ppxscal/embedding_network huggingface dataset:
Correlation of music charts and search engine rankings
Authors: Martin Klein, Olena Hunsicker, Michael L. Nelson
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

We investigate the question whether expert rankings of real-world entities correlate with search engine (SE) rankings of corresponding web resources. We compare Billboards "Hot 100 Airplay" music charts with SE rankings of associated web resources. Out of nine comparisons we found two strong, two moderate, two weak and one negative correlation. The remaining two comparisons were inconclusive.
Real-time human motion analysis for human-machine interface
Authors: Rin-ichiro Taniguchi, Satoshi Yonemoto, Daisaku Arita
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

This paper presents real-time human motion analysis for human-machine interface. In general, man-machine 'smart' interface requires real-time human motion capturing systems without special devices or markers. Although vision-based human motion capturing systems do not use such special devices and markers, they are essentially unstable and can only acquire partial information because of self-occlusion. When we analyze full-body motion, the problem becomes more severer. Therefore, we have to introduce a robust pose estimation strategy to deal with relatively poor results of image analysis. To solve this problem, we have developed a method to estimate full-body human postures, where an initial estimation is acquired by real-time inverse kinematics and, based on the estimation, more accurate estimation is searched for referring to the processed image. The key point is that our system can estimate full-body human postures from limited perceptual cues such as positions of a head, hands and feet, which can be stably acquired by silhouette contour analysis.
Pervasive knowledge-based networking for maintenance inspection in smart buildings.
Authors: Paul Mara, Rob Brennan, Declan O'Sullivan, Marcus Keane, Kris McGlinn, James O'Donnell
Venue: Proceedings of the 6th international workshop on Managing ubiquitous communications and services (2009)

In modern Smart Buildings, systems monitor and regulate energy consumption, lighting levels, humidity and other environmental factors. However, with the number of data sources increasing, the resulting information glut can reduce decision making efficiency for facility management. A promising technique to mitigate this problem is the use of an integration platform allowing smart applications to process the volume of data and aid in reducing information overload for facility managers and others, such as maintenance engineers who utilise the data. This paper presents an approach for managing data volumes by only routing the data to users or smart applications that have expressly requested it. Experiences with a prototype implementation are also described.
Boosting statistical machine translation by lemmatization and linear interpolation
Authors: Ruiqiang Zhang, Eiichiro Sumita
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

Data sparseness is one of the factors that degrade statistical machine translation (SMT). Existing work has shown that using morpho-syntactic information is an effective solution to data sparseness. However, fewer efforts have been made for Chinese-to-English SMT with using English morpho-syntactic analysis. We found that while English is a language with less inflection, using English lemmas in training can significantly improve the quality of word alignment that leads to yield better translation performance. We carried out comprehensive experiments on multiple training data of varied sizes to prove this. We also proposed a new effective linear interpolation method to integrate multiple homologous features of translation models.
Implementation and empirical evaluations of floor control protocols on PlanetLab network
Authors: Shankar M. Banik, Logan P. Daigle, Tao-hsiang Chang
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Nowadays users from different parts of the world participate in collaborative applications (online games, video-conferencing, distributed large-scale simulations) over the Internet. These applications require that at any point in time only one user can exclusively access a shared resource. The problem of providing exclusive access to shared resources in collaborative applications is known as the floor control problem. Centralized and distributed protocols for floor control problem have been proposed in the literature and simulation experiments have been conducted to study the performance of these protocols. None of these protocols have been tested on the real Internet. In this paper, we present empirical evaluations of different floor control protocols on PlanetLab network which is an overlay testbed that connects several academic institutions and industrial research labs all over the world in a virtual network. We have implemented two flavors of distributed solutions -- the randomized Aloha and the scheduled DQDB (Distributed Queue Dual Bus) based protocols. We have also implemented the centralized protocol where the users send floor requests to a central node and the central node schedules the floor requests based on First in First Out. The protocols are implemented using Berkeley Software Distribution (BSD) sockets API. For the experiments, nodes from different PlanetLab sites are selected to resemble that users from different parts of the world are participating in a collaborative application. Average waiting time to gain a floor is used as the performance metric.
Selecting and Customizing a Mereology Ontology for its Reuse in a Pharmaceutical Product Ontology
Authors: Mariano Fernández-López, Asunción Gómez-Pérez, Mari Carmen Suárez-Figueroa
Venue: Proceeding of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008) (2008)

