A comparison of three different electromagnetic scattering models for land surface delay-Doppler maps (DDMs) obtained from global navigation satellite system reflectometry (GNSS-R) along a Cyclone Global Navigation Satellite System (CYGNSS) track in the San Luis Valley, Colorado, USA, is presented. The three models are the analytical Kirchhoff solutions (AKS), the Soil And VEgetation Reflection Simulator (SAVERS), and the improved geometrical optics with topography (IGOT). Common inputs to the three models were defined by using field samples of soil moisture and texture, soil surface roughness measurements, and a digital elevation model (DEM). The resulting peak reflectivity profiles of the models and the CYGNSS data all had a dynamic range of 10 dB along the selected track, mainly due to the influence of topography. The reflectivities obtained from all three models agreed with one another to within 2.4 dB along the full length of the track. The models also showed general agreement with the corresponding CYGNSS data, although the modeled profiles were higher and smoother. Additional characterization of fine-scale surface roughness is identified as an area for future work to improve model fidelity. An intercomparison of DDM structure for three selected acquisitions is also provided.

Attention Based Convolutional Denoising Autoencoder for Two-lead ECG Denoising and Arrhythmia Classification

Today’s Massive MIMO cellular operation is dominated by orthogonal frequency division multiplexing (OFDM) modulation. One of the advantages of OFDM is the flexibility to carve up the available spectrum into resource blocks (RBs) that can operate adjacent to one another.  Massive MIMO adds spatial multiplexing layers on top of the RBs, enabling the simultaneous operation of dozens of UEs.  Cyclic prefixed single carrier modulation (CP-SCM) is an alternative to OFDM that also benefits from massive MIMO and is useful as an OFDM alternative in specific scenarios.  However, until recently, no resource allocation method has been proposed for CP-SCM.  In this paper, we present a CP-SCM resource allocation scheme using virtual antennas in a massive MIMO time domain duplexed scenario.  By creating several virtual antennas for each physical antenna, the benefits of massive MIMO are achieved with a smaller physical antenna count.  Resources are quantized into data streams, and each user can be assigned a variable number of simultaneous streams.  This paper presents a detailed development and analysis of multi-stream processing (MSP) for both uplink detection and downlink precoding.  We also introduce heterogeneous MSP, where CP-SCM and OFDM signals can be processed in the same MSP framework.

A panoramic ultra-high resolution photonic integrated circuit spectrometer is under development by the authors. The architecture comprises a tunable ring resonator stage and an AWG stage. The resolution defines the bandwidth of the ring resonator determined by the cross-coupled power and hence the gap between the access and ring waveguides. The AWG channel frequency spacing determines the required free-spectral range (FSR) and hence the perimeter of the ring resonator. The specified < 1GHz resolution combined with a FSR of 50 GHz render accurate simulation difficult obstructing the design process. In this report, a simplified design rule to determine the minimum gap between straight access waveguides and a circular ring waveguide is proposed. Realistic assumptions such as existence of local bisymmetry and adiabatic mode evolution throughout the coupling region permit a simple mode solver to determine the relationship between the cross-coupled power and the minimum gap size. A parameter extraction method is also formulated for add-drop rings equipped with two nominally identical couplers that disentangles the loss and coupling ring parameters from intensity-only transmission measurements. The proposed rule is applied to the design of ring resonators fabricated on a Si3N4 platform. The parameter extraction method is used to analyze the measured characterization data of the ring resonators. The results show good agreement between the design rule and parameters extracted from the measured data (measurement shows maximum deviation of ~43 nm from the design rule estimation) and provide experimental confirmation of the technological viability of the ring resonators required by the spectrometer.

In this paper, we propose a novel concept for engineered molecular communication (MC) systems inspired by animal olfaction. We focus on a multi-user scenario where several transmitters wish to communicate with a central receiver. We assume that each transmitter employs a unique mixture of different types of signaling molecules to represent its message and the receiver is equipped with an array comprising R different types of receptors in order to detect the emitted molecule mixtures. The design of an MC system based on \textit{orthogonal} molecule-receptor pairs implies that the hardware complexity of the receiver linearly scales with the number of signaling molecule types Q (i.e., R=Q). Natural olfaction systems avoid such high complexity by employing arrays of \textit{cross-reactive} receptors, where each type of molecule activates multiple types of receptors and each type of receptor is predominantly activated by multiple types of molecules albeit with different activation strengths. Motivated by this observation, we first develop an end-to-end MC channel model that accounts for the key properties of olfaction.

