ppxscal/embedding_network huggingface dataset:
Relevence Assessment of Topic Ontology
Authors: Xujuan Zhou, Yuefeng Li, Yue Xu, Raymond Lau
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

In traditional Information Retrieval (IR), user profiles are often represented by keyword/concepts space vectors or by some predefined categories. Unfortunately, this data is often inadequately or incompletely interpreted. Ontology-based user profile is another newer approach. This method is able to provide richer semantic information to facilitate information retrieval processes. It has become an important means for semantic-based information search and retrieval. Some ontology-based user profile models have been developed over the past few years. With the increasing usage of this method, it raises the issues of effective relevance measurement for the evaluation of ontologies. In practice, it is crucial to find a good relevance assessment algorithm for measuring the quality of ontologies. To represent user profile by relevant topic ontology, this paper presents a new method capable of measuring the user profile more objectively and hence has great potential to enhance the IR processes.
A Random Network Ensemble for Face Recognition
Authors: Kwontaeg Choi, Kar-Ann Toh, Hyeran Byun
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

In this paper, we propose a random network ensemble for face recognition problem, particularly for images with a large appearance variation and with a limited number of training set. In order to reduce the correlation within the network ensemble using a single type of feature extractor and classifier, localized random facial features have been constructed together with internally randomized networks. The ensemble classifier is finally constructed by combining these multiple networks via a sum rule. The proposed method is shown to have a better accuracy(31.5% and 15.3% improvements on AR and EYALEB databases respectively) and a better efficiency than that of the widely used PCA-SVM.
Cooperative Aspect Oriented Programming for executable business processes
Authors: Chiara Di Francescomarino, Paolo Tonella
Venue: Proceedings of the 2009 ICSE Workshop on Principles of Engineering Service Oriented Systems (2009)

AO4BPEL applied Aspect Oriented Programming to executable business processes. Although modularized, AO4BPEL aspects do not have an explicit interface and the implicit one, based on XPath, is often fragile, hence reusing aspects in different processes is quite hard. Cooperative Aspect Oriented Programming aims at making aspects reusable by means of cooperative work between base code and aspects, realized by increasing the explicit awareness of aspects at the expense of pure obliviousness. This work investigates the use of Cooperative Aspect Oriented Programming with BPEL processes.
Binary classification using ensemble neural networks and interval neutrosophic sets
Authors: Pawalai Kraipeerapun, Chun Che Fung
Venue: Neurocomputing (2009)

This paper presents an ensemble neural network and interval neutrosophic sets approach to the problem of binary classification. A bagging technique is applied to an ensemble of pairs of neural networks created to predict degree of truth membership, indeterminacy membership, and false membership values in the interval neutrosophic sets. In our approach, the error and vagueness are quantified in the classification process as well. A number of aggregation techniques are proposed in this paper. We applied our techniques to the classical benchmark problems including ionosphere, pima-Indians diabetes, and liver-disorders from the UCI machine learning repository. Our approaches improve the classification performance as compared to the existing techniques which applied only to the truth membership values. Furthermore, the proposed ensemble techniques also provide better results than those obtained from only a single pair of neural networks.
A Hierarchical Scheme for Rapid Video Copy Detection
Authors: Xiao Wu, Yongdong Zhang, Sheng Tang, Tian Xia, Jintao Li
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Today with the rapid increasing popularity of web video sharing, digital copyright protection encounters many troubles. Video copy detection schemes are emerging to cope with the digital video piracy and illegal distribution problems. But the large amount of video data and diversity of copy attacks pose difficulties on copy detection. This paper presents a hierarchical scheme to detect video copies, especially the temporal attacked and re-encoded ones. Our algorithm which is based on the ordinal signature of intra frames and effective R*-Tree indexing structure archives real time performance. Comparison experiments are conducted on the benchmarked database of CIVR 2007 copy detection showcase and demonstrate the promising results of the proposed approach.
The theoretical fundamentals of learning theory based on fuzzy complex random samples
Authors: Minghu Ha, Witold Pedrycz, Lifang Zheng
Venue: Fuzzy Sets and Systems (2009)

