ppxscal/embedding_network huggingface dataset:
Use of RADARSAT-1 data and a digital elevation model to assess flood damage and improve rice production in the lower part of the Chi River Basin, Thailand
Authors: C. Waisurasingha, M. Aniya, A. Hirano, W. Sommut
Venue: International Journal of Remote Sensing (2008)

In Thailand, flooding due to seasonal monsoon conditions frequently destroys a substantial amount of rice production, the most important agricultural activity of the country. Taking the 2001 monsoon flooding that hit the Lower Chi River Basin as an example, we developed a new method for accurately assessing damage to flood-affected paddies. A RADARSAT-1 image acquired during peak flooding was combined with a 30-m digital elevation model (DEM) to develop a 'flood-level-determination' algorithm for estimating floodwater depth. Based on the elongation capability of the rice varieties, a water depth of 80 cm was used to separate 'non-damaged' from 'damaged' paddy areas, indicating that about 60% of the paddy fields in the flooded areas were non-damaged paddies. To minimize the loss of rice and maximize farmers' incomes, a map of rice varieties appropriate for the damaged paddy areas was produced, combining the flood-affected paddy map with the flood frequency map. Our results demonstrate the potential of using single-date RADARSAT-1 data and a DEM to provide accurate and economic means of assessing flood damage to rice fields that can be used to improve rice production.
On dual problems of optimal control
Authors: A. V. Bulatov, V. F. Krotov
Venue: Automation and Remote Control (2008)

The common structure of duality of optimal control problems is suggested, which is based on the extension principle. The iterative computational algorithm is described, in which the primal and the dual problem are solved in parallel.
A Framework for Complexity Classes in Membrane Computing
Authors: Agustín Riscos-Núòez
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

The purpose of the present work is to give a general idea about the existing results and open problems concerning the study of complexity classes within the membrane computing framework. To this aim, membrane systems (seen as computing devices) are briefly introduced, providing the basic definition and summarizing the key ideas, trying to cover the various approaches that are under investigation in this area - of course, special attention is paid to the study of complexity classes. The paper concludes with some final remarks that hint the reasons why this field (as well as other unconventional models of computation) is attracting the attention of a growing community.
Original papers: A longitudinal study of the effect of time on the matching performance of a retinal recognition system for lambs
Authors: B. Barry, G. Corkery, U. Gonzales-Barron, K. Mc Donnell, F. Butler, S. Ward
Venue: Computers and Electronics in Agriculture (2008)

While there is strong evidence supporting retinal vascular pattern as a distinctive marker for sheep, it would be advantageous to get an insight into its robustness; in other words, to determine whether retinal recognition of young animals (lambs) can reach as good a matching performance as the one demonstrated for adult sheep. To this aim, a longitudinal study was devised to observe the evolution of matching scores (ms) of lamb retinal images (n=38) acquired from 1 to 22 weeks after birth. It was observed that four lamb retinas (out of 38) underwent slight curving of one or two secondary arteries, which ceased by the time they were 6-8 weeks old. However, this slight artery curving did not affect matching performance. A random effects statistical model demonstrated that lamb age had an effect (P
Retrieval of Leaf Area Index from CHRIS/PROBA data: an analysis of the directional and spectral information content
Authors: F. Vuolo, L. Dini, G. D'Urso
Venue: International Journal of Remote Sensing (2008)

The use of Earth Observation (EO) data to retrieve biophysical variables of vegetated surfaces has proved to be useful in many operative tools to gather information repetitively, at spatial and temporal resolution, for agricultural and water management applications. The launch of the European Space Agency (ESA) Compact High-Resolution Imaging Spectrometer/Project for On-Board Autonomy (CHRIS/PROBA) mission has provided an opportunity to study a multiangular and hyperspectral dataset of images with high spatial resolution. The objective of the study was to use the CHRIS/PROBA data, in both directional and spectral domains, to estimate the Leaf Area Index (LAI). For this purpose, inversion of a canopy reflectance model was performed against CHRIS data. LAI estimates were validated by using ground truth LAI measurements and compared, in terms of accuracy, to a semi-empirical approach. It was shown that, for a given spectral configuration, the directional information always improved the LAI estimation. For the best case (corn), this was achieved with an LAI root mean square error (RMSE) of 0.41 by using five angles and 62 spectral bands compared to a value of 1.42 by using one angle and four bands, as in the Landsat Thematic Mapper (TM) configuration.
On fragments of words over a q-ary alphabet
Authors: V. K. Leont'Ev, S. A. Mukhina
Venue: Problems of Information Transmission (2008)

