ppxscal/embedding_network huggingface dataset:
Realizing Adaptive Instruction (Ad-In): The Convergence of Learning, Instruction, and Assessment
Authors: Edward Dieterle, John Murray
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

In this paper, we define adaptive instruction, or Ad-In, as applied to sophisticated skills development systems that target learning and assessment in a highly individualized and interactive manner. We argue that the successful design and use of such systems rely heavily upon the interrelationships among learning styles, instructional theories, and assessment methods, in the context of personalized learning. We outline and structure the links among these topics by drawing upon recent empirical studies of virtual environments and augmented realities. The paper also presents a candidate architecture for applying Ad-In concepts in an intelligent interactive environment for skills development.
Edge Based Chinese Wine Classification Using FCM and Kernel Principal Component Analysis
Authors: Rong Guo, Xingbo Sun, Yi Wan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Micrographs of Chinese wines show floccule, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs. A semi-supervised wine classification method based on kernel principal component analysis (KPCA) method and fuzzy C-means (FCM) algorithm using edge feature from micrographs was proposed in this paper. In this work, ten Chinese wines are determined or classified in the system, such as Wuliangye, Luzhoulaojiao, Xushui, Jiannanchun, Maotai and et.al. First, the micrographs were enhanced using Rotating Kernel Transformation (RKT) Filter, and edges of these images were detected using Canny edge detector; then the edges features were mapped into parameter space through circular Hough transform, and Kernel Principal Components Analysis was performed for feature dimension reduction. We adopted the semi-unsupervised classification method improved FCM in which the cluster centers were given. The means of feature vectors generated from each wine in training set were employed as the corresponding cluster center. We compared the recognition results for different choices of parameters in Kernel Principal Components Analysis. The experimental results showed that, the classification rate was over 95%.
Practical API Protocol Checking with Access Permissions
Authors: Kevin Bierhoff, Nels E. Beckman, Jonathan Aldrich
Venue: Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming (2009)

Reusable APIs often define usage protocols. We previously developed a sound modular type system that checks compliance with typestate-based protocols while affording a great deal of aliasing flexibility. We also developed Plural, a prototype tool that embodies our approach as an automated static analysis and includes several extensions we found useful in practice. This paper evaluates our approach along the following dimensions: (1) We report on experience in specifying relevant usage rules for a large Java standard API with our approach. We also specify several other Java APIs and identify recurring patterns. (2) We summarize two case studies in verifying third-party open-source code bases with few false positives using our tool. We discuss how tool shortcomings can be addressed either with code refactorings or extensions to the tool itself. These results indicate that our approach can be used to specify and enforce real API protocols in practice.
A learning and reasoning system for intelligence analysis
Authors: Mihai Boicu, Gheorghe Tecuci, Cindy Ayers, Dorin Marcu, Cristina Boicu, Marcel Barbulescu, Bogdan Stanescu, William Wagner, Vu Le, Denitsa Apostolova, Adrian Ciubotariu
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

This paper presents a personal cognitive assistant, called Disciple-LTA, that can acquire expertise in intelligence analysis directly from intelligence analysts, can train new analysts, and can help analysts find solutions to complex problems through mixed-initiative reasoning, making possible the synergistic integration of a human's experience and creativity with an automated agent's knowledge and speed, and facilitating the collaboration with complementary experts and their agents.
A new grouping genetic algorithm approach to the multiple traveling salesperson problem
Authors: Alok Singh, Anurag Singh Baghel
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2008)

The multiple traveling salesperson problem (MTSP) is an extension of the well known traveling salesperson problem (TSP). Given m > 1 salespersons and n > m cities to visit, the MTSP seeks a partition of cities into m groups as well as an ordering among cities in each group so that each group of cities is visited by exactly one salesperson in their specified order in such a way that each city is visited exactly once and sum of total distance traveled by all the salespersons is minimized. Apart from the objective of minimizing the total distance traveled by all the salespersons, we have also considered an alternate objective of minimizing the maximum distance traveled by any one salesperson, which is related with balancing the workload among salespersons. In this paper, we have proposed a new grouping genetic algorithm based approach for the MTSP and compared our results with other approaches available in the literature. Our approach outperformed the other approaches on both the objectives.
Agent coordination with regret clearing
Authors: Sven Koenig, Xiaoming Zheng, Craig Tovey, Richard Borie, Philip Kilby, Vangelis Markakis, Pinar Keskinocak
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Sequential single-item auctions can be used for the distributed allocation of tasks to cooperating agents. We study how to improve the team performance of sequential single-item auctions while still controlling the agents in real time. Our idea is to assign that task to agents during the current round whose regret is large, where the regret of a task is defined as the difference of the second-smallest and smallest team costs resulting from assigning the task to the second-best and best agent, respectively. Our experimental results show that sequential single-item auctions with regret clearing indeed result in smaller team costs than standard sequential single-item auctions for three out of four combinations of two different team objectives and two different capacity constraints (including no capacity constraints).
Evolution patterns and gradual trends
Authors: Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire
Venue: International Journal of Intelligent Systems (2009)

