Low-loss narrowband filtering switch based on coaxial resonators

© 2013 IEEE. In this paper, a narrowband filtering switch with low loss and high selectivity is presented based on coaxial resonators for the first time. PIN diodes mounted on the printed circuit boards are embedded into a coaxial filter to enable ON and OFF states. In the ON-state, the PIN diodes are turned OFF, which do not introduce the loss and affect the linearity. Two transmission zeros are generated by a novel feeding structure, which improves the skirt selectivity. In the OFF-state, the PIN diodes are turned on. Then, lumped capacitors are loaded to the coaxial resonators so that the resonant frequencies of the resonators are changed. The passband at the operating frequency cannot be formed, resulting in high isolation. For demonstration, the coaxial-resonator-based filtering switch is designed and fabricated. Good agreement between simulated and measured results verifies the proposed ideas. Comparison with other reported filtering switches is given. The proposed filtering switch shows the advantages of high Q-factor, relatively compact size, and wide stopband responses, which is attractive in wireless systems

Effect of atomic ordering on hydrogen dissociation on Ni₃Fe surfaces

2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Cross-Layer Optimization for Industrial Internet of Things in NOMA-based C-RANs

This paper investigates non-orthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficency (EE) by jointly optimizing the power allocation, analog and digital precoding, which turns out to be an intractable non-convex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with hybrid precoding (HP) scheme can achieve higher SE and EE than traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme

Zero-Forcing Beamforming for RIS-Enhanced Secure Transmission

This article considers a reconfigurable intelligent surface (RIS) enhanced multi-antenna secure transmission system in the presence of both active eavesdroppers (AEves) and passive eavesdroppers (PEves). We propose a zero-forcing (ZF) beamforming strategy that can steer transmit beam to the null space of AEves' channel, while simultaneously enhancing the SNRs for a legitimate user equipment (UE) and PEves without perfect channel state information (CSI). The design goal is to maximize the SNR of UE subject to the transmit power constraint at the BS, SNR limitations on PEves, and reflection constraints at RIS. Due to the complexity of modeling, we first introduce a homogeneous Poisson point process (HPPP) to imitate the distribution of spatially random PEves, which derives a complicated non-convex problem. We then develop an efficient alternating algorithm where the transmit beamforming vector and the reflective beamforming vector are obtained by convex-concave procedure (CCP) and semi-definite relaxation (SDR) technique, respectively. Simulation results validate the performance advantages of the proposed optimized design

Joint 3D Trajectory Design and Time Allocation for UAV-Enabled Wireless Power Transfer Networks

This paper considers a rotary-wing unmanned aerial vehicle (UAV)-enabled wireless power transfer system, where a UAV is dispatched as an energy transmitter (ET), transferring radio frequency (RF) signals to a set of energy receivers (ERs) periodically. We aim to maximize the energy harvested at all ERs by jointly optimizing the UAV's three-dimensional (3D) placement, beam pattern and charging time. However, the considered optimization problem taking into account the drone flight altitude and the wireless coverage performance is formulated as a non-convex problem. To tackle this problem, we propose a low-complexity iterative algorithm to decompose the original problem into four sub-problems in order to optimize the variables sequentially. In particular, we first use the sequential unconstrained convex minimization based algorithm to find the globally optimal UAV two-dimensional (2D) position. Subsequently, we can directly obtain the optimal UAV altitude as the objective function of problem is monotonic decreasing with respect to UAV altitude. Then, we propose the multiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to control the phase of antenna array elements, in order to achieve high steering performance of multi-beams. Finally, with the above solved variables, the original problem is reformulated as a single-variable optimization problem where charging time is the optimization variable, and can be solved using the standard convex optimization techniques. Furthermore, we use the branch and bound method to design the UAV trajectory which can be constructed as traveling salesman problem (TSP) to minimize flight distance. Numerical results validate the theoretical findings and demonstrate that significant performance gain in terms of sum received power of ERs can be achieved by the proposed algorithm in UAV-enabled wireless power transfer networks

Superconductivity in iron telluride thin films under tensile stress

By realizing in thin films a tensile stress state, superconductivity of 13 K was introduced into FeTe, an non-superconducting parent compound of the iron pnictides and chalcogenides, with transition temperature higher than that of its superconducting isostructural counterpart FeSe. For these tensile stressed films, the superconductivity is accompanied by the softening of the first-order magnetic and structural phase transition; and also, the in-plane extension and out-of-plane contraction are universal in all FeTe films independent of sign of lattice mismatch, either positive or negative. Moreover, the correlations were found exist between the transition temperatures and the tetrahedra bond angles in these thin films.Comment: 4 pages, 4 figures, accepted by Physical Review Letter

