ppxscal/embedding_network huggingface dataset:
Adaptation of scalable multimedia documents
Authors: Benoît Pellan, Cyril Concolato
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

Several scalable media codecs have been standardized in recent years to cope with heterogeneous usage conditions and to aim at always providing audio, video and image content in the best possible quality. Today, interactive multimedia presentations are becoming accessible on handheld terminals and face the same adaptation challenges as the media elements they present: quite diversified screen, memory and processing power capabilities. In this paper, we address the adaptation of multimedia documents by applying the concept of scalability to their presentation. The Scalable MSTI document model introduced in this paper has been designed with two main requirements in mind. First, the adaptation process must be simple to execute because it may be performed on limited terminals in broadcast scenarios. Second, the adaptation process must be simple to describe so that authored adaptation directives can be transported along with the document with a limited bandwidth overhead. The Scalable MSTI model achieves both objectives by specifying Spatial, Temporal and Interactive scalability axes on which incremental authoring can be performed to create progressive presentation layers. Our experiments are conducted on scalable multimedia documents designed for Digital Radio services on DMB channels using MPEG-4 BIFS and also for web services using XHTML, SVG, SMIL and Flash. A scalable image gallery is described throughout this article and illustrates the features offered by our document model in a rich multimedia example.
Parameter Learning in Probabilistic Databases: A Least Squares Approach
Authors: Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc Raedt
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

We introduce the problem of learning the parameters of the probabilistic database ProbLog. Given the observed success probabilities of a set of queries, we compute the probabilities attached to facts that have a low approximation error on the training examples as well as on unseen examples. Assuming Gaussian error terms on the observed success probabilities, this naturally leads to a least squares optimization problem. Our approach, called LeProbLog, is able to learn both from queries and from proofs and even from both simultaneously. This makes it flexible and allows faster training in domains where the proofs are available. Experiments on real world data show the usefulness and effectiveness of this least squares calibration of probabilistic databases.
Heavy traffic analysis of maximum pressure policies for stochastic processing networks with multiple bottlenecks
Authors: Barış Ata, Wuqin Lin
Venue: Queueing Systems: Theory and Applications (2008)

A class of open processing networks operating under a maximum pressure policy is considered in the heavy traffic regime. We prove that the diffusion-scaled workload process for a network with several bottleneck resources converges to a semimartingale reflecting Brownian motion (SRBM) living in a polyhedral cone. We also establish a state space collapse result that the queue length process can be lifted from the lower-dimensional workload process.
The Next Step towards a Function Markup Language
Authors: Dirk Heylen, Stefan Kopp, Stacy C. Marsella, Catherine Pelachaud, Hannes Vilhjálmsson
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

In order to enable collaboration and exchange of modules for generating multimodal communicative behaviours of robots and virtual agents, the SAIBA initiative envisions the definition of two representation languages. One of these is the Function Markup Language (FML). This language specifies the communicative intent behind an agent's behaviour. Currently, several research groups have contributed to the discussion on the definition of FML. The discussion reveals agreement on many points but it also points out important issues that need to be dealt with. This paper summarises the current state of affairs in thinking about FML.
A Model for Requirements Change Management: Implementation of CMMI Level 2 Specific Practice
Authors: Mahmood Niazi, Charles Hickman, Rashid Ahmad, Muhammad Ali Babar
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

OBJECTIVE --- The objective of this research is to implement CMMI Level 2 specific practice --- SP 1.3-1 manage requirements changes. In this paper we have proposed a model for requirements change management and also discussed initial validation of this model. This model is based on both an empirical study that we have carried out and our extensive literature review of software process improvement (SPI) and requirements engineering (RE).METHOD --- For data collection we have interviewed SPI experts from reputed organisations. Further work includes analysing research articles, published experience reports and case studies. The initial evaluation of the model was performed via an expert review process.RESULTS --- Our model is based on five core elements identified from literature and interviews: request, validate, implement, verify and update. Within each of these elements we have identified specific activities that need to take place during requirements change management process.CONCLUSIONS --- The initial evaluation of the model shows that the requirements change management model is clear, easy to use and can effectively manage the requirements change process. However, more case studies are needed to evaluate this model in order to further evaluate its effectiveness in the domain of RE process.
A Code Generation Framework for Actor-Oriented Models with Partial Evaluation
Authors: Gang Zhou, Man-Kit Leung, Edward A. Lee
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

