Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Intelligent recommendation system for e-learning platforms

As more and more digital resources are available, finding the appropriate document becomes harder. Thus, a new kind of tools, able to recommend the more appropriated resources according the user needs, becomes even more necessary. The current project implements an intelligent recommendation system for elearning platforms. The recommendations are based on one hand, the performance of the user during the training process and on the other hand, the requests made by the user in the form of search queries. All information necessary for decision-making process of recommendation will be represented in the user model. This model will be updated throughout the target user interaction with the platform.

Feasibility of developing training programs designed to improve deficient driver factors. Volume I: a review of existing data bases and recommendations for future data collection. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Feasibility of developing training programs designed to improve deficient driver factors. Volume II: identifying accident avoidance behaviors: a guide for accident investigators. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Human factors aspects of the transfer of control from the automated highway system to the driver /

"July 1995."

Neural-Like Growing Networks in Intelligent System of Recognition of Images

The neural-like growing networks used in the intelligent system of recognition of images are under consideration in this paper. All operations made over the image on a pre-design stage and also classification and storage of the information about the images and their further identification are made extremely by mechanisms of neural-like networks without usage of complex algorithms requiring considerable volumes of calculus. At the conforming hardware support the neural network methods allow considerably to increase the effectiveness of the solution of the given class of problems, saving a high accuracy of result and high level of response, both in a mode of training, and in a mode of identification.

The effectiveness of an intelligent tutoring system on the attitude and achievement of developmental mathematics students in a community college

This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method. Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system. Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores. It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability.

Creatina quinase e dor muscular tardia na musculação : estudo experimental em adultos e jovens com o "circuit weight training" e o "multiple set system"

Universidade Estadual de Campinas . Faculdade de Educação Física

The Brain as a Distributed Intelligent Processing System: An EEG Study

Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

Exercise training associated with diet improves heart rate recovery and cardiac autonomic nervous system activity in obese children

The purpose of this study was to test the hypotheses that in obese children: 1) hypocaloric diet (D) improves both heart rate recovery at 1 min (Delta HRR1) cfter an exercise test, and cardiac autonomic nervous system activity (CANSA) in obese children; 2) Diet and exercise training (DET) combined leads to greater improvement in both Delta HRR1 after an exercise test and in CANSA, than D alone. Moreover, we examined the relationships among Delta HRR1, CANSA, cardiorespiratory fitness and anthropometric variables (AV) in obese children submitted to D and to DET. 33 obese children (10 +/- 0.2 years; body mass index (BMI) >95(th) percentile) were divided into 2 groups: D (n = 15; BMI = 31 +/- 1 kg/m(2)) and DET (n = 18; 29 +/- 1 kg/m(2)). All children performed a maximal cardiopulmonary exercise test on a treadmill. The Delta HRR1 was defined as the difference between heart rate at peak and at 1-min post-exercise. CANSA was assessed using power spectral analysis of heart rate variability at rest. The sympathovagal balance (low frequency and high frequency ratio, LF/HF) was measured. After interventions, all obese children showed reduced body weight (P < 0.05). The D group did not improve in terms of peak VO(2), Delta HRR1 or LF/HF ratio (P > 0.05). In contrast, the DET group showed increased peak VO(2) (P = 0.01) and improved Delta HRR1 (Delta HRR1 = 37.3 +/- 2.6; P = 0.01) and LF/HF ratio (P = 0.001). The DET group demonstrated significant relationships among Delta HRR1, peak VO(2) and CANSA (P < 0.05). In conclusion, DET, in contrast to D, promoted improved Delta HRR1 and CANSA in obese children, suggesting a positive influence of increased levels of cardiorespiratory fitness by exercise training on cardiac autonomic activity.

Local renin-angiotensin system regulates left ventricular hypertrophy induced by swimming training independent of circulating renin: a pharmacological study

Introduction. This study addressed the role of the local renin-angiotensin system (RAS) in the left ventriular hypertropy (LVH) induced by swimming training using pharmacological blockade. Materials and methods. Female Wistar rats treated with enalapril maleate (60 mg.kg(-1).d(-1), n = 38), losartan (20 mg.kg(-1).d(-1), n = 36) or high salt diet (1% NaCl, n = 38) were trained by two protocols (T1: 60-min swimming session, 5 days per week for 10 weeks and T2: the same T1 protocol until the 8(th) week, then 9(th) week they trained twice a day and 10(th) week they trained three times a day). Salt loading prevented activation of the systemic RAS. Haemodynamic parameters, soleus citrate synthase (SCS) activity and LVH (left ventricular/body weight ratio, mg/g) were evaluated. Results. Resting heart rate decreased in all trained groups. SCS activity increased 41% and 106% in T1 and T2 groups, respectively. LVH was 20% and 30% in T1 and T2 groups, respectively. Enalapril prevented 39% of the LVH in T2 group (p < 0.05). Losartan prevented 41% in T1 and 50% in T2 (P < 0.05) of the LVH in trained groups. Plasma renin activity (PRA) was inhibited in all salt groups and it was increased in T2 group. Conclusions. These data provide evidence that the physiological LVH induced by swimming training is regulated by local RAS independent from the systemic, because the hypertrophic response was maintained even when PRA was inhibited by chronic salt loading. However, other systems can contribute to this process.

Exercise Training Reduces Sympathetic Modulation on Cardiovascular System and Cardiac Oxidative Stress in Spontaneously Hypertensive Rats

BACKGROUND Spontaneously hypertensive rats (SHRs) show increased cardiac sympathetic activity, which could stimulate cardiomyocyte hypertrophy, cardiac damage, and apoptosis. Norepinephrine (NE)induced cardiac oxidative stress seems to be involved in SHR cardiac hypertrophy development. Because exercise training (ET) decreases sympathetic activation and oxidative stress, it may alter cardiac hypertrophy in SHR. The aim of this study was to determine, in vivo, whether ET alters cardiac sympathetic modulation on cardiovascular system and whether a correlation exists between cardiac oxidative stress and hypertrophy. METHODS Male SHRs (15-weeks old) were divided into sedentary hypertensive (SHR, n = 7) and exercise-trained hypertensive rats (SHR-T, n = 7). Moderate ET was performed on a treadmill (5 days/week, 60 min, 10 weeks). After ET, cardiopulmonary reflex responses were assessed by bolus injections of 5-HT. Autoregressive spectral estimation was performed for systolic arterial pressure (SAP) with oscillatory components quantified as low (LF: 0.2-0.75 Hz) and high (HF:0.75-4.0 Hz) frequency ranges. Cardiac NE concentration, lipid peroxidation, antioxidant enzymes activities, and total nitrates/nitrites were determined. RESULTS ET reduced mean arterial pressure, SAP variability (SAP var), LIF of SAP, and cardiac hypertrophy and increased cardiopulmonary reflex responses. Cardiac lipid peroxidation was decreased in trained SHRs and positively correlated with NE concentrations (r= 0.89, P < 0.01) and heart weight/body weight ratio (r= 0.72, P < 0.01), and inversely correlated with total nitrates/nitrites (r= -0.79, P < 0.01). Moreover, in trained SHR, cardiac total nitrates/nitrites were inversely correlated with NE concentrations (r= -0.82, P < 0.01). CONCLUSIONS ET attenuates cardiac sympathetic modulation and cardiac hypertrophy, which were associated with reduced oxidative stress and increased nitric oxide (NO) bioavailability. Am J Hypertens 2008;21:1138-1193 (C) 2008 American Journal of Hypertension, Ltd.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.