ppxscal/embedding_network huggingface dataset:
The Mathematical Model of the Endmembers in Hyperspectral Data
Authors: Dongmei Bi, Lijun Zhao, Yanjun Gong
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Hyperspectral images analysis play important role in optical spectrum analysis field. The unmixing of the endmembers is very important to hyperspectral images analysis. We propose relationship between endmembers and their mixed pixel in matrix equation. The mathematical model of the endmembers is derived on the basis of convex geometry. Image endmembers can be derived from hyperspectral data set on the basis of the mathematical model, which is called the convex model of endmembers. The mathematical model is tested by a hyperspectral image. The endmembers can be derived from hyperspectral data set by the convex model of endmembers.
DAREonline: A Web-Based Domain Engineering Tool
Authors: Raimundo F. Santos, William B. Frakes
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

DAREonline is a web-based tool for domain engineering. It supports the DARE framework in a centralized platform-independent environment. Our approach leverages concepts of Service-Oriented Architecture (SOA) to aggregate data and functionality from diverse sources that can be helpful in domain engineering. In this paper, we describe DAREonline's1 architecture and implementation, and its use in a graduate course on software design and quality. Initial results indicate that DAREonline can be a valuable resource for domain analysts and can achieve acceptance at similar levels to DARE COTS.
A Method for Rapid Feature Extraction Based on KMSE
Authors: Qi Zhu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Kernel minimum squared error (KMSE) is a mathematically tractable feature extraction method in comparison with other nonlinear methods. However, as a kernel method, it also suffers from the drawback that the classification efficiency decreases as the size of the training samples increases. In order to improve the KMSE-based classification efficiency, we propose to approximate the discriminant vector in the feature space using a certain linear combination of some samples selected from the set of the training samples. Based on this idea, we develop an algorithm to determine the samples, and a linear combination of which can approximately express the genuine discriminant vector. Experiments on benchmark dataset illustrate the effectiveness of the improvements.
DYNAMIK
Authors: Stefan Jaeger, Qingfeng Song, Su-Shing Chen
Venue: Bioinformatics (2009)

The emergence of new microscopy techniques in combination with the increasing resource of bioimaging data has given fresh impetus to utilizing image processing methods for studying biological processes. Cell tracking studies in particular, which are important for a wide range of biological processes such as embryonic development or the immune system, have recently become the focus of attention. These studies typically produce large volumes of data that are hard to investigate manually and therefore call for an automated approach. Due to the large variety of biological cells and the inhomogeneity of applications, however, there exists no widely accepted method or system for cell tracking until today. In this article, we present our publicly available DYNAMIK software environment that allows users to compute a suit of cell features and plot the trajectory of multiple cells over a sequence of frames. Using chemotaxis and Ras pathways as an example, we show how users can employ our software to compute statistics about cell motility and other cell information, and how to evaluate their test series based on the data computed. We see that DYNAMIK's segmentation and tracking compares favorably with the output produced by other software packages. Contact: jaeger@picb.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.
From data to knowledge: The interaction between data management systems in educational institutions and the delivery of quality education
Authors: Hilary Tolley, Boaz Shulruf
Venue: Computers Education (2009)

No school is an island; it is a part of a continuum or a pipeline of institutions which together form an educational pipeline through which groups of students pass. To turn a body of data into useful information for knowledge-based decision-making at any level, data must be collected, organised, analysed and reflected upon. The purpose of this paper is to discuss how schools and other educational institutions can not only collect better data but learn how to transform that data so that the information held within can be effectively shared among all stakeholders. This process will help to ensure that the school and the entire education system provide a more seamless and effective educational pipeline for students, and ultimately improve the quality of education delivered in the country as a whole.
Demonstration of PLOW: a dialogue system for one-shot task learning
Authors: James Allen, Nathanael Chambers, George Ferguson, Lucian Galescu, Hyuckchul Jung, Mary Swift, William Taysom
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

We describe a system that can learn new procedure models effectively from one demonstration by the user. Previous work to learn tasks through observing a demonstration (e.g., Lent & Laird, 2001) has required observing many examples of the same task. One-shot learning of tasks presents a significant challenge because the observed sequence is inherently incomplete -- the user only performs the steps required for the current situation. Furthermore, their decision-making processes, which reflect the control structures in the procedure, are not revealed.
Study and Safety Analysis on UCONonA Model
Authors: Zhai Zhigang, Wang Jiandong, Mao Yuguang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

