ppxscal/embedding_network huggingface dataset:
The left posterior superior temporal gyrus participates specifically in accessing lexical phonology
Authors: William W. Graves, Thomas J. Grabowski, Sonya Mehta, Prahlad Gupta
Venue: Journal of Cognitive Neuroscience (2008)

Impairments in phonological processing have been associated with damage to the region of the left posterior superior temporal gyrus (pSTG), but the extent to which this area supports phonological processing, independent of semantic processing, is less clear. We used repetition priming and neural repetition suppression during functional magnetic resonance imaging (fMRI) in an auditory pseudoword repetition task as a semantics-free model of lexical (whole-word) phonological access. Across six repetitions, we observed repetition priming in terms of decreased reaction time and repetition suppression in terms of reduced neural activity. An additional analysis aimed at sublexical phonology did not show significant effects in the areas where repetition suppression was observed. To test if these areas were relevant to real word production, we performed a conjunction analysis with data from a separate fMRI experiment which manipulated word frequency (a putative index of lexical phonological access) in picture naming. The left pSTG demonstrated significant effects independently in both experiments, suggesting that this area participates specifically in accessing lexical phonology.
Two-dimensional ultrasonic anemometer using the directivity angle of an ultrasonic sensor
Authors: Dongwoo Han, Sunghyun Kim, Sekwang Park
Venue: Microelectronics Journal (2008)

There has been continuous research on the ultrasonic sensors [L.C. Lynnworth, Y. Liu, Ultasonic flowmeters: half-century progress report 1955-2005, Ultrasonics (2006) 1371-1378]. This study used the directivity characteristic based on phase measurement, which ultrasonic sensor has. Transmitter has wide directivity, and in its range of directivity, receivers are located to measure wind direction and velocity. The velocity experiments which are the result of this production system indicate that the system error rate is 2%. The wind direction measurements also give the same result, an error of +/-3^o. This result is similar to existing anemometers. However, this new anemometer could possibly have a much higher sampling rate, operating circuit and system structure, which could be much simpler than the previous anemometer.
A Self-Test to Detect a Heart Attack Using a Mobile Phone and Wearable Sensors
Authors: Peter Leijdekkers, Valérie Gay
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

This paper describes a heart attack self-test application for a mobile phone that allows potential victims, without the intervention of a medical specialist, to quickly assess whether they are having a heart attack. Heart attacks can occur anytime and anywhere. Using pervasive technology such as a mobile phone and a small wearable ECG sensor it is possible to collect the user's symptoms and to detect the onset of a heart attack by analysing the ECG recordings. If the application assesses that the user is at risk, it will urge the user to call the emergency services immediately. If the user has a cardiac arrest the application will automatically determine the current location of the user and alert the ambulance services and others to the person's location.
Neuro-discriminate Model for the Forecasting of Changes of Companies Financial Standings on the Basis of Self-organizing Maps
Authors: Egidijus Merkevičius, Gintautas Garšva, Rimvydas Simutis
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This article presents the way how creditor can predict the trends of debtors financial standing. We propose the model for forecasting changes of financial standings. Model is based on the Self-organizing maps as a tool for prediction, grouping and visualization of large amount of data. Inputs for training of SOM are financial ratios calculated according any discriminate bankruptcy model. Supervised neural network lets automatically increase accuracy of performance via changing of weights of ratios.
Using MPEG-7 and MPEG-21 for Personalizing Video
Authors: Belle L. Tseng, Ching-Yung Lin, John R. Smith
Venue: IEEE MultiMedia (2004)

As multimedia content has proliferated over the past several years, users have begun to expect that content be easily accessed according to their own preferences. One of the most effective ways to do this is through using the MPEG-7 and MPEG-21 standards, which can help address the issues associated with designing a video personalization and summarization system in heterogeneous usage environments.
Internet governance on a dollar a day
Authors: Charles Kenny
Venue: Information Polity (2007)

