Lecture Notes In Computer Science (2008)

This Festschrift volume, pubished in honor of Ugo Montanari on the occasion of his 65th birthday, contains 43 papers, written by friends and colleagues, all leading scientists in their own right, who congregated at a celebratory symposium held on June 12, 2008, in Pisa. The volume consists of seven sections, six of which are dedicated to the main research areas to which Ugo Montanari has contributed: Graph Transformation; Constraint and Logic Programming; Software Engineering; Concurrency; Models of Computation; and Software Verification. Each of these six sections starts with an introductory paper giving an account of Ugo Montanaris contribution to the area and describing the papers in the section. The final section consists of a number of papers giving a laudation of Ugo Montanaris numerous achievements.
SBK: A Self-Configuring Framework for Bootstrapping Keys in Sensor Networks
Authors: Fang Liu, Xiuzhen Cheng, Liran Ma, Kai Xing
Venue: IEEE Transactions on Mobile Computing (2008)

Key pre-distribution has been claimed to be the only viable approach for establishing shared keys between neighboring sensors after deployment for a typical sensor network. However, none of the proposed key pre-distribution schemes simultaneously achieves good performance in terms of scalability in network size, key-sharing probability between neighboring sensors, memory overhead for keying information storage, and resilience against node capture attacks. In this paper, we propose SBK, an in-situ self-configuring framework to bootstrap keys in large-scale sensor networks. SBK is fundamentally different compared to all key pre-distribution schemes. It requires no keying information pre-deployment. In SBK, sensors differentiate their roles as either service nodes or worker nodes after deployment. Service sensors construct key spaces, and distribute keying information in order for worker sensors to bootstrap pairwise keys. An improved scheme, iSBK, is also proposed to speed up the bootstrapping procedure. We conduct both theoretical analysis and simulation study to evaluate the performances of SBK and iSBK. To the best of our knowledge, SBK and iSBK are the only key establishment protocols that simultaneously achieve good performance in scalability, key-sharing probability, storage overhead, and resilience against node capture attacks.
Deprotection kinetic monitoring of a 193nm positive tone resist by ellipsometry
Authors: H. Ridaoui, J. H. Tortai, S. Derrough, C. Sourd, H. Trouve, A. Pikon
Venue: Microelectronic Engineering (2008)

Optical changes in thin films of model photoresist materials were measured in real time with ellipsometry during UV exposure and heating. A critique change in the optical parameters of the film is detected if the sample is heated during EUV exposure, showing that deprotection reaction initiation can be measured by ellipsometry. Hence the kinetic of deprotection reaction is measured at various temperatures for different doses. Simulation of the optical changes of the film shows a rapid film compaction during the deprotection, and final compaction is linked to the deprotection ratio of the resist.
End-user adoption of animated interface agentsin everyday work applications
Authors: Alexander Serenko, Nick Bontis, Brian Detlor
Venue: Behaviour & Information Technology (2007)

Recognizing the potential contribution that interactive software agents bring to everyday work applications, this paper reports on end-user adoption of animated interface agents in one particular work application environment: Microsoft® Office. The paper develops and empirically tests a theoretical model of the factors affecting an end-user's choice to adopt and utilize such interface agents. From this theoretical model, a survey instrument was adapted and administered to 261 participants, familiar with animated interface agents. Results from a partial least squares (PLS) analysis indicates that a variety of factors are at play, which inhibit or foster a person's choice to utilize and adopt animated interface agents. Of significance is that: (a) both perceived usefulness and perceived enjoyment are important influencing factors; (b) users with high scores in innovativeness toward information technology are less likely to find animated interface agents enjoyable; (c) individuals with high animation predisposition scores perceive animated interface agents to be more enjoyable; and (d) users who perceive animated interface agents to be more enjoyable also perceive them to be more useful. Such insights can be used to leverage the introduction and rollout of animated interface agents in everyday work applications in ways that promote their avid adoption and use.
Compositional Feasibility Analysis of Conditional Real-Time Task Models
Authors: Madhukar Anand, Arvind Easwaran, Sebastian Fischmeister, Insup Lee
Venue: Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (2008)