Embedded software requires concurrency formalisms other than threads and mutexes used in traditional programming languages like C. Actor-oriented design presents a high level abstraction for composing concurrent components. However, high level abstraction often introduces overhead and results in slower system. We address the problem of generating efficient implementation for the systems with such a high level description. We use partial evaluation as an optimized compilation technique for actor-oriented models. We use a helper-based mechanism, which results in flexible and extensible code generation framework. The end result is that the benefit offered by high level abstraction comes with (almost) no performance penalty. The code generation framework has been released in open source form as part of Ptolemy II 6.0.1.
Zero-intelligence agents in prediction markets
Authors: Abraham Othman
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

We construct a novel agent-based model of prediction markets in which putative human qualities like learning, reasoning, and profit-seeking are absent. We show that the prices which emerge from a market populated by a class of distinctly inhuman agents, Zero-Intelligence agents with diffuse beliefs, replicate the findings of empirical market studies. We use this result to argue against the prevailing descriptive theories of price formation in prediction markets, which have stressed the role of expert, rational participants.
A hierarchical learning network for face detection with in-plane rotation
Authors: Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Venue: Neurocomputing (2008)

This paper presents a scale and rotation invariant face detection system. The system employs a hierarchical neural network, called SICoNNet, whose processing elements are governed by the nonlinear mechanism of shunting inhibition. The neural network is used as a face/nonface classifier that can handle in-plane rotated patterns. To train the network as a rotation invariant face classifier, an enhanced bootstrap training technique is developed, which prevents bias towards the nonface class. Furthermore, a multiresolution processing is employed for scale invariance: an image pyramid is formed through sub-sampling and face detection is performed at each scale of the pyramid using an adaptive threshold. Evaluated on the benchmark CMU rotated face database, the proposed face detection system outperforms some of the existing rotation invariant face detectors; it has fewer false positives and higher detection accuracy.
Prospecting the Appropriation of the Digital TV in a Brazilian Project
Authors: Elizabeth Furtado, Thais Kampf, Lara Piccolo, Maria Cecília Baranauskas
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

A good practice for developers of a new technology, which has great influence on the life of interested users (as in the case of the Digital TV), would be to: inform them about the benefits of the technology and challenges for its appropriation. Usually the focus of works that investigate the appropriation of Digital TV has been on avoiding the non acceptance of users towards usability and accessibility issues. This work presents other risks related to the non acceptance, influenced by the way the technology will be owned, by the topology of the city and by the life style of the population. Human and contextual factors help to overcome the non acceptance of users and give rise to some recommendations useful for the developers of this technology to mitigate such risks.
Multi-query Optimization for Distributed Similarity Query Processing
Authors: Yi Zhuang, Qing Li, Lei Chen
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

This paper considers a multi-query optimization issue for distributed similarity query processing, which attempts to exploit the dependencies in the derivation of a query evaluation plan. To the best of our knowledge, this is the first work investigating a multi- query optimization technique for distributed similarity query processing (MDSQ). Four steps are incorporated in our MDSQ algorithm. First when a number of query requests(i.e., m query vectors and m radiuses) are simultaneously submitted by users, then a cost-based dynamic query scheduling(DQS) procedure is invoked to quickly and effectively identify the correlation among the query spheres (requests). After that, an index-based vector set reduction is performed at data node level in parallel. Finally, a refinement process of the candidate vectors is conducted to get the answer set. The proposed method includes a cost-based dynamic query scheduling, a Start-Distance(SD)-based load balancing scheme, and an index-based vector set reduction algorithm. The experimental results validate the efficiency and effectiveness of the algorithm in minimizing the response time and increasing the parallelism of I/O and CPU.
A User Interface Level Context Model for Ambient Assisted Living
Authors: Manfred Wojciechowski, Jinhua Xiong
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

Within Ambient Assisted Living (AAL) context awareness is an important feature of intelligent user assisting services. In this domain different requirements regarding context modeling can be identified that are not in the focus of current context models. One important aspect is the support of an end user interface for describing context dependent service behaviour. An inhabitant of a smart home needs to get and give feedback on context in a way that can be understood and handled without context modeling expertise. At the same time such simplified context description must be matched on the technical details of context sensing and context dependent service adaptivity. In this paper we introduce a layered context model for AAL which provides different abstraction levels. Therein we focus on model elements and concepts on the user interface layer.
An Accessible Viewer for Digital Comic Books
Authors: Christophe Ponsard, Vincent Fries
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

