ppxscal/embedding_network huggingface dataset:
Analysis of Autism Prevalence and Neurotoxins Using Combinatorial Fusion and Association Rule Mining
Authors: Christina Schweikert, Yanjun Li, David Dayya, David Yens, Martin Torrents, D. Frank Hsu
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

The increase in autism prevalence has been the motivation for much research which has produced various theories for its causation. Genetic and environmental factors have been investigated. An area of focus is the affect of exposure to neurotoxins, such as mercury and lead, during critical stages in a child’s early development. In this study we apply Combinatorial Fusion Analysis (CFA) and Association Rule Mining (ARM) to autism prevalence, mercury, and lead data to generate hypotheses and explore possible associations.
Towards a Computational Model of Perception and Action in Human Computer Interaction
Authors: Pascal Haazebroek, Bernhard Hommel
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

The evaluation and design of user interfaces may be facilitated by using performance models based on cognitive architectures. A recent trend in Human Computer Interaction is the increased focus on perceptual and motor-related aspects of the interaction. With respect to this focus, we present the foundations of HiTEC, a new cognitive architecture based on recent findings of interactions between perception and action in the domain of cognitive psychology. This approach is contrasted with existing architectures.
Dynamic Grid Resource Scheduling Model Using Learning Agent
Authors: Bin Zeng, Jun Wei, HaiQin Liu
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Grid scheduling is a key problem for Grid to improve the resource management and application performance. It has been proven to be a NP-hard problem for the computation of optimal Grid schedules, which is responsible to allocate resources to user jobs with the objective such as minimizing the completion time or cost. Therefore, it is more difficult for Grid scheduling system to cope with the dynamically varied resource and jobs. To solve this problem, an adaptive negotiation based scheduling model is presented. The near-optimal schedules are selected by learning agents representing the resource and jobs respectively in Grid. The agents can reduce the size of scheduling search space through a modified reinforcement learning algorithm, where the state-value function is improved by a numerical function approximation and the balance of efficiency and complexity is obtained by a simulated annealing algorithm. The results demonstrate that the proposed negotiation model and the learning agents based negotiation model are suitable and effective for Grid environments.
Distributed k-Coverage Verification Algorithm Based on Localized Distance Information in WSNs
Authors: Xia Zhang, Cheng Wang
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

It is essential to equip the sensor nodes with simple and efficient coverage boundary detection mechanisms for ensuring the network reliability and providing the required quality of service. The existing coverage boundary detection solutions require accurate knowledge of the sensors locations,which cannot be easily obtained, or they cannot provide guarantees on the coverage quality. Therefore, we propose a distributed algorithm for individual sensor nodes to identify whether they are on the coverage boundary, by using only localized distance information. Furthermore, we extend the algorithm to k-coverage boundary detection scheme. We show the correctness and efficiency of our algorithm by theoretical proofs.
The Strategy of Description and Computation for User's QoS Preference
Authors: Quan Liang, Yuanzhuo Wang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

In order to satisfy users’ individual QoS requirements, the paper studied the QoS attributes of grid service, and put forward several ways to describe QoS preference information: ordering vector, AHP judgement matrix and language evaluation collection, and gave out the concrete methods of conversion and compulation. At the same time, a method of selecting the relatively optimal service was presented which can reflect users’ QoS preference. The numerical example analysis indicates that the method for user QoS preference is conscientiously feasible.
Predicting K/S Value of the Reactive Dyes Based on RBF Neural Network
Authors: HuiYu Jiang, Min Dong, Wei Li
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

The traditional determination method of K/S value is testing the CIEL*a*b* value of each dyeing fabric fistly by the color chromatic aberration SC–80, and then, based on the CIEL*a*b* value, they calculate the K/S value scoping 10nm within 400nm-700nm the visible region. These are finished with the help of the software Hyper Choshoku-Senka TX.The RBF neural network is used in this paper to estimate the K/S value. The correlation coefficient reaches 1.000 between the estimated value and tested one. Prediction error's biggest absolute value is 0.004, the rest is under 0.002 It shows the feasibility of the artificial neural network applied to the reactive dyes dyeing. It is a good forecast mode of K/S value ofthe reactive dyes.
Forecasting Sedimentation of constructions Based on BP Network
Authors: Ting-chen Jiang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