Effect of Lactobacillus acidophilus, Oenococcus oeni, and Lactobacillus brevis on Composition of Bog Bilberry Juice

This study investigated the impact of Lactobacillus acidophilus NCFM, Oenococcus oeni Viniflora((R)) Oenos and Lactobacillus brevis CICC 6239 on bog bilberry juice with a considerably low pH and rich in anthocyanins content. Moreover, the effects of the strains on the composition of phenolic compounds, amino acids, ammonium ion, biogenic amines, reduced sugars, organic acids, and color parameters of the juice were studied. All three bacteria consumed sugars and amino acids but exhibited different growth patterns. Lactic acid was detected only in L. acidophilus inoculated juice. The content of the phenolic compounds, especially anthocyanins, decreased in juice after inoculation. The CIELa*b* analysis indicated that the juice inoculated with L. acidophilus and O. oeni showed a decrease on a* and b* (less red and yellow) but an increase on L (more lightness), whereas the color attributes of L. brevis inoculated juice did not significantly change. Based on this study, L. brevis showed the most optimal performance in the juice due to its better adaptability and fewer effects on the appearance of juice. This study provided a useful reference on the metabolism of lactic acid bacteria in low pH juice and the evolution of primary and secondary nutrients in juice after inoculated with lactic acid bacteria

On the Inability of Markov Models to Capture Criticality in Human Mobility

We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian nature of mobility was used to establish a theoretical upper bound on the predictability of human mobility (expressed as a minimum error probability limit), based on temporally correlated entropy. Since its inception, this bound has been widely used and empirically validated using Markov chains. We show that recurrent-neural architectures can achieve significantly higher predictability, surpassing this widely used upper bound. In order to explain this anomaly, we shed light on several underlying assumptions in previous research works that has resulted in this bias. By evaluating the mobility predictability on real-world datasets, we show that human mobility exhibits scale-invariant long-range correlations, bearing similarity to a power-law decay. This is in contrast to the initial assumption that human mobility follows an exponential decay. This assumption of exponential decay coupled with Lempel-Ziv compression in computing Fano's inequality has led to an inaccurate estimation of the predictability upper bound. We show that this approach inflates the entropy, consequently lowering the upper bound on human mobility predictability. We finally highlight that this approach tends to overlook long-range correlations in human mobility. This explains why recurrent-neural architectures that are designed to handle long-range structural correlations surpass the previously computed upper bound on mobility predictability

A framework for automatic semantic video annotation

The rapidly increasing quantity of publicly available videos has driven research into developing automatic tools for indexing, rating, searching and retrieval. Textual semantic representations, such as tagging, labelling and annotation, are often important factors in the process of indexing any video, because of their user-friendly way of representing the semantics appropriate for search and retrieval. Ideally, this annotation should be inspired by the human cognitive way of perceiving and of describing videos. The difference between the low-level visual contents and the corresponding human perception is referred to as the ‘semantic gap’. Tackling this gap is even harder in the case of unconstrained videos, mainly due to the lack of any previous information about the analyzed video on the one hand, and the huge amount of generic knowledge required on the other. This paper introduces a framework for the Automatic Semantic Annotation of unconstrained videos. The proposed framework utilizes two non-domain-specific layers: low-level visual similarity matching, and an annotation analysis that employs commonsense knowledgebases. Commonsense ontology is created by incorporating multiple-structured semantic relationships. Experiments and black-box tests are carried out on standard video databases for action recognition and video information retrieval. White-box tests examine the performance of the individual intermediate layers of the framework, and the evaluation of the results and the statistical analysis show that integrating visual similarity matching with commonsense semantic relationships provides an effective approach to automated video annotation

Recent progress in organic-based radiative cooling materials: fabrication methods and thermal management properties

Organic-based materials capable of radiative cooling have attracted widespread interest in recent years due to their ease of engineering and good adaptability to different application scenarios. As a cooling material for walls, clothing, and electronic devices, these materials can reduce the energy consumption load of air conditioning, improve thermal comfort, and reduce carbon emissions. In this paper, an overview is given of the current fabrication strategies of organic-based radiative cooling materials, and of their properties. The methods and joint thermal management strategies including evaporative cooling, phase-change materials, fluorescence, and light-absorbing materials that have been demonstrated in conjunction with a radiative cooling function are also discussed. This review provides a comprehensive overview of organic-based radiative cooling, exemplifying the emerging application directions in this field and highlighting promising future research directions in the field