As the next generation access control, usage control models received serious academic attention and had been extended in much direction. But, as a fundamental problem, the safety analysis of UCON has not been explored enough. This paper completes the safety analysis of authorization UCON by analysis the safety problem of ongoing authorizations usage control models. First, presents a formal UCONonA model. Then, analysis the safety problem of a general UCONonA model is undecidable. Finally, prove the safety problem of an UCONonA system is decidable with finite attribute domain and no creating actions in the scheme.
Studies Based on the Motion Environment Sensation Aspect's Dynamic Service Combination
Authors: Zhang Yanhong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

The distributional net constructs software's network environment to be day by day complex, system's demand analysis, the flow design, the software construction, the system development and the quality assurance came under the distributional external environment influence, information system's dynamic change have led alternately the software development entire process the uncertainty attribute category. Distributional to external environment's visualization, the motion environment sensation software main body's substantialization, the dynamic auto-adapted operational mechanism's predictability set the high request alternately. Under the hierarchical motion environment sensation network construction theory influence, how to carry on the visualization the dynamic service combination, realizes the cross domain level, the enterprise function integration, enhancement system service middleware auto-adapted ability and the reusability becomes the software development technological development the important advancement.
COD: online temporal clustering for outbreak detection
Authors: Tomáš Šingliar, Denver H. Dash
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

We present Cluster Onset Detection (COD), a novel algorithm to aid in detection of epidemic outbreaks. COD employs unsupervised learning techniques in an online setting to partition the population into subgroups, thus increasing the ability to make a detection over the population as a whole by decreasing the signal-to-noise ratio. The method is adaptive and able to alter its clustering in real-time without the need for detailed background knowledge of the population. COD attempts to detect a cluster made up primarily of infected hosts. We argue that this technique is largely complementary to the existing methods for outbreak detection and can generally be combined with one or more of them. We show empirical results applying COD to the problem of detecting a worm attack on a system of networked computers, and show that thIs method results in approximately 40% lower infection rate at a false positive rate of 1 per week than the best previously reported results on this data set achieved using an HMM model customized for the outbreak detection task.
Research on Tourism Environmental Carrying Capacity of ChongMing Island
Authors: Liu Shi-dong, Sun Rui-hong, Gao Jun
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

The importance for studying the influences to the environment by tourism activities is noted by more and more people. The researching method changes from the original qualitative description to quantitative description. Taken Shanghai ChongMing Island as an example, the tourism environmental carrying capacity of this island is studied by combining with the its unique island characteristics. The factors which restrict the development of tourism in ChongMing Island are found out, which provides basis for the future tourism development activities in this island. Through large quantities of calculations, the factors which restrict the development of tourism industry in ChongMing Island within the regional scale are solid wastes, sightseeing carrying capacity of QianWei Village in golden weeks, hotel reception in peak season of tourism, and traffic outside the island. By referencing these restricting factors, more pertinence management scheme can be made for the environmental management of ChongMing Island in the future.
UA-ZBSA: a headline emotion classification through web information
Authors: Zornitsa Kozareva, Borja Navarro, Sonia Vázquez, Andrés Montoyo
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper presents a headline emotion classification approach based on frequency and co-occurrence information collected from the World Wide Web. The content words of a headline (nouns, verbs, adverbs and adjectives) are extracted in order to form different bag of word pairs with the joy, disgust, fear, anger, sadness and surprise emotions. For each pair, we compute the Mutual Information Score which is obtained from the web occurrences of an emotion and the content words. Our approach is based on the hypothesis that group of words which co-occur together across many documents with a given emotion are highly probable to express the same emotion.
Tree mining: Equivalence classes for candidate generation
Authors: F. Del Razo López, A. Laurent, M. Teisseire, P. Poncelet
Venue: Intelligent Data Analysis (2009)