If sedimentation of constructions exceeds the prescribed limits, it would give rise to huge losses forcommunity and people, so it issignificant to establish the effective and practical deformation forecasting model for the safe operation and economic development. With the unique non-linear, non-convexity, non-locality, non-steadiness, adaptability and powerful ability of calculation and information process, BP (Back Propagation)neural network can adapt to the complicated and changeable dynamic characteristics of buildings,that has broad application foreground in deformation prediction. In this paper, on the basis of deformation observation data, a basic algorithm about establishing BP neural network model in sedimentation prediction is presented.at the same time, analysis of examples are given so that the application of neural network for deformation forecasting is studiedcomprehensively andsystemically, the results show that neural network is very effective forSedimentation prediction and can serve society and people in the future.
Recognition and Translation of Hand Gestures to Urdu Alphabets Using a Geometrical Classification
Authors: Huma Tauseef, Muhammad Abuzar Fahiem, Saima Farhan
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

Recognition of hand gestures associated with different alphabets is a very important research area. The persons with vocal and hearing disabilities may benefit a lot from this research. The communication gap between these and normal persons can be filled by providing an aid in the form of a computerized translation of different hand gestures. In this paper, we have developed a recognition system to translate hand gestures into Urdu alphabets. We have formulated a comprehensive classification scheme which is core to this recognition system. The accuracy rate of our approach is 97.4% which is better than the previous approaches.
A unified model for detecting efficient and inefficient outliers in data envelopment analysis
Authors: Wen-Chih Chen, Andrew L. Johnson
Venue: Computers and Operations Research (2010)

Data envelopment analysis (DEA) uses extreme observations to identify superior performance, making it vulnerable to outliers. This paper develops a unified model to identify both efficient and inefficient outliers in DEA. Finding both types is important since many post analyses, after measuring efficiency, depend on the entire distribution of efficiency estimates. Thus, outliers that are distinguished by poor performance can significantly alter the results. Besides allowing the identification of outliers, the method described is consistent with a relaxed set of DEA axioms. Several examples demonstrate the need for identifying both efficient and inefficient outliers and the effectiveness of the proposed method. Applications of the model reveal that observations with low efficiency estimates are not necessarily outliers. In addition, a strategy to accelerate the computation is proposed that can apply to influential observation detection.
Comparison of Perceptual Grouping Criteria within an Integrated Hierarchical Framework
Authors: R. Marfil, A. Bandera
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

The efficiency of a pyramid segmentation approach mainly depends on the graph selected to encode the information within each pyramid level, on the reduction or decimation scheme used to build one graph from the graph below, and on the criteria employed to define if two adjacent regions are similar or not. This paper evaluates three pairwise comparison functions for perceptual grouping into a generic framework for image perceptual segmentation. This framework integrates the low---level definition of segmentation with a domain---independent perceptual grouping. The performance of the framework using the different comparison functions has been quantitatively evaluated with respect to ground-truth segmentation data using the Berkeley Segmentation Dataset and Benchmark providing satisfactory scores.
GLADDER: combining gesture and geometric sketch recognition
Authors: Paul Corey, Tracy Hammond
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Sketch recognition systems usually recognize strokes either as stylistic gestures or geometric shapes. Both techniques have their advantages. This paper presents a method for integrating gesture-based and geometric recognition techniques, significantly outperforming either technique on its own.
Arterial pulse wave decomposition by independent component analysis
Authors: Laila Gbaoui, Eugenijus Kaniusas
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

The analysis of the arterial pulse wave has become an important tool in the assessment of the cardiovascular activity and arterial properties. Most approaches using only the pressure or velocity pulse wave evaluate pulse parameters using the first or higher derivatives of the pulse wave. These methods are simple but limited in case the waves are noisy, weak, or their diastolic peak is damped. As an alternative, the wave intensity analysis provides a simple way to separate the forward and backward waves to asses pulse parameters but requires the simultaneous measurement of pressure and blood flow waves, which is not trivial. Thus we propose a more strategic approach facilitating the independence of the forward and reflected waves in order to increase the reliability of the extracted pulse parameters. The approach uses non-linear embedding of the photoplethys-mographical pulse wave within the scope of the independent component analysis to extract the hidden independent sources in the waveform. The results yield forward and reflected waves from single channel recording demonstrating the adequacy of the approach.
On the Stein phenomenon under divergence loss and an unknown variance-covariance matrix
Authors: Malay Ghosh, Victor Mergel
Venue: Journal of Multivariate Analysis (2009)

