ppxscal/embedding_network huggingface dataset:
Application of neural networks as a non-linear modelling technique in food mycology
Authors: E. Z. Panagou, V. S. Kodogiannis
Venue: Expert Systems with Applications: An International Journal (2009)

Fungal growth leads to spoilage of food and animal feeds and to formation of mycotoxins and potentially allergenic spores. There is a growing interest in modelling microbial growth as an alternative to time-consuming, traditional, microbiological enumeration techniques. Several statistical models have been reported to describe the growth of different micro-organisms however the nature of neural networks, as highly non-linear approximator schemes, considers them as an alternative methodology. The application of neural networks in predictive microbiology is presented in this paper. This technique was used to build up a model of the joint effect of water activity, pH level and temperature to predict the maximum specific growth rate of the ascomycetous fungus Monascus ruber. Neural network and polynomial models were compared against the experimental data using six statistical indices namely, coefficient of determination (R^2), root mean square error (RMSE), mean relative percentage error (MRPE), mean absolute percentage error (MAPE), standard error of prediction (SEP), bias (B"f) and accuracy (A"f) factors. Graphical plots were also used for model comparison. The performance of the learning-based systems provide encouraging results while sensitivity analysis showed that from the three environmental factors the most influential on fungal growth was temperature, followed by water activity and pH to a lesser extend. Neural networks offer an alternative and powerful technique to model microbial kinetic parameters and could thus become an additional tool in predictive mycology.
Mapping of Discrete Cosine Transforms onto Distributed Hardware Architectures
Authors: Rafael A. Arce-Nazario, Manuel Jiménez, Domingo Rodríguez
Venue: Journal of Signal Processing Systems (2008)

We present an algorithmically-aware, high-level partitioning methodology for discrete cosine transforms (DCT) targeted to distributed hardware architectures. The methodology relies on the exploration of alternate DCT formulations as part of the partition optimization process. To the best of our knowledge, no previously proposed DCT algorithm exists that is capable of consistently producing alternate regular formulations for an n-size DCT. Hence, a new Cooley-Tukey-like DCT factorization algorithm was developed to allow exploration of alternate formulations as part of the partitioning optimization process. The use of our factorization mechanism along with a greedy strategy to explore the space of equivalent DCT formulations yielded partitioning solutions with as much as 18% reduction in latency and 83% reduction in run-time as compared to previously proposed regular DCT formulations.
Adopting ontologies for multisource identity resolution
Authors: Milena Yankova, Horacio Saggion, Hamish Cunningham
Venue: Proceedings of the first international workshop on Ontology-supported business intelligence (2008)

Identity resolution aims at identifying the newly presented facts and linking them to their previous mentions. Our main hypothesis is that variations of one and the same fact can be recognised, duplications removed and their aggregation actually increases the correctness of fact extraction. Our approach to the identity problem has been implemented as Identity Resolution Framework (IdRF). The framework provides a general solution identifying known and new facts in specific domains, and it can be used in different applications for processing of different types of entity. It uses an ontology for internal and resulting knowledge representational formalism. The ontology not only contains the representation of the domain, but also known entities and properties. Apart from extracting information from textual sources, we also exploit structured information available in databases mapping the database schema to the ontology and populating the ontology with existing knowledge. Our main goal is not to advocate one criterion among the others, but to introduce widely applicable solution of the identity resolution problem, we present a set of customisable criteria as well as a mechanism new criteria to be added. We have carried two series of experiments in two different business intelligence domains - company profiling and recruitment - achieving rather encouraging result.
Influence of neotectonic activity on groundwater salinity and playa development in the Mendha river catchment, western India
Authors: V. S. Rathore, M. S. Nathawat, P. K. Champati Ray
Venue: International Journal of Remote Sensing (2008)