With the rise of active research fields such as bioinformatics, taxonomies and the growing use of XML documents, tree data are playing a more and more important role. Mining for frequent subtrees from these data is thus an active research problem and traditional methods (e.g., itemset mining from transactional databases) have to be extended in order to tackle the problem of handling tree-based data. Some approaches have been proposed in the literature, mainly based on generate-and-prune methods. However, they generate a large volume of candidates before pruning them, whereas it could be possible to discard some solutions as they contain unfrequent subtrees. We thus propose a novel approach, called pivot, based on equivalence classes in order to decrease the number of candidates. Three equivalence classes are defined, the first one relying on a right equivalence relation between two trees, the second one on a left equivalence relation, and the third one on the ground of a root equivalence relation. In this paper, we introduce this new method, showing that it is complete (i.e., no frequent subtree is forgotten), and efficient, as illustrated by the experiments led on synthetic and real datasets.
Research on a Vehicle Routing Schedule to Reduce Fuel Consumption
Authors: Yong Peng, Xiaofeng Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization task. This problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. Almost all the research papers of VRPs focus on minimizing the sum of travel distance (travel time). However, vehicle managers are also interested in the vehicle routing schedules which minimize fuel consumption caused by two factors. First, reducing fuel consumption means reducing the service cost. Second, reducing fuel consumption means reducing its impact on our environment (green-house effect), our health (air pollutants), and our economy (increased fuel prices). This paper provides a new vehicle routing problem based on reducing fuel consumption. That is, the optimization objective of the vehicle routing problem is to minimize the fuel consumption. The paper also gives the corresponding vehicle routing problem, the optimization objective of which is to minimize the travel distance. Through a numerical example, the two problems are compared. The result shows that a different vehicle routing schedule is probable found if the optimization objective is to minimize fuel consumption other than to minimize travel distance.
Energy Efficient DNA-Based Scheduling Scheme for Wireless Sensor Networks
Authors: Shan Suthaharan, Abhinav Chawade, Rittwik Jana, Jing Deng
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

Wireless sensor networks are currently deployed in many areas, particularly for surveillance related applications. Sensors have very limited energy and processing capabilities, hence, it becomes necessary to introduce energy efficient algorithms to maximize the lifetime of a sensor node. We propose a new scheduling scheme based on Discrete Time Markov chain models used in genetics for DNA evolution prediction. The proposed scheduler uses a single control parameter to control state changes in order to obtain a compromise between network lifetime and throughput. We discuss the design of such a Discrete Time Markov chain based scheme and compare it to a standard approach in terms of node throughput and lifetime of entire network. Finally, we show the effectiveness of this scheme by simulating various network topologies in a realistic sensor network. Our observations show that just after 75% of simulation steps 90% more nodes are alive with the proposed scheduler. The residual battery power is 82% more and the packet reception rate is increased by 51% for the entire network when compared to the standard approach.
Relation extraction from wikipedia using subtree mining
Authors: Dat P. T. Nguyen, Yutaka Matsuo, Mitsuru Ishizuka
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

The exponential growth and reliability of Wikipedia have made it a promising data source for intelligent systems. The first challenge of Wikipedia is to make the encyclopedia machine-processable. In this study, we address the problem of extracting relations among entities from Wikipedia's English articles, which in turn can serve for intelligent systems to satisfy users' information needs. Our proposed method first anchors the appearance of entities in Wikipedia articles using some heuristic rules that are supported by their encyclopedic style. Therefore, it uses neither the Named Entity Recognizer (NER) nor the Coreference Resolution tool, which are sources of errors for relation extraction. It then classifies the relationships among entity pairs using SVM with features extracted from the web structure and subtrees mined from the syntactic structure of text. The innovations behind our work are the following: a) our method makes use of Wikipedia characteristics for entity allocation and entity classification, which are essential for relation extraction; b) our algorithm extracts a core tree, which accurately reflects a relationship between a given entity pair, and subsequently identifies key features with respect to the relationship from the core tree. We demonstrate the effectiveness of our approach through evaluation of manually annotated data from actual Wikipedia articles.
Gaze Behaviors for Virtual Crowd Characters
Authors: Helena Grillon, Barbara Yersin, Jonathan Maïm, Daniel Thalmann
Venue: Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions: COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 Revised Selected and Invited Papers (2009)

Nowadays, crowds of virtual characters are used in many domains such as neurosciences, psychology, and computer sciences. Since as human beings, we are natural experts in human being representation and movement, it makes it that much harder to correctly model and animate virtual characters. This becomes even more challenging when considering crowds of virtual characters. Indeed, in addition to the representation and animation, there is the mandatory trade-off between rich, realistic behaviors and computational costs. In this paper, we present a crowd engine, to which we introduce and extra layer which allows its characters to produce gaze behaviors. We thus enhance crowd realism by allowing the characters composing it to be aware of their environment and other characters and/or a user.
Semidefinite representation of convex sets
Authors: J. William Helton, Jiawang Nie
Venue: Mathematical Programming: Series A and B (2009)