In many countries, "comic books" are very popular and are sometimes are referred to as the ninth art. The most common form of access to comics still remains the paper form. Despite its reading comfort, this media does not fit the use the navigational needs of a number of people with special needs, for example: motor-impaired people, low-sighted people and mobile users.In this paper, we explore how an electronic version of comics can be accessed optimally using a computer based interface. Among the reading modes supported, an automated mode provides a segmentation-based detection of panel boundaries and their display in the right reading order. This enables accessibility with minimal user interaction and maximal image size. Validation was carried out in a number of operational contexts such as a PC controlled through voice, a TV controlled through a remote and a mobile device.
Multi-physics and Multi-scale Modelling in Cardiovascular Physiology: Advanced User Methods for Simulation of Biological Systems with ANSYS/CFX
Authors: V. Díaz-Zuccarini, D. Rafirou, D. R. Hose, P. V. Lawford, A. J. Narracott
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

This work encompasses together a number of diverse disciplines (physiology, biomechanics, fluid mechanics and simulation) in order to develop a predictive model of the behaviour of a prosthetic heart valve in vivo. The application of simulation, for the study of other cardiovascular problems, such as blood clotting is also discussed. A commercial, finite volume, computational fluid dynamics (CFD) code (ANSYS/CFX) is used for the 3D component of the model. This software provides technical options for advanced users which allow user-specific variables to be defined that will interact with the flow solver. User-defined functions and junction boxes offer appropriate options to facilitate multi-physics and multi-scale complex applications. Our main goal is to present a 3D model using the internal features available in ANSYS/CFX coupled to a multiscale model of the left ventricle to address complex cardiovascular problems.
ZoneTag's Collaborative Tag Suggestions: What is This Person Doing in My Phone?
Authors: Mor Naaman, Rahul Nair
Venue: IEEE MultiMedia (2008)

We describe ZoneTag, a camera phone application that allows users to capture, annotate, and share photos directly from their phone.
Does the linear size adjustment to estimated effort improve web applications effort estimation accuracy?
Authors: Emilia Mendes, Nile Mosley
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

Over the last 16 years, and particularly over the last 8 years, Analogy-based effort estimation has been used to estimate effort for software projects and in several studies has presented comparable estimation accuracy to, or better than, algorithmic methods. The Analogy technique is also potentially easier to understand and apply by both researchers and practitioners. These two factors suggest that this technique has great potential as an effort estimation technique to be used within Companies. However, there are still several challenges, in particular regarding the type of effort adaptation to use in order to obtain the highest prediction accuracy, that need further investigation. Therefore this paper compares several methods of Analogy-based effort estimation and investigates the use of adaptation rules as a contributing factor to better estimation accuracy. Two datasets are used in the analysis; results show that the best predictions are obtained for the dataset that first, presents a continuous "cost" function, translated as a strong linear relationship between size and effort, and second, is more "intact" in terms of outliers and collinearity. Only one of the two types of adaptation rules employed generated good predictions.
Context Information for Understanding Forest Fire Using Evolutionary Computation
Authors: L. Usero, A. Arroyo, J. Calvo
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

One of the major forces for understanding forest fire risk and behavior is the fire fuel. Fire risk and behavior depend on the fuel properties such as moisture content. Context information on vegetation water content is vital for understanding the processes involved in initiation and propagation of forest fires. In that sense, a novel method was tested to estimate vegetation canopy water content (CWC) from simulated MODIS satellite data. An inversion of a radiative transfer model called Forest Light Interaction-Model (FLIM) from performed using evolutionary computation. CWC is critical, among other applications, in wildfire risk assessment since a decrease in CWC causes higher probability to have wildfire occurrence. Simulations were carried out with the FLIM model for a wide range of forest canopy characteristics and CWC values. A 50 subsample of the simulations was used for the training process and 50 for the validation providing a RMSE=0.74 and r2=0.62. Further research is needed to apply this method on real MODIS images.
"Zen" and the art of petascale ocean modeling: a conceptual analysis of how virtualization could be key to bringing individual science back to petascale ocean modeling
Authors: Chris Hill, Larry Rudolph
Venue: Proceedings of the 2nd workshop on System-level virtualization for high performance computing (2008)

