ppxscal/embedding_network huggingface dataset:
Experiment on Dynamic Release of Fluorine from Sediment in Yangshapao Reservoir of Western Jilin Province
Authors: Liang Xiujuan, Xiao Changlai, Feng Bo, Du Chao, Fang Zhang, Deng Songlin, Xu Xiaoling
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The specific studies are carried out according to the problem of the high concentration of fluorine in Yangshapao Lake, which is a most important multi-purpose reservoir of Diversion Project from Nenjiang River to Baicheng City in Western Jilin Province. After the diversion is actualized, the release of fluorine from the sediment may influence the water quality in the reservoir. Based on the problem mentioned above, dynamic release experiment is adopted to analyze the release concentration of fluorine changing with time, which found out that the release law of fluorine in sediment is according with logarithm distribution. The dynamic release equation and chemical reaction rate equation of fluorine in sediment are also established.
Semi-supervised sequence modeling with syntactic topic models
Authors: Wei Li, Andrew McCallum
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Although there has been significant previous work on semi-supervised learning for classification, there has been relatively little in sequence modeling. This paper presents an approach that leverages recent work in manifold-learning on sequences to discover word clusters from language data, including both syntactic classes and semantic topics. From unlabeled data we form a smooth. low-dimensional feature space, where each word token is projected based on its underlying role as a function or content word. We then use this projection as additional input features to a linear-chain conditional random field trained on limited labeled training data. On standard part-of-speech tagging and Chinese word segmentation data sets we show as much as 14% error reduction due to the unlabeled data, and also statistically-significant improvements over a related semi-supervised sequence tagging method due to Miller et al.
Extending the knowledge compilation map: Krom, Horn, affine and beyond
Authors: Hélène Fargier, Pierre Marquis
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

We extend the knowledge compilation map introduced by Darwiche and Marquis with three influential propositional fragments, the Krom CNF one (also known as the bijunctive fragment), the Hom CNF fragment and the affine fragment (also known as the biconditional fragment) as well as seven additional languages based on them, and composed respectively of Krom or Hom CNF formulas, renamable Hom CNF formulas, disjunctions of Krom CNF formulas, disjunctions of Hom CNF formulas, disjunctions of Krom or Hom CNF formulas, disjunctions of renamable Hom CNF formulas, and disjunction of fine formulas. Each fragment is evaluated w.r.t. several criteria, including the complexity of basic quaries and transformation, and its spatial efficiency is also analysed.
Cortex and memory: Emergence of a new paradigm
Authors: Joaquín M. Fuster
Venue: Journal of Cognitive Neuroscience (2009)

Converging evidence from humans and nonhuman primates is obliging us to abandon conventional models in favor of a radically different, distributed-network paradigm of cortical memory. Central to the new paradigm is the concept of memory network or cognit-that is, a memory or an item of knowledge defined by a pattern of connections between neuron populations associated by experience. Cognits are hierarchically organized in terms of semantic abstraction and complexity. Complex cognits link neurons in noncontiguous cortical areas of prefrontal and posterior association cortex. Cognits overlap and interconnect profusely, even across hierarchical levels (heterarchically), whereby a neuron can be part of many memory networks and thus many memories or items of knowledge.
Short text authorship attribution via sequence kernels, Markov chains and author unmasking: an investigation
Authors: Conrad Sanderson, Simon Guenter
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

We present an investigation of recently proposed character and word sequence kernels for the task of authorship attribution based on relatively short texts. Performance is compared with two corresponding probabilistic approaches based on Markov chains. Several configurations of the sequence kernels are studied on a relatively large dataset (50 authors), where each author covered several topics. Utilising Moffat smoothing, the two probabilistic approaches obtain similar performance, which in turn is comparable to that of character sequence kernels and is better than that of word sequence kernels. The results further suggest that when using a realistic setup that takes into account the case of texts which are not written by any hypothesised authors, the amount of training material has more influence on discrimination performance than the amount of test material. Moreover, we show that the recently proposed author unmasking approach is less useful when dealing with short texts.
Research on the Human-Water Relationship in the Middle Reaches of Yangtze River
Authors: Huang Jianwu, Wu Yijin, Qin Chaoqian, Helena Ndakeva, Tian Yajing
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

