Coordinated energy management of vehicle air conditioning system

Whilst air conditioning systems increase thermal comfortableness in vehicles, they also raise the energy consumption of vehicles. Achieving thermal comfort in an energy-efficient way is a difficult task requiring good coordination between engine and the air conditioning system. This paper presents a coordinated energy management system to reduce the energy consumption of the vehicle air conditioning system while maintaining the thermal comfortableness. The system coordinates and manages the operation of evaporator, blower, and fresh air and recirculation gates to provide the desired comfort temperature and indoor air quality, under the various ambient and vehicle conditions, the energy consumption can then be optimized. Three simulations of the developed coordinated energy management system are performed to demonstrate its energy saving capacity.

The implications of lung-regulated buoyancy control for dive depth and duration

Among air-breathing divers, control of buoyancy through lung volume regulation may be most highly developed in marine turtles. In short, the turtle lung may serve a dual role as both an oxygen store and in buoyancy control. A simple model is developed to show that, for turtles diving up to the maximum depth at which they can still use their lungs to attain neutral buoyancy, the total oxygen store will increase greatly with dive depth, and hence a corresponding increase in dive duration is predicted. Time–depth recorders attached to free-living green turtles (Chelonia mydas) at Ascension Island confirmed a marked increase in dive duration with depth, with the gradient of this relationship being >10 times that seen in diving birds and mammals. Consistent with the prediction that the lungs serve a dual role, we found that, when lead weights were added to some turtles to increase their specific gravity, the mean depth of dives decreased, but for dives to the same depth, weighted animals dived for longer. The depth distribution of green turtles seems to be generally constrained by the maximum depth at which they can still attain close to neutral buoyancy.

Dividing traffic sub-areas based on a parallel K-means algorithm

In order to alleviate the traffic congestion and reduce the complexity of traffic control and management, it is necessary to exploit traffic sub-areas division which should be effective in planing traffic. Some researchers applied the K-Means algorithm to divide traffic sub-areas on the taxi trajectories. However, the traditional K-Means algorithms faced difficulties in processing large-scale Global Position System(GPS) trajectories of taxicabs with the restrictions of memory, I/O, computing performance. This paper proposes a Parallel Traffic Sub-Areas Division(PTSD) method which consists of two stages, on the basis of the Parallel K-Means(PKM) algorithm. During the first stage, we develop a process to cluster traffic sub-areas based on the PKM algorithm. Then, the second stage, we identify boundary of traffic sub-areas on the base of cluster result. According to this method, we divide traffic sub-areas of Beijing on the real-word (GPS) trajectories of taxicabs. The experiment and discussion show that the method is effective in dividing traffic sub-areas.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Measures for controlling traffic congestion

Traffic congestion has become a severe scourge in large cities, in both the industrialized and developing countries. Increasing demand for urban transport and transit has led to longer travel times, and a greater incidence of accidents, environmental problems and deterioration in the quality of life than is considered acceptable for citizens. A multidisciplinary approach is required in order to keep the negative effects of congestion under control and to ensure standards of living remain sustainable. In view of the seriousness of the problem, ECLAC with the support of the German Agency for Technical Cooperation (GTZ) is carrying out a project to study measures that contribute to traffic control. As part of this project, initiatives regarding the supply of, and the demand for, transport have been examined, and a programme to disseminate information is being conducted.For further information, please contact Mr Alberto Bull .

Benefits of Multimodal Exercise Intervention for Postural Control and Frontal Cognitive Functions in Individuals with Alzheimer's Disease: A Controlled Trial

Objective To verify the effects of a systematized multimodal exercise intervention program on frontal cognitive function, postural control, and functional capacity components of individuals with Alzheimer's disease (AD).DesignNonrandomized controlled trial with pre- and posttraining tests in a training group and a control group.SettingKinesiotherapy program for seniors with AD, SAo Paulo State University.ParticipantsConvenience sample of older adults with AD (n=30) were assigned to a training (n=14; aged 78.67.1) and a control (n=16; aged 77.06.3) group.InterventionThe intervention program was structured with the aim of simultaneously promoting better balance and frontal cognitive capacity. The participants attended a 1-hour session three times a week for 16weeks, whereas the control group did not participate in any activity during the same period.MeasurementsFrontal cognitive function was evaluated using the Montreal Cognitive Assessment, the Clock Drawing Test, the Frontal Assessment Battery, and the Symbol Search Subtest. Postural control (center of pressure area) was analyzed under four dual-task conditions. Functional capacity components were analyzed using the Timed Up and Go Test, the 30-second sit-to-stand test, the sit-and-reach test, and the Berg Functional Balance Scale.ResultsIntervention group participants showed a significant increase in frontal cognitive function (P<.001, partial (2)=0.838), with less body sway (P=.04, partial (2)=0.04) during the dual tasks, and greater functional capacity (P=.001, partial (2)=0.676) after the 16-week period.ConclusionIntervention participants performed better on dual-task activities and had better postural balance and greater functional capacity than controls.

