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The Amazon Picking Challenge and the Amazon Robotics Challenge have shown significant progress in object picking from a cluttered scene, yet object placement remains challenging. It is useful to have pose-aware placement based on human and machine readable pieces on an object. For example, the brandname of an object placed on a shelf should be facing the human customers. The robotic vision challenges in the object placement task: a) the semantics and geometry of the object to be placed need to be analysed jointly; b) and the occlusions among objects in a cluttered scene could make it hard for proper understanding and manipulation. To overcome these challenges, we develop a pose-aware placement approach by spotting the semantic labels (e.g., brandnames) of objects in a cluttered tote and then carrying out a sequence of actions to place the objects on a shelf or on a conveyor with desired poses. Our major contributions include 1) providing an open benchmark dataset of objects and brandnames with multi-view segmentation for training and evaluations; 2) carrying out comprehensive evaluations for our brandname-based fully convolutional network (FCN) that can predict the affordance and grasp to achieve pose-aware placement, whose success rates decrease along with clutters; 3) showing that active manipulation with two cooperative manipulators and grippers can effectively handle the occlusion of brandnames. We analyzed the success rates and discussed the failure cases to provide insights for future applications. All data and benchmarks are available at https://text-pick-n-place.github.io/TextPNP/

Induction machines are commonly used in the industrial applications. They require continuous monitoring to prevent the premature failure, of which bearing faults account for most of the causes. The bearings in the rotary equipment tend to suffer fatigue failures during certain conditions such as load variation or electrical discharge. The fault detection based on the vibration analysis could be found in lots of previous literatures, and the frequency spectrum was usually adopted to identify the fault characteristic frequency. However, previous method could only detect the occurrence of bearing faults rather than making the prediction. Hence in this study, the time and frequency features were extracted to construct regression models to predict the development of the bearing faults.

Long cylindrical structure (LCS) experiences vibrations induced by both cross-flows and structural instability. As the technology of LCS facing more structural safety challenges in deep-water conditions, an appropriate control mechanism to enhance the structural integrity, such as reduce the relative motion in between the LCS and the host platform is now high in demand. This paper studies the mathematical model of structural integration for magneto-rheological (MR) damper with an LCS system. Later, curve fitting method is utilized to determine the characteristic coefficients of MR damper to be used in the equation based on a pseudo-experimental data. Then, the structural integration is regarding as a two degree-of-freedom (2-DOF) system and the efficiency of different control schemes on the tensioner stroke is evaluated. The results indicate that the semi-active control mechanism provides improved performances compared with the passive control and can reduce the complexity and avoid the spillover phenomena inherent form the active control. The anticipated impacts are lead to an advancement of understanding in the controlled dynamics of LCS and extension the applicability of LCS to wider operational limits.

The repetition index scheme (RIS) is often applied to the channel estimation of orthogonal frequency division multiplexing (OFDM) systems in the scenario that the numbers of receive antennas and transmit antennas are equal. In this paper, we apply RIS method to the channel estimation of cyclic prefixing (CP) multiple-input multiple-output (MIMO) OF DM systems with virtual carriers. The signal model is first simplified to remove the rank deficiency due to the virtual carriers. We use the RIS method and circular matrix property to generate times of equivalent symbols so as that the channel estimation can converge with few received OFDM block. The RIS method suffers from the nonwhite noise effects. We further calculate the noise correlation matrices. Then a pre-whitening technique is developed from the Cholesky factorization of the noise correlation matrix. Computer Simulations wil1 demonstrate the effectiveness of the proposed channel estimation.

A novel noise whitening technique of blind subspace channel estimations is proposed for cyclic prefixing multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. A fast convergence subspace channel estimation for cyclic prefixed MIMO-OFDM systems was presented in [1] where the repetition index was used to increase the number of equivalent received signals. However, the repetition index approach suffers from the nonwhite noise effects. In this paper, the noise correlation matrices are first calculated. Then a prewhitening technique is developed from the Choleskey decomposition of the noise correlation matrix. The noise whitening technique removes the correlation of the non-white noise. Computer Simulations show the effectiveness of the proposed noise whitening method.

P-channel transition metal dichalcogenide ultrathin-body phototransistor (UTB-PT) with a response time as fast as 100 μs has been demonstrated for the first time using the CVD-synthesized large-area bilayer WSe 2 . Because of its excellent compatibility with mass production, the application of WSe 2 UTB-PT for high-speed proximity interactive display has been proposed.

A photoinduced approach was used to synthesize a nanocomposite system comprised of DNA biopolymer and silver nanoparticles. A photoinduced switching behavior was observed while incorporating such DNA biopolymer nanocomposite as a single layer memory device and a maximum On/Off ratio of 103 can be achieved under appropriate irradiation condition. Such technique coupled with DNA-templated nanoparticle synthesis provides a facile and convenient route for photoinduced nanoparticle-conjugated DNA biopolymers for the applications of optical signal processing, optical storage, and holography.