The submissions of ICANN and ISOC to the WSIS suggested Internet governance was purely about technical standardisation, addresses, domains and some service-related issues. Under this definition, there is little for poor people to worry about. At the same time, the term 'Internet governance' in an era of convergence is perhaps particularly unhelpful in the context of developing countries and especially poor people in those countries. It is in the nature of a global network such as information infrastructure that there are a number of global governance issues. These should receive due attention. But it is worth noting that, especially regarding the information needs of poor people worldwide, the most important governance issues remain at the national level, where there is a considerable reform agenda. Indeed, to some extent what is most urgently required is less governance and different governance.
Open Domain Recommendation: Social Networks and Collaborative Filtering
Authors: Sarah K. Tyler, Yi Zhang
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Commercial enterprises employ data mining techniques to recommend products to their customers. Most of the prior research is usually focused on a specific domain such as movies or books, and recommendation algorithms using similarities between users and/or similarities between products usually performs reasonably well. However, when the domain isn't as specific, recommendation becomes much more difficult, because the data could be too sparse to find similar users or similar products based on purchasing history alone. To solve this problem, we propose using social network data, along with rating history to enhance product recommendations. This paper exploits the state of art collaborative filtering algorithm and social net based recommendation algorithm for the task of open domain recommendation. We show that when a social network can be applied, it is a strong indicator of user preference for product recommendations. However, the high precision is achieved at the cost of recall. Although the sparseness of the data may suggest that the social network is not always applicable, we present a solution to utilize the network in these cases.
Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation
Authors: Marco Signoretto, Kristiaan Pelckmans, Johan A. Suykens
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this contribution we consider the problem of regression estimation. We elaborate on a framework based on functional analysis giving rise to structured models in the context of reproducing kernel Hilbert spaces. In this setting the task of input selection is converted into the task of selecting functional components depending on one (or more) inputs. In turn the process of learning with embedded selection of such components can be formalized as a convex-concave problem. This results in a practical algorithm that can be implemented as a quadratically constrained quadratic programming (QCQP) optimization problem. We further investigate the mechanism of selection for the class of linear functions, establishing a relationship with LASSO.
`O Francesca, ma che sei grulla?' Emotions and Irony in Persuasion Dialogues
Authors: Irene Mazzotta, Nicole Novielli, Vincenzo Silvestri, Fiorella Rosis
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

In this paper we investigate the interaction between emotional and non-emotional aspects of persuasion dialogues, from the viewpoint of both the system (the Persuader), when reasoning on the persuasion attempt, and the user (the Receiver), when reacting to it. We are working on an Embodied Conversational Agent (ECA) which applies natural argumentation techniques to persuade users to improve their behaviour in the healthy eating domain. The ECA observes the user's attitude during the dialogue, so as to select an appropriate persuasion strategy or to respond intelligently to user's reactions to suggestions received. We grounded our work on the analysis of two corpora: a corpus of `natural' persuasion examples and a corpus of user's reactions to persuasion attempts.
A Trusted Group Signature Architecture in Virtual Computing Environment
Authors: Deqing Zou, Yunfa Li, Song Wu, Weizhong Qiang
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

Nowadays coordinated applications become more and more popular in network computing environments, and group is the basic unit of task processing for such applications. Members in a group exchange data with each other. Group signature is used to guarantee the integrity of exchanged data and provide source authentication. In a Virtual Machine (VM) based computing system, a Virtual Machine Monitor (VMM) allows multiple applications to run in different virtual machines, and each virtual machine runs in its own hardware protection domain, and is strongly isolated from each other. A Trusted VMM can provide stronger security protection to build group signature architecture than traditional computing platforms. In this paper, we first introduce a trusted group signature architecture in virtual computing environment and how the Trusted VMM (TVMM) provides security guarantee for group signature components. Then we propose a group signature scheme with the function of message checking based on the discrete logarithm problem (DLP). Finally, we prove the security of the group signature scheme and architecture.
Debating over heterogeneous descriptions
Authors: Maxime Morge, Jean-Christophe Routier
Venue: Applied Ontology (2007)

A fundamental interoperability problem is caused by the semantic heterogeneity of agents'ontologies in open multi-agent systems. In this paper, we propose a formal framework for agents debating over heterogeneous terminologies. For this purpose, we propose an argumentation-based representation framework to manage conflicting descriptions. Moreover, we propose a model for the reasoning of agents where they justify the description to which they commit and take into account the description of their interlocutors. Finally, we provide a dialectical system allowing agents to participate in a dialogue in order to reach an agreement over heterogeneous descriptions.
A decentralized approach to cooperative situation assessment in multi-robot systems
Authors: Giuseppe P. Settembre, Paul Scerri, Alessandro Farinelli, Katia Sycara, Daniele Nardi
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