Let $${S =\{x\in \mathbb{R}^n: g_1(x)\geq 0, \ldots, g_m(x)\geq 0\}}$$be a semialgebraic set defined by multivariate polynomials g i (x). Assume S is convex, compact and has nonempty interior. Let $${S_i =\{x\in \mathbb{R}^n:\, g_i(x)\geq 0\}}$$, and &#x2202; S (resp. &#x2202; S i ) be the boundary of S (resp. S i ). This paper, as does the subject of semidefinite programming (SDP), concerns linear matrix inequalities (LMIs). The set S is said to have an LMI representation if it equals the set of solutions to some LMI and it is known that some convex S may not be LMI representable (Helton and Vinnikov in Commun Pure Appl Math 60(5):654&#x2013;674, 2007). A question arising from Nesterov and Nemirovski (SIAM studies in applied mathematics. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 1994), see Helton and Vinnikov in Commun Pure Appl Math 60(5):654&#x2013;674, 2007 and Nemirovski in Plenary lecture, International Congress of Mathematicians (ICM), Madrid, Spain, 2006, is: given a subset S of $${\mathbb{R}^n}$$, does there exist an LMI representable set &#x015c; in some higher dimensional space $${ \mathbb{R}^{n+N}}$$whose projection down onto $${\mathbb{R}^n}$$equals S. Such S is called semidefinite representable or SDP representable. This paper addresses the SDP representability problem. The following are the main contributions of this paper: (i) assume g i (x) are all concave on S. If the positive definite Lagrange Hessian condition holds, i.e., the Hessian of the Lagrange function for optimization problem of minimizing any nonzero linear function &#x2113; T x on S is positive definite at the minimizer, then S is SDP representable. (ii) If each g i (x) is either sos-concave (&#x00a0;&#x2212;&#x00a0;&#x2207;2 g i (x)&#x00a0;=&#x00a0;W(x)T W(x) for some possibly nonsquare matrix polynomial W(x)) or strictly quasi-concave on S, then S is SDP representable. (iii) If each S i is either sos-convex or poscurv-convex (S i is compact convex, whose boundary has positive curvature and is nonsingular, i.e., &#x2207;g i (x) &#x2260; 0 on &#x2202; S i &#x2229; S), then S is SDP representable. This also holds for S i for which &#x2202; S i &#x2229; S extends smoothly to the boundary of a poscurv-convex set containing S. (iv) We give the complexity of Schm&#x00fc;dgen and Putinar&#x2019;s matrix Positivstellensatz, which are critical to the proofs of (i)&#x2013;(iii).
Analysis Time Delay of a Next Generation Name Resolution System
Authors: Fuhong Lin, Changjia Chen, Hengkui Wu, Hongke Zhang, Lili Kou
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Name resolution system is playing an important role in Internet. Owning to original design ill-considerately, DNS has some fate shortcoming. So some researchers propose using flat name resolution to replace it. Until now there are many researches on this function, but few studies on performance. We just do some performance analysis to give a deeper insight into this system. In this paper, we model the time delay in one search in the flat name resolution and it can be divided into three parts: hop time delay, transmission time delay and search time delay. Then we use simulation to give a deep insight and find that hop time delay is the biggest one, the other two can be neglected, for they are too small. But they can infect the nodes capacity, future the network scale.
Optimizing data warehouse loading procedures for enabling useful-time data warehousing
Authors: Ricardo Jorge Santos, Jorge Bernardino
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

The purpose of a data warehouse is to aid decision making. As the real-time enterprise evolves, synchronism between transactional data and data warehouses is redefined. To cope with real-time requirements, the data warehouses must be able to enable continuous data integration, in order to deal with the most recent business data. Traditional data warehouses are unable to support any dynamics in structure and content while they are available for OLAP. Their data is periodically updated because they are unprepared for continuous data integration. For real-time enterprises with needs in decision support while the transactions are occurring, (near) real-time data warehousing seem very promising. In this paper we present a survey on testing today's most used loading techniques and analyze which are the best data loading methods, presenting a methodology for efficiently supporting continuous data integration for data warehouses. To accomplish this, we use techniques such as table structure replication with minimum content and query predicate restrictions for selecting data, to enable loading data in the data warehouse continuously, with minimum impact in query execution time. We demonstrate the efficiency of the method using benchmark TPC-H and executing query workloads while simultaneously performing continuous data integration.