Nowadays, many databases record ordered or temporally annotated data, such as Web access logs or genomic sequences. Therefore, sequence mining has become an important research area. Among these data mining approaches, sequential patterns aim at describing frequent behaviors. In the access data of a commercial Web site, one may, for instance, discover that &ldquo;35&percnt; of customers successively buy a PSP then a memory stick and PSP games&rdquo;. To provide more complete information, fuzzy sequential patterns were designed, including quantitative values within the mining task. Such patterns, considering the previous example, would be &ldquo;35&percnt; of customers buy a PSP, then they buy few games many times, and then they buy a high-capacity memory stick once.&rdquo; However, symbolic or fuzzy sequential patterns, in their current form, do not allow to extract temporal tendencies that are typical of sequential data. By means of temporal tendency mining, one may discover in the same access data that &ldquo;An increasing number of purchases of PSP games during a very short period is frequently followed by a purchase of a high-capacity memory stick a few days later.&rdquo; It would be easy to conclude that the users either quickly succeed in registering or make several attempts before they look at the help page within a few seconds. To the best of our knowledge, no method has been designed for discovering this kind of patterns. Therefore, we propose, in this paper, two approaches that extract pattern-expressing trends or evolution. First, we define evolution patterns that summarize the evolution of the quantities in the data. We explain how they can be obtained from a quantitative sequence database. Second, we define gradual trends in fuzzy sequential data. These trends describe variations in the fulfillment of fuzzy properties according to time. For both kinds of patterns, we developed algorithms that were implemented and tested on real data. &copy; 2009 Wiley Periodicals, Inc.
Poker surface: combining a multi-touch table and mobile phones in interactive card games
Authors: Alireza Sahami Shirazi, Tanja Döring, Pouyan Parvahan, Bernd Ahrens, Albrecht Schmidt
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

In this paper, we introduce the design and implementation of a digital card game that combines mobile phone gestures and multi-touch tabletop interactions. Conceptually based on interactions in traditional card games, our Poker game application explores different natural ways of interaction, including touching the table as well as tilting, throwing, and shaking a mobile phone. By exemplarily translating traditional gestures into the digital domain, we provide a use case to discuss useful gestures combing mobile phones with tabletop surfaces, as well as to explore a private-public display setting for digital card games at interactive tables. Additionally, the mobile phone provides a tangible feeling similar to physical cards. The preliminary user study showed that users preferred using mobile phones for interaction compared to direct interaction on the multi-touch table.
Efficient Multi-start Strategies for Local Search Algorithms
Authors: Levente Kocsis, András György
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Local search algorithms for global optimization often suffer from getting trapped in a local optimum. The common solution for this problem is to restart the algorithm when no progress is observed. Alternatively, one can start multiple instances of a local search algorithm, and allocate computational resources (in particular, processing time) to the instances depending on their behavior. Hence, a multi-start strategy has to decide (dynamically) when to allocate additional resources to a particular instance and when to start new instances. In this paper we propose a consistent multi-start strategy that assumes a convergence rate of the local search algorithm up to an unknown constant, and in every phase gives preference to those instances that could converge to the best value for a particular range of the constant. Combined with the local search algorithm SPSA (Simultaneous Perturbation Stochastic Approximation), the strategy performs remarkably well in practice, both on synthetic tasks and on tuning the parameters of learning algorithms.
Distributed Loom Running Monitoring System Based on ZigBee Technology
Authors: Dong FangWu, Jia XiangSu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Aiming at the requirement of real-time monitoring of looms and limitations of subsistent monitor systems, a new monitor system based on ZigBee technology for looms was proposed, and then put forward its network structure. The CC2430 chip based on ZigBee technology from TI Company was applied to node controllers which function as data collection and transmission, management of monitoring network, fault alarm and so on. Then the article devised the circuit schematic for performance data collection, network monitoring node. At the same time pictured the program procedure of master node and data collection node, network protocol and structure of data frame. The result shows that the system has the following characteristics: stable and reliable, anti-jamming, low-power, small-size and low-cost, so this means it can provide the monitoring of looms in textile production with a new technology.
Web document text and images extraction using DOM analysis and natural language processing
Authors: Parag Mulendra Joshi, Sam Liu
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

