A multidimensional scaling analysis of musical sounds based on pseudo phase plane

This paper studies musical opus from the point of view of three mathematical tools: entropy, pseudo phase plane (PPP), and multidimensional scaling (MDS). The experiments analyze ten sets of different musical styles. First, for each musical composition, the PPP is produced using the time series lags captured by the average mutual information. Second, to unravel hidden relationships between the musical styles the MDS technique is used. The MDS is calculated based on two alternative metrics obtained from the PPP, namely, the average mutual information and the fractal dimension. The results reveal significant differences in the musical styles, demonstrating the feasibility of the proposed strategy and motivating further developments towards a dynamical analysis of musical sounds.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

Ant colony system based approach to single machine scheduling problems: weighted tardiness scheduling problem

The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Case-based reasoning for self-optimizing behavior

In this paper we present a Self-Optimizing module, inspired on Autonomic Computing, acquiring a scheduling system with the ability to automatically select a Meta-heuristic to use in the optimization process, so as its parameterization. Case-based Reasoning was used so the system may be able of learning from the acquired experience, in the resolution of similar problems. From the obtained results we conclude about the benefit of its use.

Safety high accuracy Context-Aware Matrix (CAM) making based on X.509 proxy certificate

Human Computer Interaction (HCl) is to interaction between computers and each person. And context-aware (CA) is very important one of HCI composition. In particular, if there are sequential or continuous tasks between users and devices, among users, and among devices etc, it is important to decide the next action using right CA. And to take perfect decision we have to get together all CA into a structure. We define that structure is Context-Aware Matrix (CAM) in this article. However to make exact decision is too hard for some problems like low accuracy, overhead and bad context by attacker etc. Many researcher has been studying to solve these problems. Moreover, still it has weak point HCI using in safety. In this Article, we propose CAM making include best selecting Server in each area. As a result, moving users could be taken the best way.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.