7 resultados para Multi-perspective

em Indian Institute of Science - Bangalore - Índia


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In this paper, we propose an extension to the I/O device architecture, as recommended in the PCI-SIG IOV specification, for virtualizing network I/O devices. The aim is to enable fine-grained controls to a virtual machine on the I/O path of a shared device. The architecture allows native access of I/O devices to virtual machines and provides device level QoS hooks for controlling VM specific device usage. For evaluating the architecture we use layered queuing network (LQN) models. We implement the architecture and evaluate it using simulation techniques, on the LQN model, to demonstrate the benefits. With the architecture, the benefit for network I/O is 60% more than what can be expected on the existing architecture. Also, the proposed architecture improves scalability in terms of the number of virtual machines intending to share the I/O device.

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The finite resolution of joint drives or sensors imparts a discrete nature to the joints of a manipulator. Because of this an arbitrary point in the workspace cannot be reached without error even in ideal mechanical environment. This paper investigates the effect of this discrete nature of the joints on the accuracy of performance of a manipulator and develops a method to select the joint states to reach a point with least error. It is shown that the configuration leading to least error cannot, in general, be found from configuration space, especially when there is large variation in the link lengths or joint resolutions or both. The anomaly becomes severe when the gross motion of the end-effector approaches the local resolution of the workspace. The paper also shows how to distinguish two workspaces which may be identical so far as the boundary points are concerned, taking the joint resolutions into account. Finally, the concepts have been extended to define continuous space global and local performance indices for general multi degree of freedom manipulators.

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Multi-view head-pose estimation in low-resolution, dynamic scenes is difficult due to blurred facial appearance and perspective changes as targets move around freely in the environment. Under these conditions, acquiring sufficient training examples to learn the dynamic relationship between position, face appearance and head-pose can be very expensive. Instead, a transfer learning approach is proposed in this work. Upon learning a weighted-distance function from many examples where the target position is fixed, we adapt these weights to the scenario where target positions are varying. The adaptation framework incorporates reliability of the different face regions for pose estimation under positional variation, by transforming the target appearance to a canonical appearance corresponding to a reference scene location. Experimental results confirm effectiveness of the proposed approach, which outperforms state-of-the-art by 9.5% under relevant conditions. To aid further research on this topic, we also make DPOSE- a dynamic, multi-view head-pose dataset with ground-truth publicly available with this paper.

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One of the different issues limiting the wider application of monolithic hydroxyapatite (HA) as an ideal bone replacement material is the lack of reasonably good electrical transport properties. The comprehensive electrical property characterization to evaluate the efficacy of processing parameters in achieving the desired combination of electroactive properties is considered as an important aspect in the development of HA-based bioactive material. In this perspective, the present work reports the temperature (RT-200 degrees C) and frequency (100 Hz-1 MHz) dependent dielectric properties and AC conductivity for a range of HA-CaTiO3 (HA-CT) composites, densified using both conventional pressureless sintering in air as well as spark plasma sintering in vacuum. Importantly, the AC conductivity of spark plasma sintered ceramics similar to upto 10(-5) (Omega cm)(-1)] are found to be considerably higher than the corresponding pressureless sintered ceramics similar to upto 10(-8) (Omega cm)(-1)]. Overall, the results indicate the processing route dependent functional properties of HA-CaTiO3 composites as well as related advantages of spark plasma sintering route. (C) 2013 Elsevier Ltd. All rights reserved.

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Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

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This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

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An electromagnetically coupled feed arrangement is proposed for simultaneously exciting multiple concentric ring antennas for multi-frequency operation. This has a multi-layer dielectric configuration in which a transmission line is embedded below the layer containing radiating rings. Energy coupled to these rings from the line beneath is optimised by suitably adjusting the location and dimensions of stubs on the line. It has been shown that the resonant frequencies of these rings do not change as several of these single-frequency antennas are combined to form a multi-resonant antenna. Furthermore, all radiators are forced to operate at their primary mode and some harmonics of the lower resonant frequency rings appearing within the frequency range are suppressed when combined. The experimental prototype antenna has three resonant frequencies at which it has good radiation characteristics.