Conditional real-time task models, which are generalizations of periodic, sporadic, and multi-frame tasks, represent real world applications more accurately. These models can be classified based on a tradeoff in two dimensions - expressivity and hardness of schedulability analysis. In this work, we introduce a class of conditional task models and derive efficient schedulability analysis techniques for them. These models are more expressive than existing models for which efficient analysis techniques are known. In this work, we also lay the groundwork for schedulability analysis of hierarchical scheduling frameworks with conditional task models. We propose techniques that abstract timing requirements of conditional task models, and support compositional analysis using these abstractions.
Unsupervised learning of multilingual short message service (SMS) dialect from noisy examples
Authors: Sreangsu Acharyya, Sumit Negi, L. V. Subramaniam, Shourya Roy
Venue: Proceedings of the second workshop on Analytics for noisy unstructured text data (2008)

Noise in textual data such as those introduced by multi-linguality, misspellings, abbreviations, deletions, phonetic spellings, non standard transliteration, etc pose considerable problems for text-mining. Such corruptions are very common in instant messenger (IM) and short message service (SMS) data and adversely affect off the shelf text mining methods. Most techniques address this problem by supervised methods. But they require labels that are very expensive and time consuming to obtain. While we do not champion unsupervised methods over supervised when quality of results is the supreme and singular concern, we demonstrate that unsupervised methods can provide cost effective results without the need for expensive human intervention to generate parallely labelled corpora. A generative model based unsupervised technique is presented that maps non-standard words to their corresponding conventional frequent form. A Hidden Markov Model (HMM) over subsequencized representation of words is used subject to a parameterization such that the training phase involves clustering over vectors and not the customary dynamic programming over sequences. A principled transformation of maximum likelihood based "central clustering" cost function into a "pairwise similarity" based clustering is proposed. This transformation makes it possible to apply "subsequence kernel" based methods that model delete and insert edit operations well. The novelty of this approach lies in that the expensive (Baum-Welch) iterations required for HMM, can be avoided through a careful factorization of the HMM Loglikelihood and in establishing the connection between information theoretic cost function and the kernel approach of machine learning. Anecdotal evidence of efficacy is provided on public and proprietary data.
Dual band array for adaptive antenna systems
Authors: Ivo Hertl, Michal Vavrda
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

In this work we design and optimise the dual-band array for adaptive antenna systems. The antenna has in one configuration directional transversal radiation with both horizontal and vertical polarization and in the second constellation omni-directional axial radiation with horizontal polarization. In the second part of the paper we present results of simulations by NEC code (method of moment) with 4nec2X as the interface. Finally comparison with other existing antennas is shown.
My Sports Pulse: Increasing Student Interest in STEM Disciplines through Sports Themes, Games and Mobile Technologies
Authors: David Metcalf, Marcelo Milrad, Dennis Cheek, Sara Raasch, Angela Hamilton
Venue: Proceedings of the Fifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in Education (2008)

My Sports Pulse is a program designed to promote student achievement and interests in science and math disciplines using sports themed scenarios and celebrity athlete presence delivered over mobile devices to reach the broadest possible audience. The program is set up to pilot in five different geographic locations around the globe, followed by a broader public launch. During the phase one pilot, research questions include the effectiveness of the program in promoting student engagement and interests in math and science. The research data will provide insight into the effectiveness of extrinsic motivators, and their transference to intrinsic motivation using games and simulations toward the study of STEM (Science, Technology, Engineering, and Mathematics) disciplines. In this paper, we will present the design heuristics and conceptual framework for the My Sports Pulse program.
Fault detection in conductive pipelines by time domain reflectometry
Authors: R. Araneo, S. Celozz, F. Maradei, G. Potini
Venue: Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation (2005)