This paper presents our experience in reusing mereology ontologies in a Pharmaceutical Product ontology, an ontology built by the EU NeOn project. It shows a set of mereology ontologies implemented in different machine interpretable languages and analyzes them according to the different types of mereology identified by Varzi. Then, it describes the specifications of mereology modeling necessities for Pharmaceutical Product. Finally, it presents the ontology which fits best with the specifications. One of the results of this work is a procedure to reuse general (also called common) ontologies.
Neural network control of an inverted pendulum on a cart
Authors: Valeri Mladenov, Georgi Tsenov, Lambros Ekonomou, Nicholas Harkiolakis, Panagiotis Karampelas
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

The balancing of an inverted pendulum by moving a cart along a horizontal track is a classic problem in the area of control. This paper describes two Neural Network controllers to swing a pendulum attached to a cart from an initial downwards position to an upright position and maintain that state. Both controllers are able to learn the demonstrated behavior which was swinging up and balancing the inverted pendulum in the upright position starting from different initial angles.
VCD Bounds for some GP Genotypes
Authors: José Luis Montaòa
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We provide upper bounds for the Vapnik-Chervonenkis dimension (VCD) of classes of subsets of Rn that can be recognized by computer programs represented by expression trees built from arithmetic operations ({+,-,*,/,}), infinitely differentiable algebraic operations (like l-root extraction), conditional instructions and sign tests. Our VCD bounds for this genotype are expressed as a polynomial function in the height of the expression trees used to represent the programs. This implies, in particular, that a GP learning machine dealing with a search space containing sequential exponential time computer programs of polynomial parallel complexity needs only a polynomial amount of training examples.
The alisa delta(crc) classifier for natural surfaces: viewpoint-invariant and illumination-invariant classification of natural surfaces using general-purpose color and texture features with the alisa delta(crc) classifier
Authors: Peter Bock
Venue:  (2008)

The objective of this research is to develop a classifier that can reliably and accurately discriminate among a large number of different natural-surfaces in color images using only general-purpose color and texture features. The general-purpose color and texture features are those which exhibit the least sensitivity to illumination and viewpoint variation in a broad range of applications for which color and texture are a reasonable basis for classification. The feature probability density function (PDF) distributions of natural-surface classes are most definitely not disjoint, which instantly obviates the appropriate use of Bayes' Decision Rule, which is profoundly confused by classes that are heavily overlapped in feature space. Therefore, it was also necessary to develop a new ALISA &delta;CRC classifier that would not be confused by the many different and often highly similar natural-surface classes. A series of experiments have been designed and conducted using the CUReT image database, Caltech facial photo images, and natural images. An ALISA &delta; CRC classifier was trained with up to 61 classes in the CUReT image database, which presents each class in 205 different and carefully controlled viewpoint and illumination conditions. The results with images not in the training set yielded classification accuracies well above 95%. This research then extended the classifier feasibility tests and accuracy measurement using mosaic images made up from different CUReT material surface classes. Next, a skin classification experiment was conducted using Caltech facial photo images that had a single class of interest with complex backgrounds. Finally, a natural image-content classification experiment was performed using natural scenery images that had several classes of interest and irregular class boundaries.
Cost based plan selection for xpath
Authors: Haris Georgiadis, Minas Charalambides, Vasilis Vassalos
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

