Synthesis and Application of Novel Nano Fe-BTC/GO Composites as Highly Efficient Photocatalysts in the Dye Degradation

Topics in Catalysis - Nano Fe-BTC/graphene oxide (GO) composites were successfully synthesized by hydrothermal treatment with a microwave-assisted method. Samples were characterized by X-ray...     

Equivalent circuit model of on-wafer CMOS interconnects for RFICs

This paper investigates the properties of the on-wafer interconnects built in a 0.18-/spl mu/m CMOS technology for RF applications. A scalable equivalent circuit model is developed. The model parameters are extracted directly from the on-wafer measurements and formulated into empirical expressions. The expressions are in functions of the length and the width of the interconnects. The proposed model can be easily implemented into commercial RF circuit simulators. It provides a novel solution to include the frequency-variant characteristics into a circuit simulation. The silicon-verified accuracy is proved to be up to 25 GHz with an average error less than 2%. Additionally, equivalent circuit model for longer wires can be obtained by cascading smaller subsections together. The scalability of the propose model is demonstrated.     

Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

Clustering is a crucial method for deciphering data structure and producing new information. Due to its significance in revealing fundamental connections between the human brain and events, it is essential to utilize clustering for cognitive research. Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties. Noisy data can lead to incorrect object recognition and inference. This research aims to innovate a novel clustering approach, named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering (PNTS3FCM), to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set (PFS) and Neutrosophic Set (NS). Our contribution is to propose a new optimization model with four essential components: clustering, outlier removal, safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled data. The effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods, standard Picture fuzzy clustering (FC-PFS) and Confidence-weighted safe semi-supervised clustering (CS3FCM) on benchmark UCI datasets. The experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.     

Scalable Model of On-Wafer Interconnects for High-Speed CMOS ICs

This paper describes the development of an equivalent circuit model of on-wafer interconnects for high-speed CMOS integrated circuits. By strategically cascading two-pi blocks together, the lumped model can characterize the distributed effects. Besides, the elaborately proposed model characterizes the frequency-variant characteristics with frequency-independent components. Thus, the model can be easily plugged into commercial computer-aided design tools. By adopting a newly invented optimization algorithm, namely, particle swarm optimization (PSO), the model parameters are extracted and formulated as empirical expressions. Therein, with each set of the geometrical parameters, the interconnect behaviors can be accurately predicted. The accuracy of the model is validated by comparisons with the on-wafer measurements up to 30 GHz. Moreover, the scalability of the proposed model is also discussed     

An information based feedback control for audio-motor binaural localization

In static scenarios, binaural sound localization is fundamentally limited by front-back ambiguity and distance non-observability. Over the past few years, “active” schemes have been shown to overcome these shortcomings, by combining spatial binaural cues with the motor commands of the sensor. In this context, given a Gaussian prior on the relative position to a source, this paper determines an admissible motion of a binaural head which leads, on average, to the one-step-ahead most informative audio-motor localization. To this aim, a constrained optimization problem is set up, which consists in maximizing the entropy of the next predicted measurement probability density function over a cylindric admissible set. The method is appraised through geometrical arguments, and validated in simulations and on real-life robotic experiments.     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

Performance Analysis of Full-Duplex Vehicle-to-Vehicle Relay System over Double-Rayleigh Fading Channels

Mobile Networks and Applications - In this paper, we study the performance of a full-duplex (FD) relay system in vehicle-to-vehicle (V2V) communication. In this relay communication system, the...     

Highly sensitive electrochemical sensor based on zirconium oxide-decorated gold nanoflakes nanocomposite 2,4-dichlorophenol detection

Journal of Applied Electrochemistry - In this study, a sensitive and selective electrochemical sensor based on a zirconia oxide-decorated gold nanoflake nanocomposite-modified glassy carbon...     

Size effects and interactions in La0.7Ca0.3MnO3 nanoparticles

La_0.7Ca_0.3MnO₃ (LCMO) nanoparticles with average diameter of 16-73 nm were prepared by reactive milling and thermal processing methods. Interaction and size effects on the magnetic properties of the LCMO nanoparticle samples were investigated. Phenomena related to the interparticle interaction, such as an un-overlapping of the M(H_ext,T)/M_S vs. H_ext/T scaling plots and a Curie-Weiss rather than Curie law behavior of the dc susceptibility at high temperatures were analyzed. The magnetization curves of interacting nanoparticles were well described by using the mean-field approximation. The dependence of the blocking temperature T_B on the strength of the interactions, magnetic anisotropy, as well as the thermal dependence of magnetization deviates from the expected Bloch law was also estimated.