We consider several combinatorial problems concerning fragments of words over a q-ary alphabet. We obtain a number of new facts, some of them being previously known in the binary case only.
Combining global, regional and contextual features for automatic image annotation
Authors: Yong Wang, Tao Mei, Shaogang Gong, Xian-Sheng Hua
Venue: Pattern Recognition (2009)

This paper presents a novel approach to automatic image annotation which combines global, regional, and contextual features by an extended cross-media relevance model. Unlike typical image annotation methods which use either global or regional features exclusively, as well as neglect the textual context information among the annotated words, the proposed approach incorporates the three kinds of information which are helpful to describe image semantics to annotate images by estimating their joint probability. Specifically, we describe the global features as a distribution vector of visual topics and model the textual context as a multinomial distribution. The global features provide the global distribution of visual topics over an image, while the textual context relaxes the assumption of mutual independence among annotated words which is commonly adopted in most existing methods. Both the global features and textual context are learned by a probability latent semantic analysis approach from the training data. The experiments over 5k Corel images have shown that combining these three kinds of information is beneficial in image annotation.
Investigating automatic dominance estimation in groups from visual attention and speaking activity
Authors: Hayley Hung, Dinesh Babu Jayagopi, Sileye Ba, Jean-Marc Odobez, Daniel Gatica-Perez
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

We study the automation of the visual dominance ratio (VDR); a classic measure of displayed dominance in social psychology literature, which combines both gaze and speaking activity cues. The VDR is modified to estimate dominance in multi-party group discussions where natural verbal exchanges are possible and other visual targets such as a table and slide screen are present. Our findings suggest that fully automated versions of these measures can estimate effectively the most dominant person in a meeting and can match the dominance estimation performance when manual labels of visual attention are used.
Answering Any Class of Japanese Non-factoid Question by Using the Web and Example Q&A Pairs from a Social Q&A Website
Authors: Tatsunori Mori, Mitsuru Sato, Madoka Ishioroshi
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

In this paper, we propose a method of non-factoid Web question-answering that can uniformly deal with any class of Japanese non-factoid question by using a large number of example Q&A pairs. Instead of preparing classes of questions beforehand, the method retrieves already asked question examples similar to a submitted question from a set of Q&A pairs. Then, instead of preparing clue expressions for the writing style of answers according to each question class beforehand, it dynamically extracts clue expressions from the answer examples corresponding to the retrieved question examples. This clue expression information is combined with topical content information from the question to extract appropriate answer candidates. The experimental results showed that the clue expressions obtained from the set of examples improved the accuracy of answer candidate extraction.
Novice LISP errors: undetected losses of information from working memory
Authors: John R. Anderson, Robin Jeffries
Venue: Human-computer interaction (1985)

Four experiments study the errors students make using LISP functions. The first two experiments show that frequency of errors is increased by increasing the complexity of irrelevant aspects of the problem. The experiments also show that the distribution of errors is largely random and that subjects' errors seem to result from slips rather than from misconceptions. Experiment 3 shows that subjects' errors tend to involve loss of parentheses in answers when the resulting errors are well-formed LISP expressions. Experiment 4 asks subjects, who knew no LISP, to judge the reasonableness of the answers to various LISP function calls. Subjects could detect many errors on the basis of general criteria of what a reasonable answer should look like. On the basis of these four experiments, we conclude that errors occur when there is a loss of information in the working memory representation of the problem and when the resulting answer still looks reasonable.
From Motion Capture to Real-Time Character Animation
Authors: Franck Multon, Richard Kulpa, Ludovic Hoyet, Taku Komura
Venue: Motion in Games: First International Workshop, MIG 2008, Utrecht, The Netherlands, June 14-17, 2008. Revised Papers (2008)

This paper describes a framework for animating virtual characters in real-time environments thanks to motion capture data. In this paper, we mainly focus on the adaptation of motion capture data to the virtual skeleton and to its environment. To speed-up this real-time process we introduce a morphology-independent representation of motion. Based on this representation, we have redesigned the methods for inverse kinematics and kinetics so that our method can adapt the motion thanks to spacetime constraints, including a control of the center of mass position. If the resulting motion doesn't satisfy general mechanical laws (such as maintaining the angular momentum constant during aerial phases) the current pose is corrected. External additional forces can also be considered in the dynamic correction module so that the character automatically bend his hips when pushing heavy objects, for example. All this process is performed in real-time.
An architecture for online comparison and validation of processing methods and computerized guidelines in intensive care units
Authors: L. Allart, C. Vilhelm, H. Mehdaoui, H. Hubert, B. Sarrazin, D. Zitouni, M. Lemdani, P. Ravaux
Venue: Computer Methods and Programs in Biomedicine (2009)