A document by Mounir Benamar . Click on the document to view its contents.

Magnetic nanoparticles are being increasingly used in numerous biomedical applications for diagnosis and therapy. During the course of these applications nanoparticle biodegradation and body clearance may occur. In this context, a portable, non-invasive, non-destructive and contactless imaging device can be relevant to trace the nanoparticle distribution before and after the medical procedure. We present a method for $in\:vivo$ imaging the nanoparticles based on the magnetic induction technique, and we show how to properly tune it for magnetic permeability tomography, maximizing the permeability selectivity. A tomograph prototype was designed and built to demonstrate the feasibility of the proposed method. It includes data collection, signal processing and image reconstruction. Useful selectivity and resolution are achieved on phantoms and animals, proving that the device can be used to monitor the presence of magnetic nanoparticles without requiring any particular sample preparation. By this way, we show that magnetic permeability tomography may become a powerful technique to assist medical procedures.

Trip purpose is essential information supporting tasks in intelligent transportation systems, such as travel behaviour comprehension, location-based service, and urban planning. The observation of trip purpose is a necessary aspect of travel surveys. However, owing to the sampling volume, survey budget, and survey frequency, relying solely on travel surveys in the era of big data is a difficult task. There has long been a demand for an accurate, generalizable, and robust inference method for trip purposes. Although existing studies contributed significant efforts to improve the trip purpose inference, the potential of leveraging the trip chain is insufficient. The spatial correlations and chaining patterns hidden in travelled zones are worthy of further exploration. The unequal importance within trip chains has not been clearly represented. Additionally, complex activity-zone mutual interdependence has not been considered in previous models. Herein, we propose a framework- Dual-Flow Attentive Network with Feature Crossing (DACross), specifically for inferring the chained trip purpose. We form trip chains innovatively that treat trip activities and travelled geographic zones as two chains with mutual interactions. We propose DACross, which consists of two parallel attentive branches and a co-attentive feature crossing module, for fully learning the intra- and inter-chain dependencies. We conducted extensive experiments on four large-scale real-world datasets to evaluate not only the performance of DACross but also the generalizability of the proposed framework among different cities and scenarios. Notably, the Experimental results prove the overall superiority of the proposed DACross.

We explore compatibility of Ru with Al-Ge eutectic wafer bonding. We first present experiments to check for the presence of Ru ternary alloy poisoning inhibiting Al-Ge melting as well as evaluations of Al-Ge melt wettability on Ru and diffusion outcomes following bond-simulating anneals. Results show that Ru is stable with no observed microstructural changes or dissolution in the melt, indicating no ternary poisoning for the applied thermal budget. Ru was found to act as an effective barrier offering good melt wettability in all considered configurations with Al and Ge. From inspection of the binary constituents of Al-Ge-Ru we propose that Al-Ge eutectic melting temperature will decrease marginally for Ru contamination in a 1-2% range before a drastic increase in melting temperature (>10°C/% Ru) at higher Ru compositions. We then demonstrate wafer-level packaged 200 mm devices and MEMS with strong bond outcomes of devices bearing Ru contacts. We conclude that Ru has high compatibility with Al-Ge eutectic bonding.

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

Present-day scenarios demand high computational power, compact, fast, and less power-hungry components. To resolve these critical issues one attempt is to integrate emerging magnetic devices with existing conventional technologies. The applications in which accuracy can be compromised to some extent in a trade-off for other attributes like energy, area, and delay is approximate computing. An efficient full adder circuit is crucial for arithmetic operations. This paper proposes a novel spintronic approximate full adder circuit based on an emerging magnetic tunnel junction (MTJ) which offers partial non-volatility, low energy consumption, area efficiency, and speed over an exact adder. By performing the simulations, the effect of STT, SHE, and VCMA switching schemes are demonstrated on the performance of the adders. The superiority of the proposed adder circuit at the fixed optimum value of VCMA and Hext over the existing adder is also shown. The proposed design has an exact carry output and approximate sum output with an accuracy of 62.5%.