We speculate on a novel role virtualization could play in creating a rounded, balanced physical science and engineering software ecosystem to support petascale computational science. The motivation for this analysis is a quest for ways to engage a broader spectrum of expertise in state-of-the-art petascale modeling activities. Current generation petascale efforts are based around massively parallel systems with greater than 50,000 cores. This presents a considerable challenge to typical computational science and engineering application analysis and development practices. To illustrate the challenge we examine an ocean model deployed on a recently commissioned &ap;60,000 core parallel system. This case study demonstrates interesting science and engineering challenges that many advanced simulations on petascale systems will face. We then describe a methodology, amenable to virtualization technology at various levels, that mitigates key aspects of the challenges outlined for a potentially broad class of applications.
Tree Automata for Non-linear Arithmetic
Authors: Naoki Kobayashi, Hitoshi Ohsaki
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

Tree automata modulo associativity and commutativity axioms, called AC tree automata, accept trees by iterating the transition modulo equational reasoning. The class of languages accepted by monotone AC tree automata is known to include the solution set of the inequality $x \times y \geqslant z$, which implies that the class properly includes the AC closure of regular tree languages. In the paper, we characterize more precisely the expressiveness of monotone AC tree automata, based on the observation that, in addition to polynomials, a class of exponential constraints (called monotone exponential Diophantine inequalities) can be expressed by monotone AC tree automata with a minimal signature. Moreover, we show that a class of arithmetic logic consisting of monotone exponential Diophantine inequalities is definable by monotone AC tree automata. The results presented in the paper are obtained by applying our novel tree automata technique, called linearly bounded projection.
A New Chinese Speech Synthesis Method Apply in Chinese Poetry Learning
Authors: Chengsong Zhu, Yaoting Zhu
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

This paper describes a new Chinese speech synthesis method apply in Chinese poetry teaching and learning, which focus on the prosody of syllables and words in Chinese poetry. As the word is a key semantic unit for Chinese poetry, we concentrate on Chinese word prosody and propose a speech synthesis method, which consider the appearance with the essence of human voice, use the homomorphism analysis over the time domain analysis to make the synthesized speech between syllables in a Chinese word sounds more natural. The prosody model of the method, however comply with the reading rules of Chinese poetry, make the user to learn Chinese poetry more convenient from the acoustic perception level.
Energy Normalization in Automatic Speech Recognition
Authors: Nikša Jakovljević, Marko Janev, Darko Pekar, Dragiša Mišković
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

In this paper a novel method for energy normalization is presented. The objective of this method is to remove unwanted energy variations caused by different microphone gains, various loudness levels across speakers, as well as changes of single speaker loudness level over time. The solution presented here is based on principles used in automatic gain control. The use of this method results in relative improvement of the performances of an automatic speech recognition system by 26 %.
Supporting Reasoning and Problem-Solving in Mathematical Generalisation with Dependency Graphs
Authors: Sergio Gutiérrez, Darren Pearce, Eirini Geraniou, Manolis Mavrikis
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

We present a brief description of the design of a diagram- based system that supports the development of thinking about mathematical generalisation. Within the software, the user constructs a dependency graph that explicitly shows the relationships between components of a task. Using this dependency graph, the user manipulates graphical visualisations of component attributes which helps them move from the specific case to the general rule. These visualisations provide the user with an intermediate representation of generality and facilitate movement between the specific details of the task, the appropriate generalisations, verbal descriptions of their understanding and various algebraic representations of the solutions.
A neural network-based approach for an assembly cell control
Authors: Y. Touati, Y. Amirat, N. Saadia, A. Ali-Chérif
Venue: Applied Soft Computing (2008)

In several robotics applications, the robot must interact with the workspace, and thus its motion is constrained by the task. In this case, pure position control will be ineffective since forces appearing during the contacts must also be controlled. However, simultaneous position and force control called hybrid control is then required. Moreover, the nonlinear plant dynamics, the complexity of the dynamic parameters determination and computation constraints makes more difficult the synthesis of control laws. In order to satisfy all these constraints, an effective hybrid force/position approach based on artificial neural networks for multi-inputs/multi-outputs systems is proposed. This approach realizes, simultaneously, an identification and control of systems, and it is implemented according to two phases: At first, a neural observer is trained off-line on the basis of the data acquired during contact motion, in order to realize a smooth transition from free to contact motion. Then, an online learning of the neural controller is implemented using neural observer parameters so that the closed-loop system maintains a good performance and compensates for uncertain/unknown dynamics of the robot and the environment. A typical example on which we shall focus is an assembly task. Experimental results on a C5 links parallel robot demonstrate that the robot's skill improves effectively and the force control performances are satisfactory, even if the dynamics of the robot and the environment change.