Fast fault section estimation in distribution control centers using adaptive genetic algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detecção da procedência de plantas psicoativas pelos isótopos estáveis do nitrogênio (15n) e oxigênio (18o)

This research examines the merits of hallucinogenic plants considered and/or psychoactive substances, such as Cannabis sativa and Ipomoea violacea, using the isotope rates of stable isotope of oxygen (18O) and nitrogen (15N), continuing projects already developed by the research group at the Center for Stable Isotope (CIE), which evaluated the isotopes carbon-13. This paper helps in creating a database that we intent to use in evaluation of each plant merit. Through the IRMS (Isotope-Ratio Mass Spectrometry) technique, it has shown that some of the 24 samples of marijuana (Cannabis sativa L.) evaluated were similar to those grown in the regions of Fairbanks and Tanacross Alaska, USA. In turn, the 50 samples of Ipomoea violacea, coming from Botucatu (SP) and Três Lagoas (MS), got their differences detected, in order to clearly identify the discrepancies between their growing regions. Thus, it was possible not only to track the geographical differences between marijuana samples collected from different regions, but also evaluate the isotopic variation of leaf, flower and seed of Ipomoea violacea. With this database, it was possible to determine the origin region of the drug and/or detect where the cultivation was carried out, aiding in the search of the traffic control agencies, such as the Federal Police in Brazil

Job satisfaction among control room operators of electrical systems

Shift workers from control centers of electrical systems are a group that has received little attention in Brazil. This study aimed to compare workers' job satisfaction at five control centers of a Brazilian company electrical system, and according to their job titles. Method: The Organization Satisfaction Index (OSI) questionnaire to assess job satisfaction was used. ANOVA was used to compare OSI means, according to job title and control center. The results showed that there is no difference in job satisfaction among job titles, but a significant difference was found according to the control center. A single organizational culture cannot be applied to several branches. It is required to implement actions that would result in job satisfaction improvements among workers of all studied control rooms centers. The high level of education of operators working in all centers might have contributed to the similar values of perceived satisfaction among distinct job titles.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Generic multisensor multitarget bias estimation architecture

Current bias estimation algorithms for air traffic control (ATC) surveillance are focused on radar sensors, but the integration of new sensors (especially automatic dependent surveillance-broadcast and wide area multilateration) demands the extension of traditional procedures. This study describes a generic architecture for bias estimation applicable to multisensor multitarget surveillance systems. It consists on first performing bias estimations using measurements from each target, of a subset of sensors, assumed to be reliable, forming track bias estimations. All track bias estimations are combined to obtain, for each of those sensors, the corresponding sensor bias. Then, sensor bias terms are corrected, to subsequently calculate the target or sensor-target pair specific biases. Once these target-specific biases are corrected, the process is repeated recursively for other sets of less reliable sensors, assuming bias corrected measures from previous iterations are unbiased. This study describes the architecture and outlines the methodology for the estimation and the bias estimation design processes. Then the approach is validated through simulation, and compared with previous methods in the literature. Finally, the study describes the application of the methodology to the design of the bias estimation procedures for a modern ATC surveillance application, specifically for off-line assessment of ATC surveillance performance.

Understanding time-drift for different aircraft descent guidance strategies

In this paper the effect of different aircraft automated descent guidance strategies on fuel burn and the temporal predictability of the executed trajectory is investigated. The paper aims to provide an understanding of how airborne automation can be permitted by Air Traffic Control to remain in control of the descent in the presence of disturbances while providing sufficient predictability. Simulations have been performed investigating different guidance strategies. While each strategy has its advantages and disadvantages, results indicate that improved temporal predictability comes at the cost of additional fuel burn and loss of predictability in other dimensions of the trajectory.