The groundwater salinity of Mendha river, one of the important streams that feed Sambhar playa in Rajasthan in western India, was studied to understand the effect of neotectonic activity on groundwater quality and salinity. We attempted to decouple the tectonic control of salinity and its contribution in the development of playa deposits in Rajasthan. Multiresolution, multidate satellite data products such as IRS-1C, IRS-1D LISS-III, PAN and Landsat MSS were digitally enhanced and analysed to model the morphotectonic evolution and hydrological regime of the region. Electrical conductance data from spatially distributed points in the Mendha river basin were correlated with the aquifer geometry deciphered from borehole lithologs and lineaments and major geomorphic features interpreted from satellite images. The results of the study reveal that the aquifer geometry is controlled by subsurface structures that have been influenced by neotectonic activity in the past 8-9 ka, significantly influencing the hydrological regime and salinity of Sambhar playa.
Yale Image Finder (YIF)
Authors: Songhua Xu, James McCusker, Michael Krauthammer
Venue: Bioinformatics (2008)

Summary: Yale Image Finder (YIF) is a publicly accessible search engine featuring a new way of retrieving biomedical images and associated papers based on the text carried inside the images. Image queries can also be issued against the image caption, as well as words in the associated paper abstract and title. A typical search scenario using YIF is as follows: a user provides few search keywords and the most relevant images are returned and presented in the form of thumbnails. Users can click on the image of interest to retrieve the high resolution image. In addition, the search engine will provide two types of related images: those that appear in the same paper, and those from other papers with similar image content. Retrieved images link back to their source papers, allowing users to find related papers starting with an image of interest. Currently, YIF has indexed over 140 000 images from over 34 000 open access biomedical journal papers. Availability: http://krauthammerlab.med.yale.edu/imagefinder/ Contact: michael.krauthammer@yale.edu
Database indexing for production MegaBLAST searches
Authors: Aleksandr Morgulis, George Coulouris, Yan Raytselis, Thomas L. Madden, Richa Agarwala, Alejandro A. Schäffer
Venue: Bioinformatics (2008)

Motivation: The BLAST software package for sequence comparison speeds up homology search by preprocessing a query sequence into a lookup table. Numerous research studies have suggested that preprocessing the database instead would give better performance. However, production usage of sequence comparison methods that preprocess the database has been limited to programs such as BLAT and SSAHA that are designed to find matches when query and database subsequences are highly similar. Results: We developed a new version of the MegaBLAST module of BLAST that does the initial phase of finding short seeds for matches by searching a database index. We also developed a program makembindex that preprocesses the database into a data structure for rapid seed searching. We show that the new ‘indexed MegaBLAST’ is faster than the ‘non-indexed’ version for most practical uses. We show that indexed MegaBLAST is faster than miBLAST, another implementation of BLAST nucleotide searching with a preprocessed database, for most of the 200 queries we tested. To deploy indexed MegaBLAST as part of NCBI'sWeb BLAST service, the storage of databases and the queueing mechanism were modified, so that some machines are now dedicated to serving queries for a specific database. The response time for such Web queries is now faster than it was when each computer handled queries for multiple databases. Availability: The code for indexed MegaBLAST is part of the blastn program in the NCBI C++ toolkit. The preprocessor program makembindex is also in the toolkit. Indexed MegaBLAST has been used in production on NCBI's Web BLAST service to search one version of the human and mouse genomes since October 2007. The Linux command-line executables for blastn and makembindex, documentation, and some query sets used to carry out the tests described below are available in the directory: ftp://ftp.ncbi.nlm.nih.gov/agarwala/indexed_megablast Contact: schaffer@helix.nih.gov Supplementary information:Supplementary data are available at Bioinformatics online.
Hashed samples: selectivity estimators for set similarity selection queries
Authors: Marios Hadjieleftheriou, Xiaohui Yu, Nick Koudas, Divesh Srivastava
Venue: Proceedings of the VLDB Endowment (2008)