To act effectively under uncertainty, multi-robot teams need to accurately estimate the state of the environment. Although individual robots, with uncertain sensors, may not be able to accurately determine the current situation, the team as a whole should have the capability to perform situation assessment. However, sharing all information with all other team mates is not scalable nor is centralization of all information possible. This paper presents a decentralized approach to cooperative situation assessment that balances use of communication bandwidth with the need for good situation assessment. When a robot believes locally that a particular plan should be executed, it sends a proposal for that plan, to one of its team mates. The robot receiving the plan proposal, can either agree with the plan and forward it on, or it can provide sensor information to suggest that an alternative plan might have higher expected utility. Once sufficient robots agree with the proposal, the plan is initiated. The algorithm successfully balances the value of cooperative sensing against the cost of sharing large volumes of information. Experiments verify the utility of the approach, showing that the algorithm dramatically out-performs individual decision-making and obtains performance similar to a centralized approach.
Changing Neighborhoods of CA: Reduced Local Structures and Embeddings for Universality
Authors: Thomas Worsch, Hidenosuke Nishio
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

This paper consists of two parts. In the first we pick up again the question under which circumstances different pairs of a local function and a neighborhood give rise to the same global behavior of CA and disprove a conjecture made in an earlier paper. In the second part we reconsider a construction showing that one can achieve universality by only changing the (positions in the) neighborhood of a CA, while not providing any information about the CA to be simulated in the initial configuration. The construction uses an embedding which in some sense is "non-local". We show that under mild conditions this is necessary.
Paper Currency Verification with Support Vector Machines
Authors: Chin-Chen Chang, Tai-Xing Yu, Hsuan-Yen Yen
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Distinct from conventional techniques where the Neural Network (NN) is employed to solve the problem of paper currency verification, in this paper, we shall present a novel method by applying the support vector machine (SVM) approach to distinguish counterfeit banknotes from genuine ones. On the basis of the statistical learning theory, SVM has better generalization ability and higher performance especially when it comes to pattern classification. Besides, discrete wavelet transformation (DWT) will also be applied so as to reduce the input scale of SVM. Finally, the results of our experiment will show that the proposed method does achieve very good performance.
Personalizing the Selection of Digital Library Resources to Support Intentional Learning
Authors: Qianyi Gu, Sebastian Chica, Faisal Ahmad, Huda Khan, Tamara Sumner, James H. Martin, Kirsten Butcher
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

This paper describes a personalization approach for using online resources in digital libraries to support intentional learning. Personalized resource recommendations are made based on what learners currently know and what they should know within a targeted domain to support their learning process. We use natural language processing and graph based algorithms to automatically select online resources to address students' specific conceptual learning needs. An evaluation of the graph based algorithm indicates that the majority of recommended resources are highly relevant or relevant for addressing students' individual knowledge gaps and prior conceptions.
An Improved Scheme for E-signature Techniques Based on Digital Encryption and Information Hiding
Authors: Huang Tao, Zhou Qihai, Zhang Le, Li Zhongjun, Lin Xun
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

In this paper, an important problem that the security of e-commerce system has become one of the core issues and the main bottlenecks which constraints the development of e-commerce is pointed out; the demand of an e-commerce system security and the realizing process of an e-signature technology as the essential key technology in the safety control are elaborated; the insufficiency in current e-signature realizing process is pointed out; based on digital encryption and information hiding, an improving thinking and some realizing schemes for the techniques of e-signature are given; a creative new idea to guide the selection among the e-signature technical schemes with a “safety/speed ratio” digital signature strength theory is proposed; and the developing direction of an e-commerce security technology is advanced.
Applications for Cognitive User Modeling
Authors: Marcus Heinath, Jeronimo Dzaack, Andre Wiesner, Leon Urbas
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Usability of complex dynamic human computer interfaces can be evaluated by cognitive modeling to investigate cognitive processes and their underlying structures. Even though the prediction of human behavior can help to detect errors in the interaction design and cognitive demands of the future user the method is not widely applied. The time-consuming transformation of a problem "in the world" into a "computational model" and the lack of fine-grained simulation data analysis are mainly responsible for this. Having realized these drawbacks we developed HTAmap and SimTrA to simplify the development and analysis of cognitive models. HTAmap, a high-level framework for cognitive modeling, aims to reduce the modeling effort. SimTrA supports the analysis of cognitive model data on an overall and microstructure level and enables the comparison of simulated data with empirical data. This paper describes both concepts and shows their practicability on an example in the domain of process control.
Workshop on Software Engineering for Large Scale Computing (SELSC)
Authors: Daniel Rodríguez, Roberto Ruiz
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