The paper develops a general class of shrinkage estimators for estimating the normal mean, which dominates the sample mean in three or higher dimensions under a general divergence loss. In the process, the earlier works of James and Stein [11] and Efron and Morris [5] are generalized considerably.
Generating synthetic children's acoustic models from adult models
Authors: Andreas Hagen, Bryan Pellom, Kadri Hacioglu
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

This work focuses on generating children's HMM-based acoustic models for speech recognition from adult acoustic models. Collecting children's speech data is more costly compared to adult's speech. The patent-pending method developed in this work requires only adult data to estimate synthetic children's acoustic models in any language and works as follows: For a new language where only adult data is available, an adult male and an adult female model is trained. A linear transformation from each male HMM mean vector to its closest female mean vector is estimated. This transform is then scaled to a certain power and applied to the female model to obtain a synthetic children's model. In a pronunciation verification task the method yields 19% and 3.7% relative improvement on native English and Spanish children's data, respectively, compared to the best adult model. For Spanish data, the new model outperforms the available real children's data based model by 13% relative.
Computing parallelism in discourse
Authors: Claire Gardent, Michael Kohlhase
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Although much has been said about parallelism in discourse, a formal, computational theory of parallelism structure is still outstanding. In this paper, we present a theory which given two parallel utterances predicts which are the parallel elements. The theory consists of a sorted, higher-order abductive calculus and we show that it reconciles the insights of discourse theories of parallelism with those of Higher-Order Unification approaches to discourse semantics, there by providing a natural framework in which to capture the effect of parallelism on discourse semantics.
An Implementation Approach for XQuery Based on Lazy Evaluation
Authors: Peng Li, Husheng Liao, Hongli Yang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In order to accelerate the execution of XQuery, this paper introduces an evaluator named as XML Query Lazy Evaluator (XQLE), which uses lazy evaluation optimization technique. The input language is Functional XML Query Language (FXQL) that is a functional language with concise form. For data model, XQLE uses generalized list with the ability to hold closure and XML node to support lazy calculation of list node. Under lazy mode, the overhead of acquiring the data that has no relationship to the final result of calculation can be eliminated. Finally, we use a lot of example programs to show the lazy evaluator has better performance compared with eager evaluator in the average execution speed.
Discrete and continuous models of the dynamics of pelagic fish: Application to the capelin
Authors: Alethea B. T. Barbaro, Kirk Taylor, Peterson F. Trethewey, Lamia Youseff, Björn Birnir
Venue: Mathematics and Computers in Simulation (2009)

In this paper, we study simulations of the schooling and swarming behavior of a mathematical model for the motion of pelagic fish. We use a derivative of a discrete model of interacting particles originated by Vicsek and Czirok et al. [A. Czirok, T. Vicsek, Collective behavior of interacting self-propelled particles, Physica A 281 (2000) 17-29; A. Czirok, H. Stanley, T. Vicsek, Spontaneously ordered motion of self-propelled particles, Journal of Physics A: Mathematical General 30 (1997) 1375-1385; T. Vicsek, A. Czirok, E. Ben-Jacob, I. Cohen, O. Shochet, Novel type of phase transition in a system of self-driven particles, Physical Review Letters 75 (6) (1995) 1226-1229; T. Vicsek, A. Czirok, I. Farkas, D. Helbing, Application of statistical mechanics to collective motion in biology, Physica A 274 (1999) 182-189]. Recently, a system of ODEs was derived from this model [B. Birnir, An ODE model of the motion of pelagic fish, Journal of Statistical Physics 128 (1/2) (2007) 535-568], and using these ODEs, we find transitory and long-term behavior of the discrete system. In particular, we numerically find stationary, migratory, and circling behavior in both the discrete and the ODE model and two types of swarming behavior in the discrete model. The migratory solutions are numerically stable and the circling solutions are metastable. We find a stable circulating ring solution of the discrete system where the fish travel in opposite directions within an annulus. We also find the origin of noise-driven swarming when repulsion and attraction are absent and the fish interact solely via orientation.
Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations
Authors: Diwas S. Kc, Christian Terwiesch
Venue: Management Science (2009)

