ppxscal/embedding_network huggingface dataset:
A comparison of pixel-based and object-oriented classification using SPOT5 imagery
Authors: Minjie Chen, Wei Su, Li Li, Chao Zhang, Anzhi Yue, Haixia Li
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

Land cover maps can assist decision-makers in both the scientific and business activities, and remote sensing techniques provide effective and efficient methods to create such maps. However, some image processing approaches may be more appropriate than others in distinguishing land-cover categories, particularly when classifying high spatial resolution imagery. Here both the pixel-based classification method based on the knowledge rule and the object-oriented fuzzy classification method have been studied systematically and deeply in this paper with SPOT5 high spatial resolution imagery. The Digital elevation model (DEM) data and the texture feature are integrated into the two knowledge-based classifications in this paper. And the result of accuracy assessment indicates that the two knowledge-based classifications can catch very good classification precision. Besides, the shape and context information can be used fully to distinguish the roads from the houses with the objected-oriented fuzzy classification method, which is hard to accomplish in pixel-based classification. Furthermore, the "Salt and Pepper" effect is eliminated very well with the objected-oriented fuzzy classification method, which always exists in pixel-based classification.
Higher-order monotone iterative methods for finite difference systems of nonlinear reaction--diffusion--convection equations
Authors: Yuan-Ming Wang, Xiao-Lin Lan
Venue: Applied Numerical Mathematics (2009)

This paper is concerned with the computational algorithms for finite difference discretizations of a class of nonlinear reaction-diffusion-convection equations with nonlinear boundary conditions. A higher-order monotone iterative method is presented for solving the finite difference discretizations of both the time-dependent problem and the corresponding steady-state problem. This method leads to an efficient linear iterative algorithm which yields two sequences of iterations that converge monotonically to a unique solution of the system. The monotone property of the iterations gives concurrently improved upper and lower bounds of the solution in each iteration. It is shown that the rate of convergence for the sum of the two produced sequences is of order p+2, where p>=1 is a positive integer depending on the construction of the method, and under an additional requirement, the higher-order rate of convergence is attained for one of these two sequences. An application is given to an enzyme-substrate reaction-diffusion problem, and some numerical results are presented to illustrate the effectiveness of the proposed method.
A note on a spanning 3-tree
Authors: Masao Tsugaki
Venue: Combinatorica (2009)

A tree T is called a k-tree, if the maximum degree of T is at most k. In this paper, we prove that if G is an n-connected graph with independence number at most n + m + 1 (n&#x2265;1,n&#x2265;m&#x2265;0), then G has a spanning 3-tree T with at most m vertices of degree 3.
Automatically generating personalized user interfaces
Authors: Daniel S. Weld
Venue:  (2008)

User Interfaces for today's software are usually created in a one-size-fits-all manner, making implicit assumptions about the needs, abilities, and preferences of the "average user" and the characteristics of the "average device." I argue that personalized user interfaces, which are adapted to a person's devices, tasks, preferences, and abilities, can improve user satisfaction and performance. I have developed three systems: (1) SUPPLE, which uses decision-theoretic optimization to automatically generate user interfaces adapted to a person's device and long-term usage; (2) ARNAULD, which allows optimization-based systems to be adapted to users' preferences; and (3) ABILITY MODELER and an extension of SUPPLE that first performs a one-time assessment of a person's motor abilities and then automatically generates user interfaces predicted to be the fastest to use for that user. My experiments show that these automatically generated, personalized user interfaces significantly improve speed, accuracy, and satisfaction for users with motor impairments compared to manufacturers' default interfaces. I also provide the first characterization of the design space of adaptive graphical user interfaces, and demonstrate how such interfaces can significantly improve the quality and efficiency of daily interactions for typical users.
Function of EEG Temporal Complexity Analysis in Neural Activities Measurement
Authors: Xiuquan Li, Zhidong Deng, Jianwei Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

We investigate the correlation between temporal complexity of EEG signal and the underlining neural activities. Fractal geometry has been proved useful in quantifying complexities of dynamical signals. Temporal fractal dimension of EEG signals provides a new neurophysiological measure. In order to better understand what the complexity measure reveals about the underling brain process, a further exploration on the neuronal generators of fractal geometry characteristics of EEG is conducted in this study. Our investigation suggests that the temporal fractal measure of EEG signals can be related to the activity diversity of neuronal population activities. The complexity measure also gives an indication on the change in synchronization state under certain mental conditions. These assumptions are supported by experimental evidence from the visual cortex and sensorimotor cortex. This work helps give an interpretation of the obtained results of the temporal complexity analysis on EEG signals and may be useful in further investigating the covert steps of brain information processing.
KIDS table: Interactive tabletop Display Systems
Authors: Kunio Sakamoto, Yuko Iwaze
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