An experimental investigation is performed to carry out the feasibility of using an electrical method for the detection of defects in conductive pipelines. The pipeline, with an auxiliary conductor acting as signal return, is treated as a transmission line, and the time domain reflectometry (TDR) technique is used to reveal the presence of holes or defects. The introduction of the auxiliary conductor reduces considerably the influence of the pipeline installation features on the propagation of electrical signals along the pipeline (i.e., presence of ground, impact of the weather conditions on the ground electrical parameters, etc.). Suitable statistical processing of the TDR measured data allows the pipeline fault identification. The proposed method is appealing since it may represent a continuous and economic diagnostic method for testing the pipeline integrity.
Nanoimprint for future non-volatile memory and logic devices
Authors: M. Meier, C. Nauenheim, S. Gilles, D. Mayer, C. Kügeler, R. Waser
Venue: Microelectronic Engineering (2008)

Nanoimprint lithography (NIL) is used to realize next generation memory and logic devices. The simple device structure consists of a resistance switching material sandwiched between two metal nanoelectrodes. Bottom and top electrodes are aligned perpendicular to each other building a crossbar array structure. A significant advantage of these future devices in addition to its simplicity is the high integration density. Crossbar arrays with 200nm electrodes and single cross junctions with 30nm electrodes were achieved using UV NIL. The bottom electrodes were embedded and planarized by spin on glass, such that an even surface for the realization of the top electrodes by UV NIL could be obtained. Finally electrical measurements demonstrated the function of the fabricated devices.
SLOT: A Fast and Accurate Technique to Estimate Available Bandwidth in Wireless IEEE 802.11
Authors: Abdelaziz Amamra, Kun Mean Hou
Venue: Proceedings of the Tenth International Conference on Computer Modeling and Simulation (2008)

Accuracy of available estimated bandwidth and convergence delay algorithm are researchers’ challenges in wireless network measurements. Currently a variety of tools are developed to estimate the end-to-end network available bandwidth such as TOPP (Train Of Packet Pair), SLoPS (Self Loading Periodic Stream), Spurce and Variable Packet Size etc. These tools are important to improve the QoS (Quality of Service) of demanding applications. However the performances of the previous tools are very different in term of probing time and estimation accuracy. In this paper we present a fast and accurate bandwidth estimation technique named SLOT. By using NS2 the performance of SLOT technique will be evaluated and the obtain results are analysed by MATLAB software and compared with the TOPP and the SLoPS ones. We show that SLOT has shorter probing time than the TOPP one, and it provides more accurate available estimated bandwidth than the SLoPS one.
Evaluation of neural networks-based controllers in batch polymerisation of methyl methacrylate
Authors: E. E. Ekpo, I. M. Mujtaba
Venue: Neurocomputing (2008)

The importance of batch reactors in today's process industries cannot be overstated. Thus said, it is important to optimise their operation in order to consistently achieve products of high quality while minimising the production of undesirables. In processes like polymerisation, these reactors are responsible for a greater number of products than other reactor types and the need for optimal operation is therefore greater. An approach based on an offline dynamic optimisation and online control strategy is used in this work to generate optimal set point profiles for the batch polymerisation of methyl methacrylate. Dynamic optimisation is carried out from which controller set points to attain desired polymer molecular end point characteristics are achieved. Temperature is the main variable to be controlled, and this is done over finite discrete intervals of time. For on-line control, we evaluate the performance of neural networks in two controllers used to track the derived optimal set points for the system. The controllers are generic model control (GMC), ([P.L. Lee, G.R. Sullivan, Generic model control, Comput. Chem. Eng. 12(6) (1998) 573-580]) and the neural network-based inverse model-based control (IMBC), ([M.A. Hussain, L.S. Kershenbaum, Implementation of an inverse model based control strategy using neural networks on a partially simulated exothermic reactor, Trans. IchemE 78(A) (2000) 299-311]). Although the GMC is a model-based controller, neural networks are used to estimate the heat release within its framework for on-line control. Despite the application of these two controllers to general batch reactors, no published work exists on their application to batch polymerisation in the literature. In this work, the performance of the neural networks within each controller's algorithm for tracking and setpoint regulation of the optimal trajectory and in robustness tests on the system is evaluated.
Detecting grassland spatial variation by a wavelet approach
Authors: Yuhong He, Xulin Guo, Bing Cheng Si
Venue: International Journal of Remote Sensing (2007)

