A novel driver assist stability system for all-wheel-drive electric vehicles

A novel driver-assist stability system for all-wheel-drive electric vehicles is introduced. The system helps drivers maintain control in the event of a driving emergency, including heavy braking or obstacle avoidance. The system comprises a fuzzy logic system that independently controls wheel torque to prevent vehicle spin. Another fuzzy wheel slip controller is used to enhance vehicle stability and safety. A neural network is trained to generate the required reference for yaw rate. Vehicle true speed is estimated by a sensor data fusion method. The intrinsic robustness of fuzzy controllers allows the system to operate in different road conditions successfully. Moreover, the ease of implementing fuzzy controllers gives a potential for vehicle stability enhancement.     

Reliability assessment of an automated distribution system

Automation can greatly enhance distribution-network reliability by speeding up service restoration and thus significantly reduce customer-outage time. The paper presents an approach to assess quantitatively the adequacy of a particular automated distribution scheme designated as the `low interruption system' (LIS). Owing to the use of a high-speed communication system and line sensors, this automated scheme can reduce drastically the number of interruptions, the service interruption time and also the area affected by the fault. This scheme provides a simple and cost-effective way to automate distribution systems in which the remotely controlled switches speed up isolation of faulted sections and the restoration of healthy sections through alternative routes. The step-by-step calculation procedure is presented using a typical small automated distribution system. The proposed technique is then applied to a larger distribution system to examine the effectiveness of the technique and also to examine the level of reliability improvement achieved by automation     

Direct adaptive fuzzy control with membership function tuning

In this paper, a direct self‐structured adaptive fuzzy control is introduced for the class of nonlinear systems with unknown dynamic models. Control is accomplished by an adaptive fuzzy system with a fixed number of rules and adaptive membership functions. The reference signal and state errors are used to tune the membership functions and update them instantaneously. The Lyapunov synthesis method is also used to guarantee the stability of the closed loop system. The proposed control scheme is applied to an inverted pendulum and a magnetic levitation system, and its effectiveness is shown via simulation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

A localization algorithm for large scale mobile wireless sensor networks: a learning approach

Localization is a crucial problem in wireless sensor networks and most of the localization algorithms given in the literature are non-adaptive and designed for fixed sensor networks. In this paper, we propose a learning based localization algorithm for mobile wireless sensor networks. By this technique, mobility in the network will be discovered by two crucial methods in the beacons: position and distance checks methods. These two methods help to have accurate localization and constrain communication just when it is necessary. The proposed method localizes the nodes based on connectivity information (hop count), which doesn’t need extra hardware and is cost efficient. The experimental results show that the proposed algorithm is scalable with a small set of beacons in large scale network with a high density of nodes. The given algorithm is fast and free from a pre-deployment requirement. The simulation results show the high performance of the proposed algorithm.     

A trust-based service suggestion system using human plausible reasoning

Nowadays, there is a growing need to manage trust in open systems as they may contain untrustworthy service providers. Agent Trust Management (ATM) tries to address the problem of finding a set of the most trusted agents in multi agent systems. This paper presents ScubAA, a novel generic ATM framework based on the theory of Human Plausible Reasoning (HPR). For each user’s request, ScubAA determines a ranked list of the most trusted service agents, within the context of the request, and forwards the request to those trusted services only. ScubAA determines an agent’s degree of trust in terms of a single personalized value derived from several types of evidences such as user’s feedback, history of user’s interactions, context of the submitted request, references from third party users as well as from third party service agents, and structure of the society of agents. ScubAA is able to utilize more trust evidences towards a more accurate value of trust. We also propose a function to figure out how similar two users are in a given context. We apply the proposed HPR-based ATM framework to the domain of Web search. The resulting ATM system recommends to the user a list of the most trusted search engines ranked according to the retrieval precision of documents returned in response to the user’s query as well as the degree of trust of the search engines have gained by interacting with other related users within the context of the query. In addition, we conduct a statistical analysis of ScubAA based on ANOVA and by using a data set of forty queries in different domains. This analysis clearly reveals that ScubAA is able to successfully assess the trustworthiness of service agents.     

Perceiving,learning, and exploiting object affordances for autonomous pile manipulation

Autonomous manipulation in unstructured environments will enable a large variety of exciting and important applications. Despite its promise, autonomous manipulation remains largely unsolved. Even the most rudimentary manipulation task—such as removing objects from a pile—remains challenging for robots. We identify three major challenges that must be addressed to enable autonomous manipulation: object segmentation, action selection, and motion generation. These challenges become more pronounced when unknown man-made or natural objects are cluttered together in a pile. We present a system capable of manipulating unknown objects in such an environment. Our robot is tasked with clearing a table by removing objects from a pile and placing them into a bin. To that end, we address the three aforementioned challenges. Our robot perceives the environment with an RGB-D sensor, segmenting the pile into object hypotheses using non-parametric surface models. Our system then computes the affordances of each object, and selects the best affordance and its associated action to execute. Finally, our robot instantiates the proper compliant motion primitive to safely execute the desired action. For efficient and reliable action selection, we developed a framework for supervised learning of manipulation expertise. To verify the performance of our system, we conducted dozens of trials and report on several hours of experiments involving more than 1,500 interactions. The results show that our learning-based approach for pile manipulation outperforms a common sense heuristic as well as a random strategy, and is on par with human action selection.     