This article first elaborates the evolution of human-water relationship in the middle reaches of Yangtze River. In the ancient times, natural habitats of the human species were centered around large water and grass rich areas. People maintained an orderly and complete relationship with the water-environment, with the progression of time agricultural societies, begun to exploit the Two-Lake Plains (Hunan and Hubei plains), they constructed irrigation projects and re-constructed the water environment. In Ming and Qing Dynasties, reclamation from lakes caused deterioration of human-water relationship, by the time china was declared a sovereign government, China’s human-water relationship had became comprehensively deteriorated. further more, this paper also analyzes the influence of human activities on the water environment focusing on aspects of the changes within the lakes system, the evolution of hydrological characteristics, the variation of the frequency of flood disaster and the deterioration of water quality in the middle reach of Yangtze River. The result showed that river systems of Yunmeng marsh, Dongting Lake, Poyang Lake, Jingjiang river have undergone profound changes; the runoff and the sediment content exhibited a decreasing trend in recent years. The frequency of flood disaster has also been on the increase in recent decades. The rapid development of agriculture and other industries accelerated the ecological environmental destruction and the water quality. Finally, the paper discusses the water environmental variation and its effects on human social culture, custom, architecture, settlement vicissitude as well as the agriculture and the influence of flood disaster intensification. The paper demonstrates that water is one of the necessary driving forces for social development.
A real-time publish/subscribe driver alert system for accident avoidance due to red light running (Poster)
Authors: Deepti Thopte, Tina Devkota, Aniruddha Gokhale
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

This poster presents Intelligent Traffic Light (ITL), which is a cyber physical system that combines information technology (e.g., real-time publish/subscribe semantics) and communications technology (e.g., mobility and wireless) with the transportation infrastructure (e.g., vehicles, traffic lights and road-side units) to address the red light running incidents. ITL behaves as the publisher and vehicles subscribe to warning messages published for them. ITL estimates when a traffic light will change to red, and warns drivers of approaching vehicles about when and how much to slow down to avoid red light running. ITL can account for road conditions, which increases its usability in challenging weather conditions.
Protecting quantum information with entanglement and noisy optical modes
Authors: Mark M. Wilde, Todd A. Brun
Venue: Quantum Information Processing (2009)

We incorporate active and passive quantum error-correcting techniques to protect a set of optical information modes of a continuous-variable quantum information system. Our method uses ancilla modes, entangled modes, and gauge modes (modes in a mixed state) to help correct errors on a set of information modes. A linear-optical encoding circuit consisting of offline squeezers, passive optical devices, feedforward control, conditional modulation, and homodyne measurements performs the encoding. The result is that we extend the entanglement-assisted operator stabilizer formalism for discrete variables to continuous-variable quantum information processing.
Design of a window comparator with adaptive error threshold for online testing applications
Authors: Amit Laknaur, Rui Xiao, Sai Durbha, Haibo Wang
Venue: Microelectronics Journal (2009)

This paper presents a novel window comparator circuit whose error threshold adjusts adaptively with respect to its input signal levels. Advantages of adaptive error thresholds over constant or relative error thresholds in analog testing applications are discussed. Analytical equations for guiding the design of the comparator circuitry are derived. The proposed comparator circuit has been designed and fabricated using a CMOS 0.18@mm technology. Measurement results of the fabricated chip are presented.
Total Variation Processing of Images with Poisson Statistics
Authors: Alex Sawatzky, Christoph Brune, Jahn Müller, Martin Burger
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Obtaining the structures with sharp edges can also be a prerequisite for further processing, e.g. segmentation of objects.A variety of approaches exists in the case of Gaussian noise, but only a few in the Poisson case. We propose some total variation (TV) based regularization techniques adapted to the case of Poisson data, which we derive from approximations of logarithmic a-posteriori probabilities. In order to guarantee sharp edges we avoid the smoothing of the total variation and use a dual approach for the numerical solution. We illustrate and test the feasibility of our approaches for data in positron emission tomography, namely reconstructions of cardiac structures with 18F-FDG and H$_2 \, ^{15}$O tracers, respectively.
An stable online clustering fuzzy neural network for nonlinear system identification
Authors: Jos&#x00e9; de Jes&#x00fa;s Rubio, Jaime Pacheco
Venue: Neural Computing and Applications (2009)

In this paper, we propose a online clustering fuzzy neural network. The proposed neural fuzzy network uses the online clustering to train the structure, the gradient to train the parameters of the hidden layer, and the Kalman filter algorithm to train the parameters of the output layer. In our algorithm, learning structure and parameter learning are updated at the same time, we do not make difference in structure learning and parameter learning. The center of each rule is updated to obtain the center is near to the incoming data in each iteration. In this way, it does not need to generate a new rule in each iteration, i.e., it neither generates many rules nor need to prune the rules. We prove the stability of the algorithm.
Quantitative Security Risk Assessment and Management for Railway Transportation Infrastructures
Authors: Francesco Flammini, Andrea Gaglione, Nicola Mazzocca, Concetta Pragliola
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