Web has emerged as the most important source of information in the world. This has resulted in need for automated software components to analyze web pages and harvest useful information from them. However, in typical web pages the informative content is surrounded by a very high degree of noise in the form of advertisements, navigation bars, links to other content, etc. Often the noisy content is interspersed with the main content leaving no clean boundaries between them. This noisy content makes the problem of information harvesting from web pages much harder. Therefore, it is essential to be able to identify main content of a web page and automatically isolate it from noisy content for any further analysis. Most existing approaches rely on prior knowledge of website specific templates and hand-crafted rules specific to websites for extraction of relevant content. We propose a generic approach that does not require prior knowledge of website templates. While HTML DOM analysis and visual layout analysis approaches have sometimes been used, we believe that for higher accuracy in content extraction, the analyzing software needs to mimic a human user and understand content in natural language similar to the way humans intuitively do in order to eliminate noisy content. In this paper, we describe a combination of HTML DOM analysis and Natural Language Processing (NLP) techniques for automated extractions of main article with associated images from web pages.
Peak Performance Trainer (PPTTM): Interactive Neuro-educational Technology to Increase the Pace and Efficiency of Rifle Marksmanship Training
Authors: Giby Raphael, Chris Berka, Djordje Popovic, Gregory K. Chung, Sam O. Nagashima, Adrienne Behneman, Gene Davis, Robin Johnson
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Marksmanship training involves a combination of classroom instructional learning and field practice involving the instantiation of a well-defined set of sensory, motor and cognitive skills. Current training procedures rely heavily on conventional classroom instruction often with qualitative assessment based on observation (i.e. coaching). We have developed a novel device called the Peak Performance Trainer (PPTTM) which can accelerate the progression from novice-to-expert based on automated inferences from neurophysiological measurements. Our previous work has revealed specific EEG correlates to stages of skill acquisition in simple learning and memory tasks. We have incorporated this knowledge as well as an array of other physiological metrics to develop a field-deployable training technology with continuous physiological monitoring in combination with simultaneous measures of performance, workload, engagement and distraction, accuracy, speed and efficiency. This paper outlines the features of the PPT and the preliminary results of its use in marksmanship training.
Email Accessibility and Social Networking
Authors: Brian Wentz, Jonathan Lazar
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

Previous studies concerning the accessibility of social networking web sites have revealed that there are components of such web sites which present accessibility problems for users with disabilities, including blind users. This paper discusses the intersection of e-mail accessible and social networking, for blind users. Not only is e-mail an important component of social networking sites, but often, an e-mail address is required for registration. The topic of e-mail and social networking is being studied in the broader context of a multi-stage research study of blind users and their e-mail usage. This multi-stage study is being conducted to understand the usage patterns and accessibility problems encountered by blind users in using both web-based and application-based e-mail. Our hope is that the research study will result in the proposal of new strategies and guidelines for accessible design. This conference presentation will report on the status of the data collection.
Estimating VaR in crude oil market: A novel multi-scale non-linear ensemble approach incorporating wavelet analysis and neural network
Authors: Kaijian He, Chi Xie, Shou Chen, Kin Keung Lai
Venue: Neurocomputing (2009)

Facing the complicated non-linear nature of risk evolutions, current risk measurement approaches offer insufficient explanatory power and limited performance. Thus this paper proposes wavelet decomposed non-linear ensemble value at risk (WDNEVaR), a novel semi-parametric paradigm, incorporating both, wavelet analysis and artificial neural network technique to further improve the modeling accuracy and reliability. Wavelet analysis is utilized to capture the multi-scale data characteristics across scales while artificial neural network technique is utilized to reduce estimation biases following non-linear ensemble algorithms. Experiment results in three major markets suggest that the proposed WDNEVaR is superior to more traditional approaches as it provides value at risk (VaR) estimates at higher reliability and accuracy.
Using Graph-Kernels to Represent Semantic Information in Text Classification
Authors: Teresa Gonçalves, Paulo Quaresma
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