Computational Science techniques are increasingly being applied in both research institutions and industry to for example, financial applications, bioinformatics applications, physical applications, data mining applications based on grid or clusters etc. As with other disciplines there are specific issues when planning and developing such applications. For example, those applications are generally distributed and based upon Grid environments or clusters with specific management and planning issues, design, testing, etc.
The Study of Dynamic Aggregation of Relational Attributes on Relational Data Mining
Authors: Rayner Alfred
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Most aggregation functions are limited to either categorical or numerical values but not both values. In this paper, we define three concepts of aggregation function and introduce a novel method to aggregate multiple instances that consists of both the categorical and numerical values. We show how these concepts can be implemented using clustering techniques. In our experiment, we discretize continuous values before applying the aggregation function on relational datasets. With the empirical results obtained, we demonstrate that our transformation approach using clustering techniques, as a means of aggregating multiple instances of attribute's values, can compete with existing multi-relational techniques, such as Progol and Tilde. In addition, the effect of the number of interval for discretization on the classification performance is also evaluated.
A New Scheduling Algorithm for Distributed Streaming Media System Based on Multicast
Authors: Yunpeng Chai, Zhihui Du, Sanli Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

To meet the growing service scale, distributed streaming media system has been widely used for streaming media applications. The schedule algorithm of distributed streaming media system on how to reduce the network bandwidth consumption and balance the load among service nodes has become a challenging problem. We develop the Period Patching Algorithm with unfixed Period to achieve the best efficiency on reducing bandwidth consumption. Furthermore, the Minimum Bandwidth Schedule Algorithm is proposed. Its major objective is reducing network bandwidth consumption and at the same time balancing the load balancing between nodes. The experiment results show that this proposed algorithm outperforms the classical scheduling algorithms both in reducing total bandwidth consumption and service response time, which is used to reflect the quality of service and load balance effect.
Objects as Actors Assuming Roles in the Environment
Authors: Tetsuo Tamai, Naoyasu Ubayashi, Ryoichi Ichiyama
Venue: Software Engineering for Multi-Agent Systems V: Research Issues and Practical Applications (2007)

To achieve the goal of realizing object adaptation to environments, a new role-based model Epsilon and a language EpsilonJ are proposed. In Epsilon, an environment is defined as a field of collaboration between roles and an object adapts to the environment assuming one of the roles. Objects can freely enter or leave environments and belong to multiple environments at a time so that dynamic adaptation or evolution of objects is realized. Environments and roles are the first class constructs at runtime as well as at model description time so that separation of concerns is not only materialized as a static structure but also observable as behaviors. Environments encapsulating collaboration are independent reuse components to be deployed separately from objects. In this paper, the Epsilon model and the language are explained with some examples. The effectiveness of the model is illustrated by a case study on the problem of integrated systems. Implementation of the language is also reported.
Optimal tester synthesis for real-time systems
Authors: Rachid Bouaziz, Ismaïl Berrada
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

Real-Time systems (RTS for short) are those systems whose behavior is time dependent. The correction of these systems does not only depend on the logical result of the computation but also on the time at which the inputs and outputs are observed. This paper proposes an approach to reduce the number of test cases considered while testing RTS. The proposed approach is based on the computation of an optimal tester. As an application of our approach, the paper proposes a case study on the real-time Ethernet protocol.
EM Algorithm with PIP Initialization and Temperature-Based Selection
Authors: Yuta Ishikawa, Ryohei Nakano
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

The EM algorithm is an efficient algorithm to obtain the ML estimate for incomplete data, but has the local optimality problem. The deterministic annealing EM (DAEM) algorithm was once proposed to solve this problem, which begins a search from the primitive initial point (PIP). Then, proposed was the mes-EM algorithm, which runs the EM repeatedly in many various directions from the PIP, and achieves good solution quality with high computing cost. This paper proposes a variant of the mes-EM, called mes-EM(β), which uses the temperature to select a small promising portion of the mes-EM runs. Our experiments for the Gaussian mixture estimation showed the proposed algorithm was much faster than the original mes-EM without degrading its solution quality.