Much of prior work in the area of service operations management has assumed service rates to be exogenous to the level of load on the system. Using operational data from patient transport services and cardiothoracic surgery---two vastly different health-care delivery services---we show that the processing speed of service workers is influenced by the system load. We find that workers accelerate the service rate as load increases. In particular, a 10% increase in load reduces length of stay by two days for cardiothoracic surgery patients, whereas a 20% increase in the load for patient transporters reduces the transport time by 30 seconds. Moreover, we show that such acceleration may not be sustainable. Long periods of increased load (overwork) have the effect of decreasing the service rate. In cardiothoracic surgery, an increase in overwork by 1% increases length of stay by six hours. Consistent with prior studies in the medical literature, we also find that overwork is associated with a reduction in quality of care in cardiothoracic surgery---an increase in overwork by 10% is associated with an increase in likelihood of mortality by 2%. We also find that load is associated with an early discharge of patients, which is in turn correlated with a small increase in mortality rate.
Power Ration Effect on Limited Power Generation Costs
Authors: Anant Oonsivilai, Kenedy A. Greyson
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

While most researches in developed countries are based on power congestion and transmission lines of more capacities, electric power supply companies inmost developing countries still have limited electric power generating plants. Limited resources such as:water, oil, gas, coal, nuclear, etc., are the causes of power ration in these countries. In this paper,operating costs of a thermal plant operating at rationing base is analyzed. Using optimal active power dispatch algorithm, the effect of power reschedule at different location on generation costs is obtained and analyzed. Fuel cost and transmission losses are considered. It is observed that, at some location,rationing affect the electric company economy due to the high loss and load under rationing, time of rationing and the uneconomical generating cost. This research contribution is to assist in economical projection for the electric companies and decide the location and time of the rationing. Results presented are based on IEEE 14-bus testing system, IEEE 30-bus testing power system.
Using uncertain chemical and thermal data to predict product quality in a casting process
Authors: Catarina Dudas, Henrik Boström
Venue: Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009)

Process and casting data from different sources have been collected and merged for the purpose of predicting, and determining what factors affect, the quality of cast products in a foundry. One problem is that the measurements cannot be directly aligned, since they are collected at different points in time, and instead they have to be approximated for specific time points, hence introducing uncertainty. An approach for addressing this problem is investigated, where uncertain numeric feature values are represented by intervals and random forests are extended to handle such intervals. A preliminary experiment shows that the suggested way of forming the intervals, together with the extension of random forests, results in higher predictive performance compared to using single (expected) values for the uncertain features together with standard random forests.
UCD-FC: deducing semantic relations using WordNet senses that occur frequently in a database of noun-noun compounds
Authors: Fintan J. Costello
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper describes a system for classifying semantic relations among nominals, as in SemEval task 4. This system uses a corpus of 2,500 compounds annotated with WordNet senses and covering 139 different semantic relations. Given a set of nominal pairs for training, as provided in the SemEval task 4 training data, this system constructs for each training pair a set of features made up of relations and WordNet sense pairs which occurred with those nominals in the corpus. A Naive Bayes learning algorithm learns associations between these features and relation membership categories. The identification of relations among nominals in test items takes place on the basis of these associations.
Road Network Analysis and Evaluation of Huizhou City Based on Space Syntax
Authors: Zheng-yu Duan, Quan Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

“Shan-shui City” is the city with Chinese characteristics, in brief, it was built in the area with mountains and rivers, and has good natural environment. Du to geographical conditions, the road network of Shan-shui City has serious structural defects. With rapid development of motorization and urbanization, the contradiction between traffic supply and demand becomes increasingly conspicuous. Space syntax is a social logic language, based on graph theory and GIS. It is a quantitative analysis method, and provides a new tool for urban road network analysis. In this paper, we analyze the road network of Huizhou city with the method of space syntax, through 2 topics: Traffic Passages of Clustered Cities, River Crossing Passages. Space syntax has been used to study the actuality of road network, and evaluate the reconstruction proposal. We hope it can provide a new method for transportation planning.
Car or Public Transport--Two Worlds
Authors: Hannah Bast
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

There are two kinds of people: those who travel by car, and those who use public transport. The topic of this article is to show that the algorithmic problem of computing the fastest way to get from A to B is also surprisingly different on road networks than on public transportation networks.On road networks, even very large ones like that of the whole of Western Europe, the shortest path from a given source to a given target can be computed in just a few microseconds. Lots of interesting speed-up techniques have been developed to this end, and we will give an overview over the most important ones.Public transportation networks can be modeled as graphs just like road networks, and most algorithms designed for road networks can be applied for public transportation networks as well. They just happen to perform not nearly as well, and to date we do not know how to route similarly fast on large public transportation networks as we can on large road networks.The reasons for this are interesting and non-obvious, and it took us a long time to fully comprehend them. Once understood, they are relatively easy to explain, however, and that is what we want to do in this article. Oh, and by the way, happy birthday, Kurt!