Statistical learning theory based on real-valued random samples has been regarded as one of the influential developments for small samples statistical estimation and learning. The key theorem of learning theory and the bounds on the rate of convergence of learning process are the most important theoretical fundamentals of the statistical learning theory. In this paper, we discuss a statistical learning theory based on fuzzy complex random samples. Firstly, the definition of fuzzy complex numbers is introduced and the fuzzy complex random variables along with their numeric characteristic are investigated. Secondly, we carry out further research focused on a special type of fuzzy complex number, namely rectangular fuzzy complex number and establish some properties and develop important theorems. We also prove the strong law of large numbers based on fuzzy complex random variables. Thirdly, the definitions of the fuzzy complex expected risk functional, the fuzzy complex empirical risk functional, the fuzzy complex empirical risk minimization principle and the consistency are provided and discussed. Finally, the key theorem of learning theory and the bounds on the rate of convergence of learning process based on fuzzy complex random samples are discussed.
A Novel Method for Power Saving in a Surveillance Environment
Authors: Souvik Sen, Amit Kumar Das
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

In this paper we propose a smart video surveillance system with real-time moving object (primarily human) detection and identification for solving the problem of excessive power consumption in a public place like shopping malls. The proposed detection system is able to handle several known constraints such as changing illumination conditions, occlusion, clutter or even irrelevent extrancous motion. It keeps track of the number of humans in the vicinity and take measures depending on the number of people within its sight. As the number of humans in the neighbourhood increases the system takes steps to gradually increase the luminosity of the area. Again, when there are a few or no individuals in the area the brightness of the area is gradually decreased. Moreover it keeps track of the members of the working staff, who generally dresses in a fixed uniform, to save power bu tuning the lighting to an adequate but not a dazzling level.
Portfolio management using value at risk: A comparison between genetic algorithms and particle swarm optimization
Authors: V. A. F. Dallagnol, J. van den Berg, L. Mous
Venue: International Journal of Intelligent Systems (2009)

In this paper, it is shown a comparison of the application of particle swarm optimization and genetic algorithms to portfolio management, in a constrained portfolio optimization problem where no short sales are allowed. The objective function to be minimized is the value at risk calculated using historical simulation where several strategies for handling the constraints of the problem were implemented. The results of the experiments performed show that, generally speaking, the methods are capable of consistently finding good solutions quite close to the best solution found in a reasonable amount of time. In addition, it is demonstrated statistically that the algorithms, on average, do not all consistently achieve the same best solution. PSO turned out to be faster than GA, both in terms of number of iterations and in terms of total running time. However, PSO appears to be much more sensitive to the initial position of the particles than GA. Tests were also made regarding the number of particles needed to solve the problem, and 50 particles-chromosomes seem to be enough for problems up to 20 assets. &copy; 2009 Wiley Periodicals, Inc.
Modeling evolutionary fitness for DNA motif discovery
Authors: Sven Rahmann, Tobias Marschall, Frank Behler, Oliver Kramer
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

The motif discovery problem consists of finding over-represented patterns in a collection of sequences. Its difficulty stems partly from the large number of possibilities to define both the motif space to be searched and the notion of over-representation. Since the size of the search space is generally exponential in the motif length, many heuristic methods, including evolutionary algorithms, have been developed. However, comparatively little attention has been devoted to the adequate evaluation of motif quality, especially when comparing motifs of different lengths. We propose an evolution strategy to solve the motif discovery problem based on a new fitness function that simultaneously takes into account (1) the number of motif occurrences, (2) the motif length, and (3) its information content. Experimental results show that the proposed method succeeds in uncovering the correct motif positions and length with high accuracy.
Development of a single-layer finite element and a simplified finite element modeling approach for constrained layer damped structures
Authors: Zhengchao Xie, W. Steve Shepard,  Jr.
Venue: Finite Elements in Analysis and Design (2009)

A new finite element (FE) is formulated based on an extension of previous FE models for studying constrained layer damping (CLD) in beams. Most existing CLD FE models are based on the assumption that the shear deformation in the core layer is the only source of damping in the structure. However, previous research has shown that other types of deformation in the core layer, such as deformations from longitudinal extension, and transverse compression, can also be important. In the finite element formulated here, shear, extension, and compression deformations are all included. As presented, there are 14 degrees of freedom in this element. However, this new element can be extended to cases in which the CLD structure has more than three layers. The numerical study shows that this finite element can be used to predict the dynamic characteristics accurately. However, there is a limitation when the core layer has a high stiffness, as the new element tends to predict loss factors and natural frequencies that are too high. As a result, this element can be accepted as a general computation model to study the CLD mechanism when the core layer is soft. Because the element includes all three types of damping, the computational cost can be very high for large scale models. Based on this consideration, a simplified finite modeling approach is presented. This approach is based on an existing experimental approach for extracting equivalent properties for a CLD structure. Numerical examples show that the use of these extracted properties with commercially available FE models can lead to sufficiently accurate results with a lower computational expense.
Band offsets at interfaces of (100)InxGa1-xAs (0≤x≤0.53) with Al2O3 and HfO2
Authors: V. V. Afanas'ev, A. Stesmans, G. Brammertz, A. Delabie, S. Sionke, A. O'Mahony, I. M. Povey, M. E. Pemble, E. O'Connor, P. K. Hurley, S. B. Newcomb
Venue: Microelectronic Engineering (2009)