Insight into the spatial variation of an ecosystem can provide better understanding of ecological processes and patterns in different scales. Detecting these multiple scales of spatial variation in grassland landscapes is valuable for determining management options, designing proper sampling regimes, and selecting suitable resolutions of remote sensing products. The objective of this study is to examine how environmental factors affect spatial variation of biophysical properties in mixed grassland ecosystems. Field leaf area index (LAI), soil moisture, and topographical parameters (relative elevation, upslope length, and a wetness index) were obtained in three parallel transects of a grassland ecosystem in Saskatchewan, Canada in 2004. One 20-m resolution SPOT 4 (HRVIR) image was acquired at the same period of the growing season but in the following year. Normalized difference vegetation index (NDVI) was calculated from the satellite image of the centre 381-m transect and two extensive 2560-m perpendicular transects. A wavelet approach was used to identify the scales of variations. Statistical results showed that LAI is significantly correlated to the wetness index (r2 = 0.37) and soil moisture (r2 = 0.43). The wetness index is better than relative elevation and upslope length in demonstrating the effect of topography on grassland vegetation. The variation of soil moisture is significant at two small scales of about 20 m and 40 m, and that of the wetness index is at the large scale of 120 m. The variation of grassland LAI is significant at three scales (20 m, 40 m, and 120 m), which indicates that the spatial variation of LAI might be controlled by both topography and soil moisture, though the 120 m is the dominant scale of variation in LAI. NDVI significantly correlated with grassland LAI along the centre transect. The effect of topography on grassland LAI is also proven by the significant relationships between NDVI and the wetness index. The wavelet analysis identifies the variation of two extensive transects at the scale of about 120 m, which is similar to the dominant variation scale of grassland LAI. These results confirmed that the effect of topography on spatial variation can be identified from the appropriate satellite image. This study suggests that the spatial scales of soil and topographic data aid in the selection of appropriate satellite image resolution for monitoring and managing ecosystems.
Loop-free path restoration with QoS and label constraints in MPLS networks
Authors: Mort Naraghi-Pour, Chung-Yu Wei
Venue: Journal of High Speed Networks (2007)

In this paper we investigate traffic engineering for fault restoration techniques in Multiprotocol Label Switching networks carrying QoS and best effort traffic. We consider off-line computation of the working and backup paths for the QoS traffic as well as the paths for the best effort traffic. Two cases of 1+1 and 1:1 path protection are considered. Our algorithms allow for control on the size of the label space for each router in the network and ensures that the created routes are loop free. In addition, explicit routes can be accommodated supporting both node and link affinity.
Adaptive boundary layer meshing for viscous flow simulations
Authors: Onkar Sahni, Kenneth E. Jansen, Mark S. Shephard, Charles A. Taylor, Mark W. Beall
Venue: Engineering with Computers (2008)

A procedure for anisotropic mesh adaptation accounting for mixed element types and boundary layer meshes is presented. The method allows to automatically construct meshes on domains of interest to accurately and efficiently compute key flow quantities, especially near wall quantities like wall shear stress. The new adaptive approach uses local mesh modification procedures in a manner that maintains layered and graded elements near the walls, which are popularly known as boundary layer or semi-structured meshes, with highly anisotropic elements of mixed topologies. The technique developed is well suited for viscous flow applications where exact knowledge of the mesh resolution over the computational domain required to accurately resolve flow features of interest is unknown a priori. We apply the method to two types of problem cases; the first type, which lies in the field of hemodynamics, involves pulsatile flow in blood vessels including a porcine aorta case with a stenosis bypassed by a graft whereas the other involves high-speed flow through a double throat nozzle encountered in the field of aerodynamics.