Conventional information displays provide us some images. However these images are generally two-dimensional(2D). If the images are displayed in the three-dimensional (3D) space, these images are in the air at a distance from a desk and users can directly touch and interact them such that kids can make play clay. In addition, many applications for 3D imaging can be proposed. The authors have researched the 3D displays and applications. We developed new applications and a prototype interactive tabletop holographic display system. These systems consist of the object recognition system and the spatial imaging system. In this paper, we describe the recognition system using RFID tags and a tabletop display system using a conventional CRT display and a holographic technology.
DrilLs-M: Multimedia Testing System with Operation-Style Answering --Application to Kanji Letter Shape Learning --
Authors: Hiroyuki Tominaga, Yu Kinugasa, Naoko Yamashita, Toshihiro Hayashi, Toshinori Yamasaki
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

There are some practical Web-based testing systems and drill type CAI with multimedia questioning. Many of these systems do not adopt adequate answering methods for multimedia materials. In this research, we propose a model of operation style answering for multimedia questioning. We classify the answering and input operation to determine description format. We develop DrilLs-M: multimedia testing system based on the model and description. It enables some natural user actions as answering, such as, designation of areas and drawing lines with a mouse or pen tablet. It supports experiential learning effectively. We introduce an application to Kanji letter shape learning. And we discuss the suitable answering style. It offers matching methods and input guide interface.
Organic design techniques utilized in the development of a domain-based integrated knowledge repository to enhance learning outcomes
Authors: David Lubliner, George Widmeyer, Fadi P. Deek
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

The goal of the research was to design and build an organic knowledge repository that had the inherent ability to grow and evolve over time. A design artifact -- Constructivist Unifying Baccalaureate Epistemology (CUBE) -- was designed and tested to validate the efficacy of this approach. Concept Clustering displayed as a knowledge map was used to display linkages between related concepts. Two models that facilitate this organic nature of the system were developed for this research; a Knowledge Weighting Model and the Aggregation-Integration-Master model. A ranking/voting feature was incorporated which enabled students and faculty to add content to the knowledge base and collectively evaluate the relative weights of conceptual threads. The two design goals of this approach were validated. First, students and faculty were able to enter information that dynamically altered the organization and structure of the knowledge repository. Second, students utilizing the Integrated Knowledge Repository developed a more complex understanding of the interconnected nature of the materials linking a discipline than those students who take conventional single topic courses.
Incorporating helpful behavior into collaborative planning
Authors: Ece Kamar, Ya'akov Gal, Barbara J. Grosz
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper considers the design of agent strategies for deciding whether to help other members of a group with whom an agent is engaged in a collaborative activity. Three characteristics of collaborative planning must be addressed by these decision-making strategies: agents may have only partial information about their partners' plans for sub-tasks of the collaborative activity; the effectiveness of helping may not be known a priori; and, helping actions have some associated cost. The paper proposes a novel probabilistic representation of other agents' beliefs about the recipes selected for their own or for the group activity, given partial information. This representation is compact, and thus makes reasoning about helpful behavior tractable. The paper presents a decision-theoretic mechanism that uses this representation to make decisions about two kinds of helpful actions: communicating information relevant to a partner's plans for some sub-action, and adding domain actions that are helpful to other agent(s) into the collaborative plan. This mechanism includes a set of rules for reasoning about the utility of helpful actions and the cost incurred by doing them. It was tested using a multi-agent test-bed with configurations that varied agents' uncertainty about the world, their uncertainty about each others' capabilities or resources, and the cost of helpful behavior. In all cases, agents using the decision-theoretic mechanism to decide whether to help outperformed agents using purely axiomatic rules.
A structured P2P network based on the small world phenomenon
Authors: Jie Xu, Hai Jin
Venue: The Journal of Supercomputing (2009)