The electron energy band alignment at interfaces of In"xGa"1"-"xAs (0=
Network-Wide Measurements of TCP RTT in 3G
Authors: Peter Romirer-Maierhofer, Fabio Ricciato, Alessandro D'Alconzo, Robert Franzan, Wolfgang Karner
Venue: Proceedings of the First International Workshop on Traffic Monitoring and Analysis (2009)

In this study we present network-wide measurements of Round-Trip-Time (RTT) from an operational 3G network, separately for GPRS/EDGE and UMTS/HSxPA sections. The RTTs values are estimated from passive monitoring based on the timestamps of TCP handshaking packets. Compared to a previous study in 2004, the measured RTT values have decreased considerably. We show that the network-wide RTT percentiles in UMTS/HSxPA are very stable in time and largely independent from the network load. Additionally, we present separate RTT statistics for handsets and laptops, finding that they are very similar in UMTS/HSxPA. During the study we identified a problem with the RTT measurement methodology -- mostly affecting GPRS/EDGE data -- due to early retransmission of SYNACK packets by some popular servers.
Monitoring process mean and variability with generally weighted moving average control charts
Authors: Shey-Huei Sheu, Shih-Hung Tai, Yu-Tai Hsieh, Tse-Chieh Lin
Venue: Computers and Industrial Engineering (2009)

This study investigates control charts for simultaneous monitoring of process mean and process variability when an individual observation is taken at each sampling point. A combined scheme consisting of a two-side generally weighted moving average (GWMA) mean chart and a two-side GWMA variance chart is developed. This new combined scheme will compare with the exponentially weighted moving average (EWMA) single charts and a combined EWMA chart. It is shown that the combination of the GWMA charts is more sensitive than the combination of the EWMA charts for detecting small shifts in the process mean and variance. An example and a simple procedure for the design of a combined GWMA chart are also given to illustrate this study.
Technology and Teaching: Making the Right Choices
Authors: H. Muir, C. Dudley, K. Nakazawa
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This paper describes the key role the design and employment of a suite of Technology Evaluation Tools (TET) played in the development of a whole of discipline approach to Information and Communication Technology Supported Teaching. In partnership with the university's Institute of Higher Education Research and Development, a set of Technology Evaluation Tools was developed that assisted in ensuring that any technology chosen for inclusion in our teaching programs would serve the program and the students well. This paper discusses the project and some of its outcomes.
Finding compact structural motifs
Authors: Dongbo Bu, Ming Li, Shuai Cheng Li, Jianbo Qian, Jinbo Xu
Venue: Theoretical Computer Science (2009)

Protein structural motif detection has important applications in structural genomics. Compared with sequence motifs, structural motifs are more sensitive in revealing the evolutionary relationships among proteins. A variety of algorithms have been proposed to attack this problem. However, they are either heuristic without theoretical performance guarantee, or inefficient due to employing exhaustive search strategies. This paper studies a reasonably restricted version of this problem: the compact structural motif problem. We prove that this restricted version is still NP-hard, and we present a polynomial-time approximation scheme to solve it. This is the first approximation algorithm with a guaranteed ratio for the protein structural motif problem.
Decision support for caregivers through embedded capture and access
Authors: Gregory D. Abowd
Venue:  (2008)

The care of individuals with concerns about development, health, and wellness is often a difficult, complicated task and may rely on a team of diverse caregivers. There are many decisions that caregivers must make to help ensure that the best care and health monitoring are administered. For my dissertation work, I have explored the use of embedded capture and access to support decision-making for caregivers. Embedded capture and access integrates simple and unobtrusive capture and useful access, including trending information and rich data, into existing work practices. I hypothesized that this technology encourages more frequent access to evidence, increased collaboration amongst caregivers, and decisions made with higher confidence.I have explored this technology through real-world deployments of new embedded capture and access applications in two domains. For the first domain, I have developed two applications to support decision-making for caregivers administering therapy to children with autism. The first application, Abaris, supports therapists working with a single child in a home setting, and the second application, Abaris for Schools, extends the ideas of Abaris for use in a school setting for many teachers working with multiple children. The second domain I have explored is decision-making for parents of newborn children. In particular, I developed and evaluated embedded capture and access technology to support parents, pediatricians, and secondary childcare providers in making decisions about whether a child&rsquo;s development is progressing normally in order to promote the earlier detection of developmental delays.
Games with a purpose for social networking platforms
Authors: Walter Rafelsberger, Arno Scharl
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