Clinical decision support systems are a combination of software techniques to help the clinicians in their medical decision making process via functionalities ranging from basic signal analysis to therapeutic planning and computerized guidelines. The algorithms providing all these functionalities must be very carefully validated on real patient data and must be confronted to everyday clinical practice. One of the main problems when developing these techniques is the difficulty to obtain high-quality complete patient records, comprising data coming both from the biomedical equipment (high-frequency signals), and from numerous other sources (therapeutics, imagery, clinical actions, etc.). In this paper, we present an infrastructure for developing and testing such software algorithms. It is based on a bedside workstation where testing different algorithms simultaneously on real-time data is possible in the ward. It is completed by a collaborative portal enabling different teams to test their software algorithms on the same patient records, making comparisons and cross-validations more easily.
Self-organized adaptive legged locomotion in a compliant quadruped robot
Authors: Jonas Buchli, Auke Jan Ijspeert
Venue: Autonomous Robots (2008)

In this contribution we present experiments of an adaptive locomotion controller on a compliant quadruped robot. The adaptive controller consists of adaptive frequency oscillators in different configurations and produces dynamic gaits such as bounding and jumping. We show two main results: (1) The adaptive controller is able to track the resonant frequency of the robot which is a function of different body parameters (2) controllers based on dynamical systems as we present are able to "recognize" mechanically intrinsic modes of locomotion, adapt to them and enforce them. More specifically the main results are supported by several experiments, showing first that the adaptive controller is constantly tracking body properties and readjusting to them. Second, that important gait parameters are dependent on the geometry and movement of the robot and the controller can account for that. Third, that local control is sufficient and the adaptive controller can adapt to the different mechanical modes. And finally, that key properties of the gaits are not only depending on properties of the body but also the actual mode of movement that the body is operating in. We show that even if we specify the gait pattern on the level of the CPG the chosen gait pattern does not necessarily correspond to the CPG's pattern. Furthermore, we present the analytical treatment of adaptive frequency oscillators in closed feedback loops, and compare the results to the data from the robot experiments.
Affine Romance
Authors: Stan Kelly-Bootle
Venue: Queue (2008)

Buyer (and seller) beware
Real-Time Reasoning Based on Event-Condition-Action Rules
Authors: Ying Qiao, Xiang Li, Hongan Wang, Kang Zhong
Venue: Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS (2008)

In this paper, we develop a reasoning mechanism for real-time and active database (RTADB). The core of this reasoning mechanism is a real-time inference algorithm based on Event-condition-action (ECA) rules, called RTIAE. This algorithm is based on heuristic search on a rule graph so as to give the actions responding to occurring events as many as possible under certain timing constraint. Furthermore, we conduct a series of simulations studies to analyze the performance of the proposed algorithm and compare it with depth-first algorithm.
Context Grouping Mechanism for Context Distribution in Ubiquitous Environments
Authors: M. Kirsch-Pinheiro, Y. Vanrompay, K. Victor, Y. Berbers, M. Valla, C. Frà, A. Mamelli, P. Barone, X. Hu, A. Devlic, G. Panagiotou
Venue: Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems: (2008)

Context distribution is a key aspect for successful applications within mobile and ubiquitous computing environments. In such environments, context information is acquired by several and multiple context sensors distributed over the environment. Applications collect and react to these data, according to predefined adaptation mechanisms. The success of these mechanisms depends on the availability of context information, which is disseminated over the network. However, in practice, only a fraction of the observable context information is required by the adaptation mechanisms. Moreover, for privacy reasons, it is important to delimitate a scope for context dissemination. In this work we address these issues by proposing a context grouping mechanism which allows the definition of groups based on the context characteristics. Each group is defined by these characteristics and delimitate a given context information set that can be distributed among group members. This approach of context grouping acts as a two-fold mechanism. On the one hand, it controls and organizes context distribution over a peer-to-peer network. On the other hand, it proposes a primary and low-level privacy mechanism for context distribution, which is an important aspect influencing context distribution.
Evaluation of the Weather Research and Forecasting model for two frost events
Authors: Thara Prabha, Gerrit Hoogenboom
Venue: Computers and Electronics in Agriculture (2008)