We study selectivity estimation techniques for set similarity queries. A wide variety of similarity measures for sets have been proposed in the past. In this work we concentrate on the class of weighted similarity measures (e.g., TF/IDF and BM25 cosine similarity and variants) and design selectivity estimators based on a priori constructed samples. First, we study the pitfalls associated with straightforward applications of random sampling, and argue that care needs to be taken in how the samples are constructed; uniform random sampling yields very low accuracy, while query sensitive realtime sampling is more expensive than exact solutions (both in CPU and I/O cost). We show how to build robust samples a priori, based on existing synopses for distinct value estimation. We prove the accuracy of our technique theoretically, and verify its performance experimentally. Our algorithm is orders of magnitude faster than exact solutions and has very small space overhead.
Joint rate-and-power allocation for multi-channel spectrum sharing networks
Authors: Yuan Wu, Danny H. K. Tsang
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

In this abstract, we propose a study on joint rate-and-power allocation problem for multi-channel spectrum sharing networks (SSNs). We formulate this cross-layer optimization problem as a non-cooperative potential game GJRPA in which each user has a coupled two-tuple strategy, i.e., simultaneous rate and multi-channel power allocations. A multi-objective cost function is designed to represent user's awareness of both QoS provisioning and power saving. Using the game-theoretic formulation, we investigate the properties of Nash equilibrium (N.E.) for our GJRPA model, including its existence, and properties of QoS provisioning as well as power saving. Furthermore, a layered structure is derived by applying Lagrangian dual decomposition to GJRPA and a distributed algorithm is proposed to find the N.E. via this structure.
Enhancing SCTP loss recovery: An experimental evaluation of early retransmit
Authors: Per Hurtig, Anna Brunstrom
Venue: Computer Communications (2008)

To reduce cost and provide more flexible services, telecommunication operators are currently replacing traditional circuit-switched telephony networks with packet-switched IP networks. To support the stringent requirements of telephony signaling (SS7), the SIGTRAN working group of the IETF specified the transport protocol SCTP. SCTP was developed to overcome a number of problems that follow from using TCP for signaling transport. However, the design of SCTP was to a great extent still based on TCP, and some problems related to signaling transport were inherited. For example, the loss recovery mechanisms in SCTP are almost identical to those of TCP. This is a problem as signaling traffic has stringent requirements on timely message delivery. TCP was not designed to meet stringent requirements on timely message delivery, and therefore the loss recovery was not optimized for it. To optimize SCTP's loss recovery for signaling traffic, we consider the loss recovery enhancement early retransmit. To make early retransmit even better suited for signaling traffic we propose a packet-based version, which was also recently included in the early retransmit specification. By experimentally evaluating this algorithm, we show that the packet-based early retransmit algorithm, in some cases, can reduce SCTP's loss recovery time by 62%.
The initial development of object knowledge by a learning robot
Authors: Joseph Modayil, Benjamin Kuipers
Venue: Robotics and Autonomous Systems (2008)

We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. We evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks, including object recognition and achieving goals that require both planning and continuous control.
Development of bio-mimetic entertainment dolphin robots
Authors: Daejung Shin, Seung Y. Na, Jin Y. Kim, Yong-Gwan Won, Bae-Ho Lee
Venue: WSEAS Transactions on Computers (2008)

Development of bio-mimetic entertainment dolphin robots that act like real dolphins in terms of autonomous swimming and human-dolphin interactions are introduced. Body structures, sensors and actuators, governing microcontroller boards, swimming and interaction features are described for a typical entertainment dolphin robot. Actions of mouth-opening, tail splash or water blow through a spout hole are the typical responses of interaction when touch sensors on its body detect users' demand. A pair of microphones as the ears of a dolphin robot, in order to improve the entertainment dolphin robot's ability to interact with people, is used to estimate the peak sound directions from surrounding viewers. Dolphin robots should turn towards people who demand to interact with them, while swimming autonomously.
Using assertions to help end-user programmers create dependable web macros
Authors: Andhy Koesnandar, Sebastian Elbaum, Gregg Rothermel, Lorin Hochstein, Christopher Scaffidi, Kathryn T. Stolee
Venue: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering (2008)