Scientists have been long investigating procedures, models and tools for the risk analysis in several domains, from economics to computer networks. This paper presents a quantitative method and a tool for the security risk assessment and management specifically tailored to the context of railway transportation systems, which are exposed to threats ranging from vandalism to terrorism. The method is based on a reference mathematical model and it is supported by a specifically developed tool. The tool allows for the management of data, including attributes of attack scenarios and effectiveness of protection mechanisms, and the computation of results, including risk and cost/benefit indices. The main focus is on the design of physical protection systems, but the analysis can be extended to logical threats as well. The cost/benefit analysis allows for the evaluation of the return on investment, which is a nowadays important issue to be addressed by risk analysts.
Realistic Depth Blur for Images with Range Data
Authors: Benjamin Huhle, Timo Schairer, Philipp Jenke, Wolfgang Straßer
Venue: Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging (2009)

We present a system that allows for changing the major camera parameters after the acquisition of an image. Using the high dynamic range composition technique and additional range information captured with a small and low-cost time-of-flight camera, our setup enables us to set the main parameters of a virtual camera system and to compute the resulting image. Hence, the aperture size and shape, exposure time, as well as the focus can be changed in a postprocessing step. Since the depth-of-field computation is sensitive to proper range data, it is essential to process the color and depth data in an integrated manner. We use a non-local filtering approach to denoise and upsample the range data. The same technique is used to infer missing information regarding depth and color which occur due to the parallax between both cameras as well as due to the lens camera model that we use to simulate the depth of field in a physically correct way.
Association Rules Algorithm Research in Optical Warning System
Authors: Hu Chaoju, Peng Min
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Mining association rules with multiple minimum supports is an important research aspect of data mining. In this paper we propose a database partition method to mine the frequent item sets, and use MIS-tree to store the crucial information about frequent patterns. We use the CFP-growth algorithm to mine local frequent patterns and insert them into the global frequent pattern. The experiment on OASN shows that the method is effective to predict the optical warning level.
Fashion Support from Clothes with Characteristics
Authors: Yuri Yonezawa, Yoshio Nakatani
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

Fashion can be a source of daily enjoyment, as well as source of anxiety, in our lives. In this paper, we propose a new system for supporting a person's fashion coordination. This system produces pleasant coordination between a person and his or her clothes when the person stands in front of the closet each morning and picks out the day's attire. Each item of clothing has its corresponding software agent with a specific characteristic decided by color, based on psychological findings. The scenario is as follows: First, the user enters the total fashion image for the desired fashion profile for the day, such as "today's image is red." When the user goes to the closet, clothing that is red or verging on red start to appeal. The user hears messages such as "Choose me because you had a good day last time you chose me," and "No, choose me because it is hot today." An Integrated Circuit (IC) tag is put on each hanger, and the chosen article of clothing is identified by the IC tag reader affixed to user's finger. The episodic database and the database of basic fashion knowledge are connected to each as a knowledge source for conversation.
A Neural Oscillation Model for Contour Separation in Color Images
Authors: Yu Ma, Xiaodong Gu, Yuanyuan Wang
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

A novel neural oscillation model is proposed to perform the contour detection and separation for color images. The model improves the prototype of relaxation oscillation and combines four kinds of image features as the external stimulation, in order to control the oscillation. Experimental results show that the contours of different objects can be detected by oscillation and separated by desynchronization. This model may help to promote the investigation on the mechanism of the neural system.
The Effect of Brand on the Evaluation of Websites
Authors: Antonella Angeli, Jan Hartmann, Alistair Sutcliffe
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

The effect of brand on consumer attitudes towards real and virtual goods is largely documented in consumer psychology and marketing. There is an obvious link between the design of a website and its brand. Yet, this effect has attracted little attention from the HCI community. This paper presents empirical evidence showing that brand attitude influences the evaluation of websites. The effect was reliable across different measures: people holding better attitudes were more positive in the evaluation of aesthetics, pleasure and usability. A sample of students (N=145) with a background in HCI was tested, suggesting that brand may influence the output of expert evaluators. The study provides support to the proposition of UX as a contextual-dependent response to the interaction with computing systems and has important implications for the design and evaluation of websites which are discussed in the conclusion.
Based Mobile Agent Transaction Authentication Scheme
Authors: Zhiming Zhang, Min Yu, Minghe Huang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