Activating pulp toward acetylation by chemical or mechanical means

Activation of pulps during acetylation, by prior mechanical or chemical treatment, has been investigated. The effect of degree of beating on the acetylation rate of wood and bagasse pulps has been studied. It is found that the acetylation rate of pulps increases when the degree of beating of pulps is increased to a definite degree, after which it slows down. The maximum reactivity of bagasse pulp is obtained at 50°SR, while that of wood pulp is observed at 30°SR. The effect of grafting of acrylonitrile onto bagasse and wood pulps on their reactivity during acetylation has been also studied. The results indicate that grafting of acrylonitrile onto pulps has a favorable effect on their acetylation rate. This is dependent on the degree of grafting as well as the origin of pulp fibers. The most suitable method of activation during acetylation reaction is dependent on the origin of the pulp. The reactivity of bagasse pulp during acetylation is influenced more by beating of pulp, prior to the reaction, than by the grafting of acrylonitrile onto pulp. On the other hand, the acetylation reaction of wood pulp is activated by grafting rather than by beating. Also the effect of the activation process, mechanical or chemical, on the strength properties of the paper sheets produced from acetylated pulps has been investigated. Chemical activation of wood pulp prior to acetylation resulted in pulp with slightly higher strength properties than that activated by mechanical means. But, in the case of bagasse pulp, mechanical activation resulted in a pulp with strength superior to that produced by chemical activation.     

Mechanical properties of composites from sawdust and recycled plastics

Mechanical properties of wood plastic composites (WPCs) manufactured from sawdust and virgin and/or recycled plastics, namely high density polyethylene (HDPE) and polypropylene (PP), were studied. Sawdust was prepared from beech industrial sawdust by screening to the desired particle size and was mixed with different virgin or recycled plastics at 50% by weight fiber loading. The mixed materials were then compression molded into panels. Flexural and tensile properties and impact strength of the manufactured WPCs were determined according to the relevant standard specifications. Although composites containing PP (virgin and recycled) exhibited higher stiffness and strength than those made from HDPE (virgin and recycled), they had lower unnotched impact strengths. Mechanical properties of specimens containing recycled plastics (HDPE and PP) were statistically similar and comparable to those of composites made from virgin plastics. This was considered as a possibility to expand the use of recycled plastics in the manufacture of WPCs. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3641–3645, 2006     

Effects of redox-active interlayer anions on the oxygen evolution reactivity of NiFe-layered double hydroxide nanosheets

Nickel-iron layered double hydroxide (NiFe-LDH) nanosheets have shown optimal oxygen evolution reaction (OER) performance; however, the role of the intercalated ions in the OER activity remains unclear. In this work, we show that the activity of the NiFe-LDHs can be tailored by the intercalated anions with different redox potentials. The intercalation of anions with low redox potential (high reducing ability), such as hypophosphites, leads to NiFe-LDHs with low OER overpotential of 240 mV and a small Tafel slope of 36.9 mV/dec, whereas NiFe-LDHs intercalated with anions of high redox potential (low reducing ability), such as fluorion, show a high overpotential of 370 mV and a Tafel slope of 80.8 mV/dec. The OER activity shows a surprising linear correlation with the standard redox potential. Density functional theory calculations and X-ray photoelectron spectroscopy analysis indicate that the intercalated anions alter the electronic structure of metal atoms which exposed at the surface. Anions with low standard redox potential and strong reducing ability transfer more electrons to the hydroxide layers. This increases the electron density of the surface metal sites and stabilizes their high-valence states, whose formation is known as the critical step prior to the OER process.

Open image in new window

     

Intracellular localization of samarium in the lactating mammary gland cells: ultrastructural and microanalytical study

The frequent use of some rare earths in the medical and industrial domains make us worry about their intracellular behavior into the body. Reason for which we have investigated the subcellular localization of one of these elements, the samarium, in the mammary gland of lactating female wistar rats using two very sensitive methods of observation and microanalysis, the transmission electron microscopy and the secondary ion mass spectrometry. The ultrastructural study showed the presence of electron dense deposits in the lactating mammary glandular epithelial cell lysosomes of the samarium-treated rats, but no loaded lysosomes were observed in those of control rats. The microanalytical study allowed both the identification of the chemical species present in those deposits as samarium isotopes ((152) Sm(+)) and the cartography of its distribution. Our results confirm the previous ones showing that lysosomes of the glandular epithelial cells are the site of the intracellular concentration of foreign elements such as gallium. The intralysosomal deposits observed in the mammary glandular cells of the samarium-treated rats are similar in their form and density to those observed with the same element in other varieties of cells, such as liver, bone marrow, and spleen cells. Our ultrastructural and microanalytical results and those obtained in previous studies allow deducing that the intralysosomal deposits are very probably composed of an insoluble samarium phosphate salt.