Distributed Computing and Artificial Intelligence: 10th International Conference
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Proceedings indexed by :. China, China. Deadline : Thu 26 Sep Oct 26, - Oct 28, - No.
Deadline : Mon 30 Sep Mar 21, - Mar 24, - Shenzhen. Other stakeholders should be rewarded with a better understanding of the potential and challenges of the agent-oriented approach. Authors of selected papers from PAAMS will be invited to submit an extended and improved version to special issue in different journals. First Award: EMiR 2. Special Issues Authors of selected papers from PAAMS will be invited to submit an extended and improved version to special issue in different journals. Actions perform basic operations in the middleware, discharging the process load of control elements. The proposal is fully compatible with the standard and can be easily added to an existing system.
Proposal has been tested in a distributed mobile robot navigation system with interesting results. This article provides an algorithm that is dedicated to repeated trajectory optimization with a fixed horizon and addresses processes that are difficult to describe by the established laws of physics. Typically, soft-computing methods are used in such cases, i. Both suffer from high dimensions that make the problems complex or even computationally infeasible. We propose a way how to start from very simple problems and - after the simple problems are covered sufficiently - proceed to more complex ones.
We provide also a case study related to the dynamic optimization of the HVAC heating, ventilation, and air conditioning systems. One of the open issues in risk literature is the difference between risk perception and effective risk, especially when the risk is clearly defined and measured.
Until now, the main focus has been given on the behaviour of individuals and the evidences of their biases according to some stimulus. Consequently, it is important to analyse what are the main reasons for those biases and identify the dimensions and mechanisms involved. To that purpose, we tackle the classic problem of tax fraud as a case study.
In this paper, we will look into how agent based modelling methodology can help unfold the reasons why individuals commit errors of judgment when risk is involved. In this paper, we deal with automated multi-issue concurrent negotiations. A buyer utilizes a number of threads for negotiating with a number of sellers. We propose a method based on the known PSO algorithm for threads coordination. The PSO algorithm is used to lead the buyer to the optimal solution best deal through threads team work.
Moreover, we propose a weights adaptation scheme for optimizing buyer behavior and promoting efficiency. This is proved by our results through a wide range of experiments. We have an increasingly sedentary population without the care to make a healthy diet. Therefore, it becomes necessary to give the population the opportunity, despite living a very busy and tiring life, to have control over important aspects to their health. This work aims to present a model of an ambient intelligence system for monitoring the weight and physical activity in active individuals.
Distributed Computing and Artificial Intelligence: 10th International Conference
To accomplish this objective we have developed a mobile application that allows users to monitor their weight over a period of time, identify the amount of food they consume and the amount of exercise they practice. This mobile application will give information to users about dietary and physical activity guidelines in order to improve their lifestyles. It is expected that students improve their lifestyles. In an idea generation meeting, the facilitator role is essential to obtain good results. The emotional context of the meeting partially determines the un success of the meeting, so the facilitator needs to obtain and process this information.
Thus, the facilitator role is to assist the participants to reach their goals, i. In this paper is proposed an emotional aware architecture whose aim is to assist the facilitator in the process of maximizing the results of the meeting. Intelligent environments and ambient intelligence provide means to monitor physical environments and to learn from users, generating data that can be used to promote sustainability. With communities of intelligent environments, it is possible to obtain information about environment and user behaviors which can be computed and ranked.
Such rankings are bound to be dynamic as users and environments exchange interactions on a daily basis. This work aims to use knowledge from communities of intelligent environments to their own benefit. The approach presented in this work uses information from each environment, ranking them according to their sustainability assessment. Recommendations are then computed using similarity and clustering functions ranking users and environments, updating their previous records and launching new recommendations in the process.
In this paper we present a distributed solution for the acquisition, processing, archiving and diffusion of endoscopic procedures.
The goal is to provide a system capable of managing all administrative and clinical information including audiovisual content since the acquisition process to the searching process of previous exams, for comparison with new cases. In this context, a device for the acquisition of the endoscopic video was designed. All the information is stored in a structured and standardized way, allowing its reuse and sharing. To facilitate this sharing process, the video undergoes several processing steps in order to obtain a summarized video and the respective content characteristics.
The proposed solution uses an annotation system that enables content querying, thus becoming a versatile tool for research in this area. A streaming module in which the endoscopic video is transmitted in real time is also provided. Texture classification poses a well known difficulty within computer vision systems. This paper reviews a method for image segmentation based on the classification of textures using artificial neural networks.
10th International Conference
The supervised machine learning system developed here is able to recognize and distinguish among multiple feature regions within one or more photographs, where areas of interest are characterized by the various patterns of color and shape they exhibit. The use of an enhancement filter to reduce sensitivity to illumination and orientation changes in images is explored, as well as various post-processing techniques to improve the classification results based on context grouping.
Nowadays there are several systems that help people with disabilities on their quotidian tasks. The visual impairment is a problem that affects several people in their tasks and movements. In this work we propose an architecture capable of processing information from the environment and suggesting actions to the user with visual impairments, to avoid a possible obstacle. This architecture intends to improve the support given to the user in their daily movements.
PAAMS Conference Practical Applications of Agents & Multi-Agent Systems
The research offers a quite simple view of methods to classify edible and poisonous mushrooms. To achieve our aim, we will study different structures of neural nets and learning algorithms, and select the best one, according to the test results. Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved.
The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation.
Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.
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Most of the current efforts in the development of believable bots in videogames — bots that behave like human players — are based on classical AI techniques. Specifically, we design virtual bots using Continuous-Time Recurrent Neural Network CTRNNs as the controllers of the non-player characters, and we add a learning module to make an agent be capable of re-learning during its lifetime. The ultimate goal of the contest would be to develop a computer game bot able to behave the same way humans do.
This paper presents a system composed by a set of tools that facilitate the work of disabled people in their work environment. The PANGEA platform was used to build the base architecture of the system, where each tool is designed as a collection of intelligent agents that offer the services as Web-services. Moreover, all the system is implemented as an Open MAS. In this paper two tools are presented in detail, the proximity detection tool and the translator tool for people with hearing impairments.
Cloud computing is revolutionizing the services provided through the Internet, and is continually adapting itself in order to maintain the quality of its services. This study also presents Warehouse 3. State-of-the-art approaches to collaborative filtering are based on the use of an input matrix that represents each user profile as a vector in a space of items and, analogically, each item as a vector in a space of users.
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When the behavioral input data have the form of. We propose to use a matrix, in which columns represent RDF-like triples and rows represent users, items, and relations. This document provides an approach to biometrics analysis which consists in the location and identification of faces in real time, making the concept a safe alternative to Web sites based on the paradigm of user and password. Numerous techniques are available to implement face recognition including the principal component analysis PCA , neural networks, and geometric approach to the problem considering the shapes of the face representing a collection of values.
The study and application of these processes originated the development of a security architecture supported by the comparison of images captured from a webcam using methodology of PCA, and the Hausdorff algorithm of distance as similarity measures between a general model of the registered user and the objects faces stored in the database, the result is a web authentication system with main emphasis on efficiency and application of neural networks. From the last decade, Web services technology has witnessed a great adoption rate as a new paradigm of communication and interoperability between different software systems.
This fact, has led to the emergence of Web services and to their proliferation from outside the boundary of the UDDI business registry to other potential service resources such as public and private service registries, service portals, and so on. The main challenge that arises from this situation is the fact that for the same service implementation, several service descriptions are published in different service registries.