With Mobile Agent is becoming common in a variety of applications on Electronic Commerce, How to protect the transaction security is the key technology of based Agent Electronic Commerce System. In this paper, a Mobile Agent security transaction Authentication Scheme is proposed, the Scheme effectively protects the Mobile Agent transaction security by using bilinear pairings, hash function and Exclusive Or operation. Comparing with previous security schemes for Mobile Agent, this scheme provides more security and improves effectively in computing and memory efficiency.
Experimental Study on Mobile RFID Performance
Authors: Zhong Ren, Chiu C. Tan, Dong Wang, Qun Li
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

An increasing number of applications use RFID in their design, but there is a lack of understanding of how mobility affects RFID performance in these applications. Unlike static RFID experiments, mobile RFID studies require more expensive equipment that are unavailable to most researchers. In this paper, we conduct machine-aided experiments to study the effects of mobility on RFID. Our results show that up to 50 RFID tags moving at speeds up to 2 m/s can be reliably read.
A Regulatory-Based Approach to Safety Analysis of Unmanned Aircraft Systems
Authors: James T. Luxhøj, Ahmet Öztekin
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

Unmanned Aircraft Systems (UAS), the new frontier in civil aviation, add another dimension to the ever-increasing complexity of the current National Airspace System (NAS) in the United States. The future inclusion of private and commercial operations of the UAS into the NAS, unavoidably, raises safety concerns. As the NAS becomes increasingly more complex and constrained, the associated hazard and safety risk modeling must also mature in sophistication. Thus, there is a need for advanced studies focusing on risk-based system safety analysis of emergent UAS operations. This paper presents a regulatory-based integrated approach to system safety and risk analysis of the UAS operations and their interaction with the current NAS and the future Next Generation (NextGen) Airspace.
Neurocognitive Approach to Clustering of PubMed Query Results
Authors: Paweł Matykiewicz, Włodzisław Duch, Paul M. Zender, Keith A. Crutcher, John P. Pestian
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Internet literature queries return a long lists of citations, ordered according to their relevance or date. Query results may also be represented using Visual Language that takes as input a small set of semantically related concepts present in the citations. First experiments with such visualization have been done using PubMed neuronal plasticity citations with manually created semantic graphs. Here neurocognitive inspirations are used to create similar semantic graphs in an automated fashion. This way a long list of citations is changed to small semantic graphs that allow semi-automated query refinement and literature based discovery.
Research on Emergency Knowledge Retrieval Mechanism Based on Domain Ontology
Authors: Huang Weidong, Zhu Hengmin, Wang Chuanlei, Shen Yu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

In this paper, on the basis of constructing domain ontology database and designing meta-search engine, and relying on the reasoning mechanism of domain ontology and abundant internet sources, we propose the emergency domain ontology-based intelligent meta-search system and carried out the example verification. The results show that the model has great practical significance. The introduction of meta-search engine into the domain source retrieval expands the coverage of the search, enhances the recall ratio of source retrieval and improves the retrieval accuracy and intelligent level of search engine through constructing domain ontology database.
Some restriction tests in a new class of regression models for proportions
Authors: Tatiane F. N. Melo, Klaus L. P. Vasconcellos, Artur J. Lemonte
Venue: Computational Statistics Data Analysis (2009)

The main purpose of this work is to study the behaviour of Skovgaard's [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian Journal of Statistics 28, 3-32] adjusted likelihood ratio statistic in testing simple hypothesis in a new class of regression models proposed here. The proposed class of regression models considers Dirichlet distributed observations, and the parameters that index the Dirichlet distributions are related to covariates and unknown regression coefficients. This class is useful for modelling data consisting of multivariate positive observations summing to one and generalizes the beta regression model described in Vasconcellos and Cribari-Neto [Vasconcellos, K.L.P., Cribari-Neto, F., 2005. Improved maximum likelihood estimation in a new class of beta regression models. Brazilian Journal of Probability and Statistics 19, 13-31]. We show that, for our model, Skovgaard's adjusted likelihood ratio statistics have a simple compact form that can be easily implemented in standard statistical software. The adjusted statistic is approximately chi-squared distributed with a high degree of accuracy. Some numerical simulations show that the modified test is more reliable in finite samples than the usual likelihood ratio procedure. An empirical application is also presented and discussed.