Sensoring a Generative System to Create User-Controlled Melodies

[EN] The automatic generation of music is an emergent field of research that has attracted the attention of countless researchers. As a result, there is a broad spectrum of state of the art research in this field. Many systems have been designed to facilitate collaboration between humans and machines in the generation of valuable music. This research proposes an intelligent system that generates melodies under the supervision of a user, who guides the process through a mechanical device. The mechanical device is able to capture the movements of the user and translate them into a melody. The system is based on a Case-Based Reasoning (CBR) architecture, enabling it to learn from previous compositions and to improve its performance over time. The user uses a device that allows them to adapt the composition to their preferences by adjusting the pace of a melody to a specific context or generating more serious or acute notes. Additionally, the device can automatically resist some of the user’s movements, this way the user learns how they can create a good melody. Several experiments were conducted to analyze the quality of the system and the melodies it generates. According to the users’ validation, the proposed system can generate music that follows a concrete style. Most of them also believed that the partial control of the device was essential for the quality of the generated music

Developing Home Care Intelligent Environments: From Theory to Practice

One of the main aims of the pervasive systems is to be able to adapt themselves in execution time to the changes in the number of resources available, the mobility of the users, variability in the needs of the users and failures of the system. This work presents HoCa, a multi-agent based architecture designed to facilitate the development of pervasive systems. HoCa presents a new model where multi-agent systems and service oriented architectures are integrated to facilitate compatible services. HoCa has been applied to case study in a real scenario, aimed to provide automatic assistance to dependent people at their home, and the results obtained are presented in this paper

Forest Fires Prediction by an Organization Based System

In this study, a new organization based system for forest fires prediction is presented. It is an Organization Based System for Forest Fires Forecasting (OBSFFF). The core of the system is based on the Case-Based Reasoning methodology, and it is able to generate a prediction about the evolution of the forest fires in certain areas. CBR uses historical data to create new solutions to current problems. The system employs a distributed multi-agent architecture so that the main components of the system can be remotely accessed. All the elements building the final system, communicate in a distributed way, from different type of interfaces and devices. OBSFFF has been applied to generate predictions in real forest fire situations, using historical data both to train the system and to check the results. Results have demonstrated that the system accurately predicts the evolution of the fires. It has been demonstrated that using a distributed architecture enhances the overall performance of the system

The THOMAS architecture in Home Care scenarios: A case study

Today, the need for architectures and computational models for large scale open multi-agent systems is considered a key issue for the success of agent technology in real world scenarios. The main goal of this paper is to describe a case study in Home Care scenarios applying an abstract architecture and a computational model for large scale open multi-agent systems based on a service-oriented approach. The architecture used is THOMAS, which specifically addresses the design of Home Care systems. This paper presents services examples for the management of a dependent home environment, and demonstrates the new features of the proposal

A Contingency Response Multi-agent System for Oil Spills

This paper presents CROS, a contingency response multi-agent system for oil spills situations. The system makes use of a Case-Based Reasoning system which generates predictions to determine the probability of finding oil slicks in certain areas of the ocean. CBR uses past information to generate new solutions to the current problem. The system employs a distributed multi-agent architecture so that the main components of the system can be accessed remotely. Therefore, all functionalities can communicate in a distributed way, even from mobile devices. The core of the system is a group of deliberative agents acting as controllers and administrators for all functionalities. The system has been used to predict real oil spill situations. Results have demonstrated that the system can accurately predict the presence of oil slicks in determined zones. It has been demonstrated that using a distributed architecture can enhance the overall performance of the system

SCMAS: A Distributed Hierarchical Multi-agent Architecture for Blocking Attacks to Databases

One of the main attacks on databases is the SQL injection attack which causes severe damage both in the commercial aspect and the confidence of users. This paper presents a novel strategy for detecting and preventing SQL injection attacks consisting of a multi-agent based architecture called SCMAS. The SCMAS architecture is structured in hierarchical layers and incorporates SQLCBR agents with improved learning and adaptation capabilities. The SQLCBR agents presented within this paper have been specifically designed to classify SQL injection attacks and to predict the behaviour of malicious users. These agents incorporate a new technique based on a mixture of neural networks and a technique based on a temporal series. This paper begins with a detailed explanation of the SCMAS architecture and the SQLCBR agents. The results of their application to a case study are then presented and discussed

MISIA: Middleware Infrastructure to Simulate Intelligent Agents

Nowadays there is a clear trend towards using methods and tools that can help to develop multiagent systems (MAS). This study presents a multiagent based middleware for the agents behavior simulation. The main challenge of this work is the design and development of a new infrastructure that can act as a middleware to communicate the current technology in charge of the development of the multiagent system and the technology in charge of the simulation, visualization and analysis of the behavior of the agents. It is a key element when considering that MAS are autonomous, adaptive and complex systems and provides advances abilities for visualization. The proposed middleware infrastructure makes it possible to visualize the emergent agent behaviour and the entity agent. It also allows visualization of the interaction between the agent and the environment

Applying HoCCAC to Plan Task the COPD Patient: A Case Study

This paper presents a multiagent system that facilitates the performance of daily tasks for Chronic Obstructive Pulmonary Disease (COPD) patient within a context-aware environment. The paper analyzes the relevant aspects of context-aware computing and presents a prototype that can be applied to monitor COPD patient at their homes. The system includes computational elements that are integrated within a domestic environment with the goal of capturing context-related information and managing the events carried out by the patient. The services are support by the processing and reasoning out of the data received by the agents in order to offer proactive solutions to the user. The results obtained with this prototype are presented in this paper

Context-aware multiagent system: Planning home care tasks

Context-aware systems are able to capture information from the context in which they are executed, assign a meaning to the gathered information, and change their behavior accordingly. As a result, the systems can offer services to users according to their individual situation within the context. This article analyzes the important aspects of context-aware computing such as capturing information for context attributes and determining the manner of interacting with users in the environment. Used in conjunction with mobile devices, context-aware systems are specifically used to improve the usability of applications and services. This article proposes the home care context-aware computing (HoCCAC) multiagent system that identifies and maintains a permanent fix on the location of patients in their home, and manages the infrastructure of services within their environment securely and reliably by processing and reasoning the data received. Based on the multiagent system, a prototype was developed to monitor patients in their home. The HoCCAC multiagent system uses a critical path method-based planning model that, in the present study, prepares the most optimal task-planning schedule for the patients in their home, is capable of reacting automatically when faced with dangerous or emergency situations, replanning any plans in progress and sending alert messages to the system. The results obtained with this prototype are presented in this article

Cloud-IO: Cloud Computing Platform for the Fast Deployment of Services over Wireless Sensor Networks

In the recent years, a new computing model, known as Cloud Computing, has emerged to react to the explosive growth of the number of devices connected to Internet. Cloud Computing is centered on the user and offers an efficient, secure and elastically scalable way of providing and acquiring services. Likewise, Ambient Intelligence (AmI) is also an emerging paradigm based on ubiquitous computing that proposes new ways of interaction between humans and machines, making technology adapt to the users’ necessities. One of the most important aspects in AmI is the use of context-aware technologies such as Wireless Sensor Networks (WSN) to perceive stimuli from both the users and the environment. In this regard, this paper presents Cloud-IO, a Cloud Computing platform for the fast integration and deployment of services over WSN