Most text classification systems use bag-of-words representation of documents to find the classification target function. Linguistic structures such as morphology, syntax and semantic are completely neglected in the learning process.This paper proposes a new document representation that, while including its context independent sentence meaning, is able to be used by a structured kernel function, namely the direct product kernel.The proposal is evaluated using a dataset of articles from a Portuguese daily newspaper and classifiers are built using the SVM algorithm. The results show that this structured representation, while only partially describing document's significance has the same discriminative power over classes as the traditional bag-of-words approach.
Research on the Characteristics of Dynamic Map Information
Authors: Miao Lei, Li Xinyan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Dynamic cartographic visualization is popularly used to discovery knowledge in practice. In this paper it’s deeply discussed about dynamic map information, such as the categories, the characteristics, the way of representation and the limitation. A prototype system about population changes is presented to test.
Stereoscopic aerial photography: an alternative to model-based urban mobility approaches
Authors: Michel Ferreira, Hugo Conceição, Ricardo Fernandes, Ozan K. Tonguz
Venue: Proceedings of the sixth ACM international workshop on VehiculAr InterNETworking (2009)

In the absence of large-scale deployments of VANETs, simulation based research is until now the only choice available to address and validate the design of protocols in the context of vehicular networks. The simulation frameworks involved in this research have to model two essential components, namely the vehicular mobility and the wireless inter-vehicle communication. Both of these aspects are especially complex in urban scenarios. In this paper we propose an alternative approach to obtain a realistic configuration of vehicles, and the respective traveling speeds, based on stereoscopic aerial photography, that is available to virtually every city in the world. We further use the aerial perspective of an urban area to identify a buildings layer and evaluate a wireless communication model that accounts for the obstructions caused by such layer on the connectivity of the wireless network. We evaluate our proposal over the city of Porto and compare the results obtained with model-based mobility approaches. Our results show significant differences in the connectivity profile of the analyzed urban VANET.
Learning to match names across languages
Authors: Inderjeet Mani, Alex Yeh, Sherri Condon
Venue: Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization (2008)

We report on research on matching names in different scripts across languages. We explore two trainable approaches based on comparing pronunciations. The first, a cross-lingual approach, uses an automatic name-matching program that exploits rules based on phonological comparisons of the two languages carried out by humans. The second, monolingual approach, relies only on automatic comparison of the phonological representations of each pair. Alignments produced by each approach are fed to a machine learning algorithm. Results show that the monolingual approach results in machine-learning based comparison of person-names in English and Chinese at an accuracy of over 97.0 F-measure.
A generalized Weierstrass elliptic function expansion method for solving some nonlinear partial differential equations
Authors: E. A. Saied, Reda G. Abd El-Rahman, Marwa I. Ghonamy
Venue: Computers Mathematics with Applications (2009)

The present paper deals with families of non-trivial solutions of the equation (dd@xw)^2=Pw^4(@x)+Qw^2(@x)+R. On the basis of these solutions, a direct and generalized algebraic algorithm is described for constructing the new solutions of some nonlinear partial differential equations (NLPDEs). Subsequently, many new and more general exact solutions in terms of the Weierstrass elliptic function @?(@x;g"2,g"3) are obtained. The method can be applied to other NLPDEs in mathematical physics.
Who should run the internet?
Authors: Win Treese
Venue: netWorker (2009)

The future of network innovation and user service hangs in the balance.
Routing and Performance Evaluation of Dual Priority Delta Networks under Hotspot Environment
Authors: D. C. Vasiliadis, G. E. Rizos, C. Vassilakis
Venue: Proceedings of the 2009 First International Conference on Advances in Future Internet (2009)

Large swings in the demand for content are commonplace within the Internet. Although Multistage Interconnection Networks (MINs) are fairly flexible in handling varieties of traffic loads, their performance considerably degrades by hotspot traffic, especially at increasing size networks. As alleviation to the tree saturation problem, the prioritizing of packets is proposed leading to a scheme that natively supports multi priority traffic. In this paper the performance evaluation of double-buffered Delta Networks under single hotspot setups, with different offered loads, and 2-class routing traffic is presented and analyzed using simulation experiments. Performance comparison of dual vs. single priority scheme is outlined under hotspot environment, by calculating a universal performance factor, which effectively includes the importance aspect of each of the two most important performance metrics, namely packet throughput and delay. The findings of this paper can be used by MIN designers to optimally configure their networks.