We present a complete XPath cost-based optimization and execution framework and demonstrate its effectiveness and efficiency for a variety of queries and datasets. The framework is based on a logical XPath algebra with novel features and operators and a comprehensive set of rewriting rules that together enable us to algebraically capture many existing and novel processing strategies for XPath queries. An important part of the framework is PSA, a very efficient cost-based plan selection algorithm for XPath queries. In the presented experimental evaluation, PSA picked the cheapest estimated query plan in 100% of the cases. Our cost-based query optimizer independent of the underlying physical data model and storage system and of the available logical operator implementations, depending on a set of well-defined APIs. We also present an implementation of those APIs, including primitive access methods, a large pool of physical operators, statistics estimators and cost models, and experimentally demonstrate the effectiveness of our end-to-end query optimization system.
Chemical Data Assimilation with CMAQ: Continuous vs. Discrete Advection Adjoints
Authors: Tianyi Gou, Kumaresh Singh, Adrian Sandu
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The Community Multiscale Air Quality (CMAQ) system is the Environmental Protection Agency's main modeling tool for atmospheric pollution studies. CMAQ-ADJ, the adjoint model of CMAQ, offers new capabilities such as receptor-oriented sensitivity analysis and chemical data assimilation. This paper presents the construction of discrete advection adjoints in CMAQ. The new adjoints are thoroughly validated against finite differences. We assess the performance of discrete and continuous advection adjoints in CMAQ on sensitivity analysis and 4D-Var data assimilation applications. The results show that discrete adjoint sensitivities better agree with finite difference value than their continuous counterparts. However, continuous adjoints result in a faster convergence of the numerical optimization in 4D-Var data assimilation. Similar conclusions apply to modified discrete adjoints.
A Perceptual Weighting Filter Based on ISP Pseudo-cepstrum and Its Application in AMR-WB
Authors: Fenglian Li, Xueying Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Wideband speech codec with bandwidth 50--7000Hz provides a significant improvement of codec speech in naturalness and intelligibility.But the spectral tilt is more pronounced in wideband speech signals due to the wide dynamic range between low and high frequencies. For solving this problem, a novel perceptual weighting filter is proposed based on the cepstral difference of Immittance Spectral Pairs (ISP) pseudo-cepstrum and linear prediction cepstral coefficients.The filter significantly compensates the spectral tilt of wideband signals that codec does not require an additional tilt compensation.The frequency response of proposed filter is consistent with the auditory masking theory.The effect of the filter to compensate the spectral tilt of wideband speech signals is much better than the perceptual weighting filter based on the cepstral difference of ISP multiplied-polynomial cepstrum and linear prediction cepstral coefficients.The effective application of the proposed filter to the adaptive multi-rate wideband (AMR-WB) speech codec indicates that the proposed filter not only efficiently compensates the spectral tilt, but also improves the objective evaluation quality values of wideband speech signals.
The Principle of State Expansion in Task State-Space Navigation
Authors: Darren Pearce, Rosemary Luckin
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Users typically navigate the state space of a task through the explicit manipulation of its constituent elements. This paper proposes the Principle of State Expansion (PoSE), a novel alternative to such explicit manipulation. Under the PoSE, users manipulate a collection of states and navigate through the state space by selecting states to expand. An abstract task is presented that contrasts the approaches and demonstrates the generality of the PoSE. This is followed by discussion of WordBird and X-Panda, two concrete implementations of software that follow the PoSE. In conclusion, the advantages over explicit manipulation are discussed especially with reference to the potential for sophisticated learner modelling.
A Confidence-Based Update Rule for Self-updating Human Face Recognition Systems
Authors: Sri-Kaushik Pavani, Federico M. Sukno, Constantine Butakoff, Xavier Planes, Alejandro F. Frangi
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

The aim of this paper is to present an automatic update rule to make a face recognition system adapt itself to the continuously changing appearance of users. The main idea is that every time the system interacts with a user, it adapts itself to include his or her current appearance, and thus, it always stays up-to-date. We propose a novel quality measure, which is used to decide whether the information just learnt from a user can be used to aggregate to what the system already knows. In the absence of databases that suit our needs, we present a publicly available database with 14,279 images of 35 users and 74 impostors acquired in a span of 5 months. Experiments on this database show that the proposed measure is adequate for a system to learn the current appearance of users in a non-supervised manner.
Research group on digital government in North America: developing a comparative and transnational agenda
Authors: J. Ramon Gil-Garcia, Luis F. Luna Reyes, Sehl Mellouli, Celene Navarrete, Theresa Pardo, Jing Zhang
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

This poster describes the second year's progress of the research group on Comparative and Transnational Digital Government in North America. This group was formed in 2007 to advance electronic government research across geographic and political boundaries in the region, with the support of the National Science Foundation Digital Government Research Program and the home institutions of the members in Canada, Mexico, and the United States. During the second year of activities, the group members joined their expertise and interests in two face-to-face meetings in Canada. During the second year of work, group members advanced research proposals and developed preliminary products on two topical areas as well as a first draft of a Research Agenda for North America. The group members will continue the discussion of this research agenda in Cholula, Mexico as part of the activities of the 10th Annual International Conference on Digital Government Research (dg.o 2009).
Making use of architecture throughout the software life cycle - How the build hierarchy can facilitate product line development
Authors: Hataichanok Unphon
Venue: Proceedings of the 2009 ICSE Workshop on Sharing and Reusing Architectural Knowledge (2009)

