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This work presents two 4-bit resistor-string digital-to-analog converters (R-DAC) designed in 22nm FDSOI technology. Both DACs are connected to a shared resistor string to make the final layout more compact. The small on-resistance of the Transmission-Gate (TG) switches designed in the FDSOI node yields a low Internal non-linearity (INL) and Differential non-linearity (DNL) in the DACs output. The effect of the temperature variations on the linearity performance of the DACs is also studied. It is shown that the temperature gradients can be compensated for by equally distributing the switches on the layout area. Post-layout simulations show an approximately fixed INL and DNL of, respectively, 0. 17LSB and 0. 1LSB over a wide temperature range from-40°C to 125{0} C. Two R-DACs dissipate the static/dynamic power of 0. 12/0.155mW with the layout size of only 70 mu m{2}, showing a high performance for two 4-bit DACs.

In this paper, the benefits of the Negative-Capacitance FET (NCFET) in the design of a Low Noise Amplifier (LNA) are assessed. The effect of gain enhancement due to the Ferroelectric (Fe) layer on the performance of a common-source (CS) LNA is analytically modeled for NCFETs with 14 nm FinFET as the base technology. Simulations show a high gain for the NCFET-based LNA. Such performance in conjunction with the integrability with CMOS technology indicates the potential of NCFET for analog/RF design.

‘Common Law’ judicial systems follow the doctrine of precedent, which means the legal principles articulated in court judgements are binding in subsequent cases in lower courts. For this reason, lawyers must search prior judgements for the legal principles that are relevant to their case. The difficulty for those within the legal profession is that the information that they are looking for may be contained within a few paragraphs or sentences, but those few paragraphs may be buried within a hundred-page document. In this study, we create a schema based on the relevant information that legal professionals seek within judgements and perform text classification based on it, with the aim of not only assisting lawyers in researching cases, but eventually enabling large-scale analysis of legal judgements to find trends in court outcomes over time.

In this paper, a small-signal model of Negative Capacitance FETs (NCFETs) is developed and the analog performance of NCFETs is studied using the developed model. A new ferroelectric factor K is introduced to capture the ferroelectric gain in NCFETs as compared to traditional small signal MOSFET/FinFET models. Using our new NCFET small-signal model, we show analog design trade-offs between various analog benchmarks such as gain, bandwidth, cut-off frequency, and linearity. Additionally, the developed model is used to demonstrate trade-offs in NCFET analog performance as ferroelectric parameters are changed. Results show that if pushed for a higher intrinsic gain via thicker Fe layers in NCFETs, the linearity of the device suffers. This reveals inherent device level trade-off in NCFETs for analog circuit performance.

This paper presents for the first-time a physics-based non-linear large signal model for Ka-band GaN power amplifier design using the new industry standard ASM-HEMT compact model. A novel methodology combining the effectiveness and accuracy of modeling the intrinsic device region with ASM-HEMT, and distributed effects at Ka-band with electromagnetic (EM) simulations is developed. The intrinsic semiconductor region for each finger of the GaN HEMT device is modeled with ASM-HEMT, and in a multi-finger device, the single finger model is coupled with EM simulations capturing distributed effects accurately. The developed non-linear model shows excellent accuracy with measured non-linear data for a commercial GaN-HEMT device, and with measurements performed on a Ka-band MMIC power amplifier.

Mumbai is the commercial capital of the country. The economy and morphology of the city has been shaped by the physical infrastructure but has neglected the ecological and social aspects in planning. This has led to the extreme vulnerability of the region to ecological and social negative externalities. The region experiences urban flooding every year disrupting the daily lives and inflicting loss to both the life and livelihood of many. Also, the state of emergency due to climate change that the planet deals with fighting sustenance for humankind is a severe challenge. Especially Mumbai, one of the largest cities in the world, is at risk of being wiped out. It is built from an archipelago of islands, the city’s historic downtown core-the island city is particularly vulnerable along with most of the suburban districts. This leads to an urgent need for providing resilience to the socio-ecological system in the region by providing climate adaptive capacity against floods., Architecture, Urbanism and Building Sciences | Complex Cities

This paper presents a generalized formulation of a decoupling scheme for n ×n multivariable processes. The proposed Adj dynamic decoupling {mathcal{K}}-builds on deriving the decoupler based on the adjoint of the process transfer function matrix. The decoupler is designed such that it contains lesser dynamics yet ensures a performance close to the ideal decoupling. The proposed scheme always ensures the realiz-ability of the decoupler while providing a superior decoupling performance. Procedure for deriving the decoupler with simple rules is presented in this manuscript. The half-rule is utilized to obtain a simplistic description of the higher-order models. The applicability of the proposed decoupling scheme for lower as well as high-dimensional MIMO processes is demonstrated through various simulation studies. The effectiveness of the proposed scheme against existing decoupler is highlighted with a comparative performance evaluation study.

his manuscript introduces an optimal detuning approach for designing a centralized PI control system for multi-input multi-output (MIMO) processes. Based on the approach, two multivariable PI controller designs are proposed in this manuscript. The proposed approach formulates the centralized PI controller design problem in an optimization framework and transforms it into an equivalent detuning parameter(s) design problem. While the centralized controller design with the proposed 1-Optimal Detuning Parameter (ODP) method is carried out as a multi-stage problem, the proposed 2-ODP method formulates the controller design as a single-stage optimization problem. An effective transfer function (ETF) parameterization followed by controller synthesis using the IMC theory and further the optimal detuning comprises the various stages in 1-ODP design. In this regard, a novel ETF parameterization procedure for large scale processes or systems with higher-order elements is presented in this manuscript. Contrary to the centralized controller design in the kp,ki space, where the dimensionality of the optimization problem blows at O(2n2), the proposed 1-ODP and 2-ODP design methods always aim at solving a uni- and bi-dimensional optimization problem, respectively, irrespective of the dimensionality of the MIMO process. Hence, the proposed method is easily applicable even to high-dimensional MIMO processes. Several illustrative industrial MIMO systems are considered to demonstrate the applicability of the proposed methods to highly interacting and large scale processes. The simulation studies show that the proposed methods performs better as compared to the other centralized PI controller designs. Even with parameter variations, the proposed methods give satisfactory closed-loop performance. Further, robust stability analysis for the proposed designs is performed by considering multiplicative input and output uncertainties.

Neuromorphic or bioinspired computational platforms, as an alternative for von-Neumann structures, have benefitted from the excellent features of emerging technologies in order to emulate the behavior of the biological brain in an accurate and energy-efficient way. Integrability with CMOS technology and low power consumption make ferroelectric field-effect transistor (FEFET) an attractive candidate to perform such paradigms, particularly for image processing. In this article, we use the FEFET device to make energy-efficient oscillatory neurons as the main parts of neural networks for image processing applications, especially for edge detection. Based on our simulation results, we estimated a significant energy efficiency compared with other technologies, which shows roughly 5-120\times reduction, depending on the design.