Web macros give web browser users ways to "program" tedious tasks, allowing those tasks to be repeated more quickly and reliably than when performed by hand. Web macros face dependability problems of their own, however: changes in websites or failure on the part of end-user programmers to anticipate possible macro behaviors can cause macros to act incorrectly, often in ways that are difficult to detect. We would like to provide at least some of the benefits of software engineering methodologies to the creators of web macros. To do this we adapt assertions to web-macro programming scenarios. While assertions are well-known to professional software engineers, our web macro assertions are unique in their focus on website evolution, are generated automatically, and encode the expectations and assumptions of a rapidly growing group of users who often have limited formal programming expertise. We have integrated our techniques for assertion generation and evaluation into a web macro tool, and performed an empirical study investigating its use. Our results show that the assertions can help web macro users detect macro failures and correct macro faults.
Control of Robot Manipulators in Terms of Quasi-Velocities
Authors: Krzysztof Kozłowski, Przemysław Herman
Venue: Journal of Intelligent and Robotic Systems (2008)

In this paper we present new control algorithms for robots with dynamics described in terms of quasi-velocities (Kozłowski, Identification of articulated body inertias and decoupled control of robots in terms of quasi-coordinates. In: Proc. of the 1996 IEEE International Conference on Robotics and Automation, pp. 317---322. IEEE, Piscataway, 1996a; Zeitschrift für Angewandte Mathematik und Mechanik 76(S3):479---480, 1996c; Robot control algorithms in terms of quasi-coordinates. In: Proc. of the 34 Conference on Decision and Control, pp. 3020---3025, Kobe, 11---13 December 1996, 1996d). The equations of motion are written using spatial quantities such as spatial velocities, accelerations, forces, and articulated body inertia matrices (Kozłowski, Standard and diagonalized Lagrangian dynamics: a comparison. In: Proc. of the 1995 IEEE Int. Conf. on Robotics and Automation, pp. 2823---2828. IEEE, Piscataway, 1995b; Rodriguez and Kreutz, Recursive Mass Matrix Factorization and Inversion, An Operator Approach to Open- and Closed-Chain Multibody Dynamics, pp. 88---11. JPL, Dartmouth, 1998). The forward dynamics algorithms incorporate new control laws in terms of normalized quasi-velocities. Two cases are considered: end point trajectory tracking and trajectory tracking algorithm, in general. It is shown that by properly choosing the Lyapunov function candidate a dynamic system with appropriate feedback can be made asymptotically stable and follows the desired trajectory in the task space. All of the control laws have a new architecture in the sense that they are derived, in the so-called quasi-velocity and quasi-force space, and at any instant of time generalized positions and forces can be recovered from order $O({\cal N})$ recursions, where ${\cal N}$ denotes the number of degrees of freedom of the manipulator. This paper also contains the proposition of a sliding mode control, originally introduced by Slotine and Li (Int J Rob Res 6(3):49---59, 1987), which has been extended to the sliding mode control in the quasi-velocity and quasi-force space. Experimental results illustrate behavior of the new control schemes and show the potential of the approach in the quasi-velocity and quasi-force space.
Fusing time series expression data through hybrid aggregation and hierarchical merge
Authors: Elena Tsiporkova, Veselka Boeva
Venue: Bioinformatics (2008)

Summary: A novel integration approach targeting the combination of multi-experiment time series expression data is proposed. A recursive hybrid aggregation algorithm is initially employed to extract a set of genes, which are eventually of interest for the biological phenomenon under study. Next, a hierarchical merge procedure is speci.cally developed for the purpose of fusing together the multiple-experiment expression pro.les of the selected genes. This employs dynamic time warping alignment techniques in order to account adequately for the potential phase shift between the different experiments. We subsequently demonstrate that the resulting gene expression pro.les consistently re.ect the behavior of the original expression pro.les in the different experiments. Contact: vboeva@tu-plovdiv.bg Supplementary information: Supplementary data are available at http://www.tu-plovdiv.bg/Container/bi/DataIntegration/
Multi-scale thermal pattern monitoring of a large lake (Lake Geneva) using a multi-sensor approach
Authors: D. Oesch, J. -M. Jaquet, R. Klaus, P. Schenker
Venue: International Journal of Remote Sensing (2008)