This paper presents an empirical study of how the application of genuine architecture can be employed beyond the design phase of product line development. The study is based on a co-operative research project with a company developing product line architecture for hydraulic modelling software. By concretising the architecture as a build hierarchy the architecture mediates the evolution of the design throughout the whole software life cycle. The empirical evidence has confirmed the improvements of (1) the software quality and flexibility, (2) the communication and cooperation with new developers, (3) the distribution of work and parallel implementation, and (4) the foreseen usage by hydraulic and environmental consultants who tailor the software. Our research further indicates requirements for the architectural analysis tools that are deliberately embedded in the daily development practices.
Understanding Decision Making in Cost Engineering Using Protocol Analysis
Authors: Oliver Houseman, Rajkumar Roy
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Previous theories describing the cost engineering process have been derived from prescriptive or descriptive analysis but there has been no empirical test of these theories. The protocol analysis techniques utilised in this study provide a method to inspect the cost engineering process at a cognitive level. A hypothesis describing the thinking process of a cost engineer is objectively tested using the results obtained from protocol analyses of cost engineers engaged in a detailed cost estimate. The hypothesis is objectively supported for the first time by these findings.
Combining Dimensional Analysis and Heuristics for Causal Ordering--In Memory of Dr Rob Milne --
Authors: Qiang Shen, Taoxin Peng
Venue: Proceeding of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer (2006)

This paper is a refined version of the work that the authors presented at the 13th International Workshop on Qualitative Reasoning, jointly with the late Dr Rob Milne. It is dedicated to Rob in recognition of his significant contribution and support for the research described herein. The paper presents a novel approach for generating causal dependencies between system variables, from an acausal description of the system behaviour, and for identifying the end causal impact, in terms of whether a change in the value of an influencing variable will lead to an increase or a decrease in the value of the influenced variables. This work is based on the use of the conventional method for dimensional analysis developed in classical physics, in conjunction with the exploitation of general heuristics. The utility of the work is demonstrated with its application to providing causal explanation for a benchmark problem that involves a dynamic feedback loop. The results reflect well the common-sense understanding of the causality in such a system that is otherwise difficult to capture using conventional causal ordering methods.
A WebGIS-based system for rainfall-runoff prediction and real-time water resources assessment for Beijing
Authors: Yangwen Jia, Hongli Zhao, Cunwen Niu, Yunzhong Jiang, Hong Gan, Zhi Xing, Xueli Zhao, Zhixin Zhao
Venue: Computers Geosciences (2009)

A WebGIS-based system designed to predict rainfall-runoff and assess real-time water resources for Beijing was developed to provide support for scientific decision making regarding solving water shortages while effectively reducing urban flood threats in the city. The system adopts a Browse Server (B/S) structure and combines the distributed hydrologic modeling and WebGIS techniques. For this system, a distributed hydrologic model of Beijing that adopts a grid cell-size of 1km by 1km and covers the city's entire area of 16,400km^2 was developed and validated. This model employs a simple, yet practical rainfall-runoff correlation curve method to predict runoff, as well as prediction approaches for rainfall, evaporation, subsurface runoff and recharge to groundwater. In addition, a framework for the assessment of real-time water resources assessment based on hydrologic monitoring stations and the distributed model was established. Finally, a WebGIS-based system for rainfall-runoff prediction and real-time water resources assessment for Beijing was developed by integrating a data platform, the professional models and the WebGIS techniques. This system was successfully integrated into the hydrologic prediction practices of the General Station of Hydrology, Bureau of Beijing Water Affairs in 2005, and the demonstration version of the system can be seen on the Web at http://123.127.143.23/enewRF/login/login.aspx?ReturnUrl=%2fenewRF%2ftemp.aspx.
Impact of Knowledge Support on the Performance of Software Process Tailoring
Authors: Peng Xu, Balasubramaniam Ramesh
Venue: Journal of Management Information Systems (2008)

The use of a well-defined process is a widely recognized approach to increasing quality and productivity in software development. Building software processes from scratch each time is expensive and risky. Therefore, they are often created by tailoring existing processes and standards. Process tailoring is a knowledge-intensive activity. This research explores the link between knowledge support and software process tailoring performance under different levels of tailoring task complexity. It theoretically develops and tests how the fit between knowledge (generalized and contextualized) and software tailoring task complexity influences process tailoring performance. Process tailoring performance is conceptualized in terms of effectiveness and efficiency. The results from an experiment and a protocol analysis show that contextualized knowledge outperforms generalized knowledge in improving tailoring performance, and that such improvement in performance is greater in complex process tailoring tasks when compared to simple tasks.