In this paper, we propose a new structured P2P overlay network, named SW-Uinta(small-world). In order to reduce the routing latency, we firstly construct the Uinta network in which both physical characteristics of network and data semantic are considered. Furthermore, based on Uinta, a nondeterministic caching strategy is employed to allow for poly-logarithmic search time while having only a constant cache size. Compared with the deterministic caching strategy proposed by previous P2P systems, the nondeterministic caching strategy can reduce communication overhead for maintaining the routing cache table. Cache entries in the cache table of peer nodes can be updated by subsequent queries rather than only by running stabilization periodically. In the following, a novel cache replacement scheme, named the SW cache replacement scheme, is used to improve lookup performance, which has proved to satisfy the small-world principle. So we call this network SW-Uinta(small-world). After that, according to the theoretical analysis, it can be proved that SW-Uinta(small-world) can get O((log¿2 N)/k) search time with O(k) cache size. Lastly, the performance of SW-Uinta(small-world) is compared with those of other structured P2P networks such as Chord and Uinta. It shows that SW-Uinta(small-world) can achieve improved object lookup performance and reduce maintenance cost.
Plenary lecture 5: iterative solution paradigms for uncalibrated robot vision control
Authors: Mirjana Bonkovic
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

Vision is one of the most important sense in humans. Numerous attempts to mimic that powerful sense have been the main topic of extensive robotic research for decades. Demonstrated applications of vision control in which information acquired from camera(s) is used for guiding a robot system, span the broad range of human activity and include well-known theoretical, as well as practical knowledge of visual servoing themes. Visual servoing problem is, in fact, the problem of systems of nonlinear equations solving, which is a mature and well founded mathematical area with rich foundations of papers, studying the various type of problems with appropriate approaches. Uncalibrated, model free, robot visual servoing has been widely applicable in robot vision due to minimal requirements related to calibration and robot kinematic's parameters. The appropriate solutions are mostly derived from quasy-Newton approach for the nonlinear problem solving and represent various iterative approaches for acquiring an optimal solution. However, if the robot has been controlled in the unstructured environments, the mentioned problem has been proven hard as the real system has been influenced with the noise. Up to now, there are numerous examples which successfully use described approach for robot visual servoing. The numerical quasy-Newton methods serves as a theoretical background for problem solving, which has been proven hard as the real system has been influenced with the noise. Consequently, additional attention has to be paid which assured stability and the robustness of the proposed method. Various methods offer specific improvements which are related mostly to the specific task requirements. This lecture has a goal to present and compare the efficacy of the various iterative optimization procedures which, due to their successfulness, established itself as a paradigm for appropriate problem solving.
Positive solutions of nonlinear m-point boundary value problems on time scales
Authors: N. Aykut Hamal, Fulya Yoruk
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, by using fixed point theorems in a cone and the associated Green's function, we study the existence of at least two and three positive solutions to the m-point boundary value problem (BVP) on time scales, u^@D^@?(t)+f(t,u(t))=0,t@?[0,1]@?T,@bu(0)-@cu^@D(0)=0,u(1)=@?i=1m-2@a"iu(@e"i),m>=3, where T is a time scale, f@?C"l"d([0,1]x[0,~),[0,~)), @b,@c@?[0,~),@a"i@?[0,~) for i=1,2,...,m-2, and @e"i satisfy 0
An efficient implementation of a least squares Monte Carlo method for valuing American-style options
Authors: Christian Jonen
Venue: International Journal of Computer Mathematics (2009)

Several methods for valuing high-dimensional American-style options were proposed in the last years. Longstaff and Schwartz (LS) have suggested a regression-based Monte Carlo approach, namely the least squares Monte Carlo method. This article is devoted to an efficient implementation of this algorithm. First, we suggest a code for faster runs. Regression-based Monte Carlo methods are sensitive to the choice of basis functions for pricing high-dimensional American-style options and, like all Monte Carlo methods, to the underlying random number generator. For this reason, we secondly propose an optimal selection of basis functions and a random number generator to guarantee stable results. Our basis depends on the payoff of the high-dimensional option and consists of only three functions. We give a guideline for an efficient option price calculation of high-dimensional American-style options with the LS algorithm, and we test it in examples with up to 10 dimensions.
HLA-Based Emergency Response Plan Simulation and Practice over Internet
Authors: Wan Hu, Hong Liu, Qing Yang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Efficient emergency response for disasters needs systematic response preparedness and plan. Distributed computer simulation and practice drilling can help to perfect the emergency response plan and train the participants. In this paper, a distributed simulation and practice framework which realizes extending HLA/RTI to Internet based on Grid service is proposed. The framework aims to the advantage of Grid technology as well as the reusability and interoperability of simulation modules. The results of experiments of the prototype indicate the feasibility of the framework, which provide a platform for emergency response drilling distributed simulation over Internet. At the end of paper, the future development plan has been discussed.
A Perspective Ontology and IS Perspectives
Authors: Mauri Leppänen
Venue: Proceeding of the 2008 conference on Information Modelling and Knowledge Bases XIX (2008)