This paper comprehensively addresses homomorphic encryption from both theoretical and practical perspectives. The paper delves into the mathematical foundations required to understand fully homomorphic encryption FHE. It consequently covers design fundamentals and security properties of FHE, and describes the main FHE schemes based on various mathematical problems. On a more practical level, the paper presents a view on privacy-preserving Machine Learning using homomorphic encryption, then surveys FHE at length from an engineering angle, covering the potential application of FHE in fog computing, and cloud computing services. It also provides a comprehensive analysis of existing state-of-the-art FHE libraries and tools, implemented in software and hardware, and the performance thereof.

This paper presents an analysis for the Age of Information (AoI) in a wireless sensor network consisting of multiple VLC/RF IoT sensors. In this network, we use an energy harvesting method, and all sensors utilize the stored energy in their batteries and transmit update packets with a specific power. We present two main optimization problems based on PD-NOMA scheme for average AoI with the sensor’s transmit power constraint. By optimizing these problems, the average AoI for each sensor and the total average AoI in the proposed system are reduced by 10% and 15%, respectively.

Crosstalk noise between the two force components (axial and transverse) and temperature is always present when the fibre Bragg grating (FBG) sensor technology is utilized in many sophisticated equipment. To address this, we proposed a theoretical method that decouples the two force components while eliminating the effect of temperature, using a combination of modified FBGs and a bandwidth modulation mechanism. Our previous study showed the first step in our continuous effort to prove the concept. In this study, the second part of proving the decoupling approach while avoiding the temperature effect is proved experimentally. In addition to the tapered FBG (TFBG) in its neutral axis, a hollow shaft prototype that resembles the construction of several medical surgery equipment is being developed further to include a linear chirped FBG (CFBG) along its shaft’s surface. The experimental results demonstrate that the estimated axial and transverse force values are consistent with their actual values, with RMS errors of less than 0.32 N and less than 0.16 N, respectively, over the range of (0 N – 10 N). The presented method can potentially be extended to small surgical instruments such as ophthalmia’s needle and ablation catheter.

Physical layer security (PLS) is an essential way to provide security to users in wireless networks against active or passive attacks. The quantification of the provided security is measured through secrecy outage probability and outage probability. For cognitive vehicular networks (CVN), PLS can increase the amount of the quality of services in infotainment applications. Due to the broadcast nature of the wireless channels, it is challenging to achieve the perfect secrecy between the transmitting and receiving nodes. Furthermore, in CVN, when resources are being shared in an underlay manner, the need arises to find the highest and lowest achievable quantification of performance measures for poor fading scenarios. The knowledge of the maximum achievable performance helps to design and develop the anti eavesdropping solutions. In a particular direction, firstly, this paper finds the closed-form expressions of first-order secrecy metrics over multiple input multiple output 2x2 Nakagami-m channel for vehicular networks. The derived closed-form expressions are further utilized to find the upper and lower bounds of secrecy outage probability, and outage probability using the integral bound method for CVN. The derived bound provides the knowledge of the region over a valid signal-to-noise ratio for which the maximum and minimum achievable performance can exist. To restrict the amount of eavesdropping, the convex optimization-based approach is proposed. The optimization method helps secrecy metrics to remain in a specific region of the value. Therefore, the work provides insights over the classical approach and the information-theoretic approach. These works enhance the knowledge to prepare the anti-eavesdropping methods for connected cars. Moreover, the derived analytical expressions demonstrate the impact of the wireless medium on secrecy performance while the derived bound demonstrates the impact of the magnitude of wireless fading parameters.

In this paper, a quasi-synchronization operation of a doubly-fed linear motor is proposed to achieve accurate regulation of both the traction and the contactless power transfer. A new control structure is proposed to achieve the loose coupling control between the stator side and the mover side, where the scalar control is used for the stator side controller (SSC), and the field-oriented control (FOC) is adopted for the mover side controller (MSC). The SSC and the MSC is with “frequency-coupling”, which enhances the reliability of the whole control system with less information exchange between the SSC and the MSC. The effectiveness of the proposed design is validated through both simulation and experimental studies.

This work proposes a hybrid intelligent Deep Learning (DL)-enabled mechanism to secure IIoT infrastructure from lethal and sophisticated multi-variant botnet attacks. The proposed mechanism has been rigorously evaluated with latest available dataset, standard and extended performance evaluation metrics, and current DL benchmark algorithms. Besides, cross validation of our results are also performed to clearly show overall performance.