Meso-local-scale weather information could be used as a guideline for crop protection to effectively manage and mitigate the effects of frost damage. The main goal of this study was to evaluate the meso-local-scale weather forecasts from the state-of-the-art Advanced Research Weather Research and Forecasting (WRF-ARW) model for episodic frost events. We selected two periods: an episode of intermittent frost occurrences from 3-9 December 2006 characterizing both advective and radiative type frost and an extended period of advective frost from 3-11 April 2007 that caused severe crop damage across the southeastern United States. The high-resolution ARW model simulations were compared against observations taken in blueberry and peach orchards by the Georgia Automated Environmental Monitoring Network (AEMN; www.georgiaweather.net). Comparisons were made for air, wetbulb, and dewpoint temperature, and wind speed and direction. Nighttime temperatures were forecasted with a bias of +/-1.5^oC with cold biases during the April case and warmer biases during the December case. The daytime temperature predictions showed a consistent increase in cold bias (up to -2 to -4^oC) with time of the day until 2h before sunset. The model skill in predicting dewpoint temperature strongly depended on the time of day; low biases
Prediction of domestic warm-water consumption
Authors: Elena Serban, Daniela Popescu
Venue: WSEAS Transactions on Computers (2008)

The paper presents methodologies able to predict dynamic warm water consumption in district heating systems, using time-series analysis. A simulation model according to the day of a week has been chosen for modeling the domestic warm water consumption in a block of flats with 60 apartments. The analysis of the residuals indicates good simulation and prediction models for the cases studied. Double-cross validation was done using data collected by the SCADA system from District Heating Company of Iasi.
In Search of Optimum Possible Organizations through Agent Modeling - Business Environment Recognition Models
Authors: Masahiro Toriyama, Takamasa Kikuchi, Yuji Nakagawa, Takashi Yamada, Takao Terano
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

This paper presents a novel agent-based simulation model to analyze organization structures, which will show optimum possible performances against environmental and organizational changes. The model is a natural extension of the tag model of cultural assimilations proposed by Axelrod. Using the model, we investigate the landscape of "could be" space of organizations using random search. The proposed model focuses on the process of how the organizational recognition on business environment changes when they face new one. Regular personnel reshuffle program is also performed on the model. The major findings are: 1) Optimum organizational structure is contingent upon who recognizes the environment, and 2) Personnel decision of who and when to transfer, has much more impact than existence of regular personnel reshuffle system.
A patch spectral purification method to extract field patch average parameters from moderate resolution data
Authors: J. Li, Q. Liu, Q. Liu, Y. Tang, Q. Xiao
Venue: International Journal of Remote Sensing (2008)

Satellite remote sensing data with high spatial and temporal resolutions are required in the dynamic monitoring of agricultural information. However, currently it is not yet possible to embrace the advantages of both high spatial resolution and high temporal resolution in a single sensor. Combining the merits from different remote sensing data will greatly benefit agricultural applications. In this paper, a patch spectral purification (PSP) method is developed to estimate the pure reflectance of field patches by combining high and moderate spatial resolution image data. The PSP method adopts the linear mixing model to build equations from moderate spatial resolution images, estimates initial values of field patch reflectance by statistical means to provide constraints to the solution and solves the equation sets based on Bayes' theorem. We chose one farm in Xinjiang, China as the study area and took 250 m MODIS image data as an example to test the performance of the method. The sensitivity analysis and the validation indicate that the PSP method is capable of giving a good estimation of pure field patch reflectance from mixed pixels of 250 m MODIS images in the study area.
Corn-yield estimation through assimilation of remotely sensed data into the CSM-CERES-Maize model
Authors: Hongliang Fang, Shunlin Liang, Gerrit Hoogenboom, John Teasdale, Michel Cavigelli
Venue: International Journal of Remote Sensing (2008)

One of the applications of crop simulation models is to estimate crop yield during the current growing season. Several studies have tried to integrate crop simulation models with remotely sensed data through data-assimilation methods. This approach has the advantage of allowing reinitialization of model parameters with remotely sensed observations to improve model performance. In this study, the Cropping System Model-CERES-Maize was integrated with the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products for estimating corn yield in the state of Indiana, USA. This procedure, inversion of crop simulation model, facilitates several different user input modes and outputs a series of agronomic and biophysical parameters, including crop yield. The estimated corn yield in 2000 compared reasonably well with the US Department of Agriculture National Agricultural Statistics Service statistics for most counties. Using the seasonal LAI in the optimization procedure produced the best results compared with only the green-up LAIs or the highest LAI values. Planting, emergence and maturation dates, and N fertilizer application rates were also estimated at a regional level. Further studies will include investigating model uncertainties and using other MODIS products, such as the enhanced vegetation index.
GIMSAN
Authors: Patrick Ng, Uri Keich
Venue: Bioinformatics (2008)

Summary: We present GIMSAN (GIbbsMarkov with Significance ANalysis): a novel tool for de novo motif finding. GIMSAN combines GibbsMarkov, our variant of the Gibbs Sampler, described here for the first time, with our recently introduced significance analysis. Availability: GIMSAN is currently available as a web application and a stand-alone application on Unix and PBS (Portable Batch System) cluster through links from http://www.cs.cornell.edu/~keich. Contact: keich@cs.cornell.edu