Information processing is often such a large and complex artifact that it goes beyond a human being's capacity to conceive, model and develop it with all of its aspects at a time. For this reason, it is typical for one to focus on some aspects of it in one time and on other aspects in another time, depending on the problem at hand. For recurrent situations it is necessary to have a structured and well-defined set of perspectives which guide selections and shifts of focuses. This paper presents a light-weight perspective ontology which provides a set of well-defined perspectives, established on three dimensions, to conceive issues in information processing in an organized manner. The perspective ontology can be applied on different information processing layers, such as information systems (IS), information systems development (ISD) and method engineering (ME). To demonstrate the applicability of the ontology, it is used to derive a set of IS perspectives with basic IS concepts and constructs. The IS perspectives are then deployed as a framework in a comparative analysis of current perspectives in the IS literature.
Predicting High-level Student Responses Using Conceptual Clustering
Authors: Roberto Legaspi, Raymund Sison, Ken-ichi Fukui, Masayuki Numao
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

A conceptual clustering algorithm can search through huge amounts of data looking for multi-dimensional structures, where each structure or cluster represents a relevant concept in the problem-solving domain. We investigated on the effect of cluster knowledge for a learning agent to improve its prediction of higher level student response aspects. Our empirical results show that when cluster knowledge is utilized by a function approximator, prediction is improved as compared to treating the entire data population as a single cluster.
New Horizons in Mobile and Wireless Communications: Reconfigurability, 1st edition
Authors: Ramjee Prasad, Albena Mihovska
Venue:  (2009)

Based on cutting-edge research projects in the field, this comprehensive 4-volume book series provides the latest details and covers the most impactful aspects of mobile, wireless, and broadband communications development. These books present key systems and enabling technologies in a clear and accessible manner, offering you a detailed roadmap the future evolution of next generation communications. Drawing upon the insights of leading experts in the field, each of the four volumes is dedicated to an area of critical importance, including Radio Interfaces; Networks, Services and Applications; Reconfigurability; and Ad Hoc Networks.
Probing Technology as Affordances for Negotiating Meaning in the Elementary Science Classroom ----A Participation Perspective
Authors: Fei-Ching Chen, Huo-Ming Jiang, Jie-Chi Yang, Yu-Wei Lee
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Probing technologies are assumed to augment and speed inquiry learning. However, in practice, handheld-based classroom practice is regarded as only having scratched the surface of what is possible. The purpose of this article is to propose regarding the probe as a catalyst for negotiating meaning in inquiry learning activities. Viewed from a participation-framework perspective, we claim that probing technologies trigger the cycle of, and interplay between, reified object generation (numbers, graphs,...) and engaged participation among learners. An analysis of a probe-supported inquiry activity in a grade 5 elementary classroom is conducted. Three episodes in an inquiry classroom reveal the focusing and reified effects of probes in enhancing meaning negotiation, and in supporting student-driven exploration. The function of probes in both emergent and instantaneous aspects of learning is also discussed.
Semi-supervised learning for natural language processing
Authors: John Blitzer, Xiaojin Jerry Zhu
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Tutorial Abstracts (2008)

The amount of unlabeled linguistic data available to us is much larger and growing much faster than the amount of labeled data. Semi-supervised learning algorithms combine unlabeled data with a small labeled training set to train better models. This tutorial emphasizes practical applications of semisupervised learning; we treat semi-supervised learning methods as tools for building effective models from limited training data. An attendee will leave our tutorial with 1. A basic knowledge of the most common classes of semi-supervised learning algorithms and where they have been used in NLP before. 2. The ability to decide which class will be useful in her research. 3. Suggestions against potential pitfalls in semisupervised learning.
Random Subset Optimization
Authors: Boi Faltings, Quang-Huy Nguyen
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization problems benefit significantly from randomization. However, well-known algorithms such as stochastic search or simulated annealing perform a less directed random walk than used in satisfiability. By making a closer analogy to the technique used in Walksat, we obtain a different kind of randomization called random subset optimization. Experiments on both structured and random problems show strong performance compared with other local search algorithms.