The applicability of satellite imagery products from different sensors (AVHRR-derived multi-channel sea surface temperature (MCSST), MODIS sea surface temperature (SST) products 5-Min L2 Swath 1 km and Landsat TM band 6 thermal signature) for the comprehensive monitoring of temperature and its temporal patterns over a large lake is tested in this study. The coverage of cloud-free satellite data for Lake Geneva is reported throughout a year and, more specifically, during a 13 day period in summer 2003. In a second step, we demonstrate the feasibility of the AVHRR/MODIS imagery to discern day and night temperature patterns, by generating day and night climatologies and various spatial statistics over the 13 day period. The different day and night surface thermal patterns observed by satellite imagery could be linked to the thermal structure existing in deeper water using the concept of the diurnal decoupled layer. The forcing of the persistent patterns, two warm cores divided by a saddle-shaped cold anomaly, is explained by wind periodicity and insolation conditions. The patterns can be matched to features postulated by findings of different limnologists in the past. Other surface temperature related phenomena such as water upwelling and downwelling and the occurrence of plumes are related to meteorological and hydrological events. The lakewide average lake surface water temperature (LSWT) trends for day and night during the study period are roughly parallel. A sudden loss of stored heat can be explained by episodes of long fetch, synoptic wind (bise) that interrupted the predominant breeze regime.
Feasibility of neural network approach in spectral mixture analysis of reflectance spectra
Authors: Jyotsna Ravi, SebastianThomas Lee, Manidurai Paulraj, Rolando Hernandez
Venue: International Journal of Remote Sensing (2008)

In the present work, we perform spectral mixture analysis using Chi-square minimization (χ2 minimization) procedure and test the feasibility of applying an inverse technique, neural network (NN) approach, for the spectral unmixing. The training of NN is carried out using the Levenberg-Marquardt algorithm (LM) with the initial weights for training being chosen randomly. The experiments are performed in the laboratory by mixing young, matured and dead leaves of a sequoia tree in various proportions and reflectance spectra of these mixtures are recorded. The proportions are chosen to model a few near-real situations like different kinds of vegetation in a forest (by mixing young leaves and matured leaves) and trees damaged in a forest fire or affected by certain virus (by mixing matured and dead leaves) and a combination of all these (by mixing young, matured and dead leaves). The spectral mixture analysis employing χ2 minimization and the inverse procedure utilizing NN with two hidden layers yielded consistent results in accordance with the proportion of each kind of leaf.
In search of an optimization technique for Artificial Neural Network to classify abnormal heart sounds
Authors: Samit Ari, Goutam Saha
Venue: Applied Soft Computing (2009)

Artificial Neural Network (ANN) finds use in classification of heart sounds for its discriminative training ability and easy implementation. The selection of number of nodes for an ANN remains an important issue as an overparameterized ANN gets trained along with the redundant information that results in poor validation. Also a larger network means more computational expense, resulting more hardware and time related cost. Therefore, a compact and optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signals. This work attempts to (i) design a compact form of output layer with less number of nodes than output classes, (ii) select a set of input features that are effective for identification of heart sound signals using Singular Value Decomposition (SVD), QR factorization with column pivoting (QRcp) and Fisher's F-ratio, (iii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure using SVD and (iv) select and prune weights based on the concept of local relative sensitivity index (LRSI) for empirically chosen overparameterized ANN structure for phonocardiogram (PCG) classification. It is observed that the proposed techniques perform better in terms of reduction of model residues and time complexity for classifying 12 different pathological cases and normal heart sound.