The online games market has matured in recent years. It is now a multi-billion dollar business with hundreds of millions players worldwide. At the same time, social networking platforms have witnessed unprecedented growth rates and increasingly offer developer interfaces to leverage and extend their built-in core functionality. Benefiting from these trends, games with a purpose are a proven way of leveraging the wisdom of the crowds to address tasks that are trivial for humans but still not solvable by computer algorithms in a satisfying manner. This paper presents an application framework to develop interactive games with a purpose on top of social networking platforms, suitable for deployment in both mobile and Web-based environments. A set of analytic tools helps to evaluate the results and to pre-process the gathered data for use in external applications.
Pendaphonics: an engaging tangible pendulum-based sonic interaction experience
Authors: Anne-Marie Skriver Hansen, Dan Overholt, Winslow Burleson, Camilla Nørgaard Jensen, Byron Lahey, Kasia Muldner
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

Pendaphonics is a tangible physical-digital-sonic environment and interactive system that motivates children and adults to be physically active and explorative. The development of this system presents a strategy for the design and evaluation of a low-cost, flexible, large scale tangible system that is engaging for children and adults alike. Pendaphonics has been installed in a public new media arts space, where over 200 people have interacted with it. Here, we describe Pendaphonics tangible interaction scenarios, including the broad potential of this system as a compositional and choreographic tool, an educational exhibit, and as an interface that facilitates playful interaction, exploration, discovery and creativity.
Intersection and Signed-Intersection Kernels for Intervals
Authors: Francisco J. Ruiz, Cecilio Angulo, Núria Agell
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

In this paper two kernels for interval data based on the intersection operation are introduced. On the one hand, it is demonstrated that the intersection length of two intervals is a positive definite (PD) kernel. On the other hand, a signed variant of this kernel, which also permits discriminating between disjoint intervals, is demonstrated to be a conditionally positive definite (CPD) kernel. The potentiality and performance of the two kernels presented when applying them to learning machine techniques based on kernel methods are shown by considering three different examples involving interval data.
Generating usable formats for metadata and annotations in a large meeting corpus
Authors: Andrei Popescu-Belis, Paula Estrella
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

The AMI Meeting Corpus is now publicly available, including manual annotation files generated in the NXT XML format, but lacking explicit metadata for the 171 meetings of the corpus. To increase the usability of this important resource, a representation format based on relational databases is proposed, which maximizes informativeness, simplicity and reusability of the metadata and annotations. The annotation files are converted to a tabular format using an easily adaptable XSLT-based mechanism, and their consistency is verified in the process. Metadata files are generated directly in the IMDI XML format from implicit information, and converted to tabular format using a similar procedure. The results and tools will be freely available with the AMI Corpus. Sharing the metadata using the Open Archives network will contribute to increase the visibility of the AMI Corpus.
Relationship Discovery Ontology in Asymmetric Warfare
Authors: Kofi Apenyo
Venue: Proceeding of the 2008 conference on Formal Ontologies Meet Industry (2008)

Nowadays, with battles increasingly being fought in urban theaters, enemy combatants can include not only the military but also pseudo-military forces and the civilian population. Given the new battlespace and the realities of the Information Age, military intelligence needs to be processed in new ways in order “to know the enemy”. Just as data models and information systems such as the Joint Consultation Command & Control Information Exchange Data Model and the Blue Force Situational Awareness System provide support for the traditional military, novel information systems that capture enemy force and command structure must be built and utilized to achieve information superiority in asymmetric warfare. An information system with a core of the relationships among humans, relationships among organizations, and relationships among humans and organizations is postulated to improve the commander's understanding of enemy presence in his area of operations. Accordingly, this paper develops a relationship discovery ontology from basic modeling principles and then presents a prototype system built on the Protégé ontology engine. The prototype, populated with synthesized but representative human intelligence messages, has been used to demonstrate that a commander may obtain actionable intelligence to capture adversaries and preempt potential enemy attacks. The author validated the ontology model by comparison with concepts from other technologies, by mapping human intelligence messages to model concepts and properties, and by demonstrating the functionality of the prototype.