In this work, a thorough assessment of the robustness of complementary channel HfO2 ferroelectric FET (FeFET) against total ionizing dose (TID) radiation is conducted, with the goal of determining its suitability for use as high-performance and energy-efficient embedded nonvolatile memory (eNVM) for space applications. We demonstrate that: i) ferroelectric HfO2 thin film is robust against X-ray and proton irradiation; ii) FeFET exhibits a polarization state dependent radiation sensitivity where the high-VTH (HVT) state sees noticeable negative VTH shift and low-VTH (LVT) is immune to irradiation, irrespective of the channel type; iii) the state dependence is ascribed to the depolarization field in the HVT, which points toward the channel and facilitates the transport and trapping of radiation-generated holes close to the channel. In the future, radiation hardening techniques need to be considered.

A simple IOT-based soil and water testing system for evaluating the characteristics of arid soil was created. To track the changing soil quality and water availability while maximising water use effectiveness across the seasons, a sensor-based monitoring system with ethernet connectivity and mobile IoT is developed. This study is centred in the Indian state of Maharashtra, which is one of the major producers of oil and pulses and has a diversity of soil types. The primary crop that was taken into account was soybean because it is a crop that is widely grown in the area. Up until seed germination and roots, this crop was under observation. When compared to seeds produced using the traditional way of production, those produced using the IoT-based smart system were larger. Any automated irrigation system can benefit from this IOT-based monitoring system’s assistance. This method makes it very simple to collect data, analyse that data, and use that understanding to distribute water without the need for manual labour.

This paper is a comment to the article “A Novel Designed Sparse Array for Noncircular Sources with High Degree of Freedom” published by Mathematical Problems in Engineering Journal of Hindawi publishers. This comment identifies a few errors made by the authors of the above paper and provides suitable corrective measures.

A document by Enrico Maria Vitucci . Click on the document to view its contents.

The criteria for choosing the number and shape of the subarrays are examined. We propose a possible sub-array configuration that seems capable of offering good performance in terms of jammer and clutter cancellation.

Smartphone-mounted handheld GPR are mainly used for detecting rebar and are attracting attention in the field of infrastructure maintenance. However, the information obtained by electromagnetic wave radar is the round-trip propagation time of electromagnetic waves from the transmitting antenna to the receiving antenna, which requires estimation of the relative permittivity in the medium to be converted into distance information. In this study, we propose a method for estimating relative permittivity and depth that takes advantage of curve reactions generated from any reflective object, including rebar and cracks. First, we confirmed that the relative permittivity can be estimated with practicable accuracy by curve fitting, in which theoretical and measured curves are observed. Next, we proposed an algorithm that automatically extracts the range to be fitted, making it possible to obtain the relative permittivity and the depth to be estimated simultaneously. As a result, we succeeded in estimating the relative permittivity with high accuracy on the millimeter-order of less than 5% error in the 0.1 second range.

Smartphone-Mounted Handheld GPR are used to detect rebar, but quantitative detection of damage is difficult due to small reflectance. In this study, we propose an algorithm to quantitatively estimate damage thickness from received waveforms obtained from electromagnetic radar. A simple estimation method that separates peaks from above and below the crack from the time waveform is extremely difficult due to the presence of subtractive interference and side lobes. Therefore, we focus on the amplitude spectrum with the phase information dropped and estimate the damage thickness by pattern matching with a rigorous theoretical spectrum that takes multiple reflections into account. Rough damage thickness is determined by first combining multiple centroids of amplitude intensity and low-frequency components, and then spectral pattern matching is performed within the gating and bandwidth ranges set for each region, which also contributes to improving processing speed. As a result, damage thicknesses from 2 mm to 180 mm could be quantitatively estimated with a single algorithm in the 0.001 second range, confirming the practical feasibility of this algorithm.

This paper explicates the design and implementation of a switch capacitor DC-DC converter system for  Radio Frequency (RF) energy harvesting applications for an input voltage in the sub-150mV range, using 180-nm CMOS triple-well BCD technology. The proposed system incorporates a charge pump architecture that employs an improvised Dynamic Gate Biasing (DGB), Forward and Reverse Body Bias technique (FRBB), along with a time axis symmetrical clocking scheme implemented using an advanced bootstrapped CMOS driver to enhance the overall drive capability of the system at low input voltages. Post-layout extracted simulations demonstrate that the proposed system achieves higher overall efficiency, delivering a peak Power Conversion Efficiency (PCE) of 85.8% at 125mV input voltage, outperforming other state-of-the-art architectures in similar voltage ranges. Moreover, the proposed system exhibits reliable operation even at input voltages as low as 85mV, while maintaining good overall efficiency.

Single-photon avalanche detectors (SPADs) are well-suited for satellite-based quantum communication because of their advantageous operating characteristics as well as their relatively straightforward and robust integration into satellite payloads. However, space-borne SPADs will encounter damage from space radiation, which usually manifests itself in the form of elevated dark counts. Methods for mitigating this radiation damage have been previously explored, such as thermal and optical (laser) annealing. Here we investigate in a lab, using a CubeSat payload, laser annealing protocols in terms of annealing laser power and annealing duration, for their possible later use in orbit. Four Si SPADs (Excelitas SLiK) irradiated to an equivalent of 10 years in low Earth orbit exhibit very high dark count rates (>300 kcps at -22 C operating temperature) and significant saturation effects. We show that annealing them with optical power between 1 and 2 W yields reduction in dark count rate by a factor of up to 48, as well as regaining SPAD sensitivity to a very faint optical signal (on the order of single photon) and alleviation of saturation effects. Our results suggest that an annealing duration as short as 10 seconds can reduce dark counts, which can be beneficial for power-limited small-satellite quantum communication missions. Overall, annealing power appears to be more critical than annealing duration and number of annealing exposures.

This paper would introduce new method to approach magnetism in multidimensional structure of atoms.

Performance modelling of a deep learning application is essential to improve and quantify the efficiency of the model framework. However, existing performance models are mostly case-specific, with limited capability for the new deep learning frameworks/applications. In this paper, we propose a generic performance model of an application in a distributed environment with a generic expression of the application execution time that considers the influence of both intrinsic factors/operations (e.g. algorithmic parameters/internal operations) and extrinsic scaling factors (e.g. the number of processors, data chunks and batch size). We formulate it as a global optimization problem and solve it using regularization on a cost function and differential evolution algorithm to find the best-fit values of the constants in the generic expression to match the experimentally determined computation time. We have evaluated the proposed model on three deep learning frameworks (i.e., TensorFlow, MXnet, and ytorch). The experimental results show that the proposed model can provide accurate performance predictions and interpretability. In addition, the proposed work can be applied to any distributed deep neural network without instrumenting the code and provides insight into the factors affecting performance and scalability.

Design, analysis and development a Type IV composite pressure vessel.

We propose a peak-tracking BOTDA (PT-BOTDA) equipped with an efficient dynamic Brillouin frequency shift (BFS) searching scheme based on ternary search. The proposed scheme establishes a feedback loop between the chosen frequency and the corresponding Brillouin gain to reduce the required number of scanning frequencies in one measurement. We also evaluate the performance of the proposed scheme under scenarios of different searching granularities and dynamic sensing ranges. Experimental results indicate that in all situations, the proposed PT-BOTDA can achieve at least 85% reduction in the scanning frequency number with a 3-meter spatial resolution, while maintaining a convincing BFS searching accuracy under sufficient SNR condition.

This survey is the first work on the current standard for lightweight cryptography, standardized in 2023 and used for security of embedded systems. Security issues as well as implementations and side-channel attacks for this lightweight standard by NIST is discussed.

We all know and often use compression software, why the compression software cannot reduce the file size after compressing the compressed file, and even multiple compressions will make the file size larger. Through research on compression software and compression algorithms, we found that based on previous theories, data compression has a limit. This article provides a new theory, expounds a new mathematical method, and implements a new compression algorithm, which can compress files multiple times and accumulate the compression rate, for example, compressing a 1Gb file into 1Kb.

The study presents a new approach for solving the sensor subset selection problem using set encoding and genetic algorithms, aiming to minimize the number of sensors while maintaining accurate spatial estimation. The proposed method, tested on groundwater data from the Savannah River Site, introduces novel crossover and mutation methods, outperforming a previous greedy method with an R2 higher than 0.98 for reduced sensor counts.

In this paper we present a new decomposition and generative model for functional connectivity (FC), achieve 10x data compression, 97.3% identifiability, and modest improvent on FC-based predictive tasks. Additionally we are able to generate synthetic subjects with user-inputted clinical characteristics. fMRI and phenotype data came from the Neurodevelopmental Genomics: Trajectories of Complex Phenotypes database of genotypes and phenotypes repository, dbGaP Study Accession ID phs000607.v3.p2, as well as the Bipolar and Schizophrenia Network for Intermediate Phenotypes study (http://b-snip.org/). Additional data from OpenNeuro study ds004144 on fibromyalgia is included in the linked-to code.

In this paper, the efficiency and the quality factor (Q) of an infinitesimal loop antenna with the circumference of 0.01λ enclosed in a µ-negative (MNG) shell of 0.023λ diameter is investigated. It is demonstrated that an MNG shell can be designed to produce an electrically small system with a matched input impedance leading to total efficiency approaching unity. Simulation results show that the fractional bandwidth of significantly better than Chu limit can be obtained, especially if the material is regarded dispersionless. The calculated Q of the antenna with LL model, M model, and Z model MNG are 74.5%, 55.9%, and 37.5% of those predicted by Chu limit, respectively.