Dongseok Jeon

A syringe-implantable electrocardiography (ECG) monitoring system is proposed. The noise optimization and circuit techniques in the analog front-end (AFE) enable 31 nA current consumption while a minimum energy computation approach in the digital back-end reduces digital energy consumption by 40%. The proposed SoC is fabricated in 65 nm CMOS and consumes 64 nW while successfully detecting atrial fibrillation arrhythmia and storing the irregular waveform in memory in experiments using an ECG simu

A physically based semiempirical model for electron mobilities of the MOSFET inversion layers that is valid over a large temperature range (77 K<or=T<or=370 K) is discussed. It is based on a reciprocal sum of three scattering mechanisms, i.e. phonon, Coulomb, and surface roughness scattering, and is explicitly dependent on temperature and transverse electric field. The model is more physically based than other semiempirical models, but has an equivalent number of extracted parameters. It is show

Advances in neural network and machine learning algorithms have sparked a wide array of research in specialized hardware, ranging from high-performance convolutional neural network (CNN) accelerators to energy-efficient deep-neural network (DNN) edge computing systems [1]. While most studies have focused on designing inference engines, recent works have shown that on-chip training could serve practical purposes such as compensating for process variations of in-memory computing [2] or adapting to

A bstract Measurements are presented of the differential cross sections for Z bosons produced in proton-proton collisions at $$ \sqrt{s} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msqrt> <mml:mi>s</mml:mi> </mml:msqrt> </mml:math> = 13 TeV and decaying to muons and electrons. The data analyzed were collected in 2016 with the CMS detector at the LHC and correspond to an integrated luminosity of 35 . 9 fb − 1 . The measured fiducial inclusive product of cross section and bra

A temperature-dependent model for long-channel silicon-on-insulator (SOI) MOSFETs for use in the temperature range 27 degrees C-300 degrees C, suitable for circuit simulators such as SPICE, is presented. The model physically accounts for the temperature-dependent effects in SOI MOSFETs (such as threshold-voltage reduction, increase of leakage current, decrease of generation due to impact ionization, and channel mobility degradation with increase of temperature) which are influenced by the unique

This paper proposes a design approach targeting circuits operating at extremely low supply voltages, with the goal of reducing the voltage at which energy is minimized, thereby improving the achievable energy efficiency of the circuit. The proposed methods accomplish this by minimizing the circuit's ratio of leakage to active current. The first method, super pipelining, increases the number of pipeline stages compared to conventional ultra low voltage (ULV) pipelining strategies, reducing the le

Electrocardiography (ECG) is a critical source of information for a number of heart disorders. In arrhythmia studies and treatment, long-term observation is critical to determine the nature of the abnormality and its severity. However, even small body-wearable systems can impact a patient's everyday life and signals captured using such systems are prone to noise from sources such as 60Hz power and body movement. In contrast, implanted devices are less susceptible to these noise sources and, whil

Modern deep learning-based models have seen outstanding performance improvement with speech enhancement tasks. The number of parameters of state-of-the-art models, however, is often too large to be deployed on devices for real-world applications. To this end, we propose Tiny Recurrent U-Net (TRU-Net), a lightweight online inference model that matches the performance of current state-of- the-art models. The size of the quantized version of TRU-Net is 362 kilobytes, which is small enough to be dep

In this paper, the authors also show how clocking overhead can be reduced through circuit techniques to facilitate super pipelining while process variation is addressed through the use of latch-based design. Additionally, architecture modifications are proposed to improve energy efficiency and throughput. Measurements show that the FFT core consumes 17.7nJ per 1024-pt complex FFT while operating at 30MHz at V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999

Recent advances in neural network (NN) and machine learning algorithms have sparked a wide array of research in specialized hardware, ranging from high-performance NN accelerators for use inside the server systems to energy-efficient edge computing systems. While most of these studies have focused on designing inference engines, implementing the training process of an NN for energy-constrained mobile devices has remained to be a challenge due to the requirement of higher numerical precision. In

An inclusive search is presented for long-lived particles using displaced jets. The search uses a data sample collected with the CMS detector at the CERN LHC in 2017 and 2018, from proton-proton collisions at a center-of-mass energy of 13 TeV. The results of this search are combined with those of a previous search using a data sample collected with the CMS detector in 2016, yielding a total integrated luminosity of 132 fb -1 . The analysis searches for the distinctive topology of displaced track

A search for long-lived particles decaying to displaced, nonprompt jets and missing transverse momentum is presented. The data sample corresponds to an integrated luminosity of 137 fb − 1 of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC in 2016–2018. Candidate signal events containing nonprompt jets are identified using the timing capabilities of the CMS electromagnetic calorimeter. The results of the search are consistent with the

This paper presents an energy-efficient face detection and recognition processor aimed at mobile applications. The algorithmic optimizations including hybrid search scheme for face detection significantly reduce computational complexity and architecture modification such as feature memory segmentation and further reduce energy consumption. We utilize characteristics of the implemented algorithm and propose a 5T SRAM design heavily optimized for mostly-read operations. Systematic reset and write

This article analyzes the efficient mechanism for downsizing the public sector, focusing on adverse selection in productive efficiency. Each worker is assumed to have two type-dependent reservation utilities: the status quo utility in the public sector before downsizing and the utility that the worker expects to obtain by entering the private sector. The efficient mechanism consists of a menu of probability (of remaining in the public sector) and transfer pairs that induces self-selection. A wor

This paper proposes a design methodology for voltage overscaling (VOS) of ultra-low-power systems. This paper first proposes a probabilistic model of the timing error rate for basic arithmetic units and validates it using both simulations and silicon measurements of multipliers in 65-nm CMOS. The model is then applied to a modified K-best decoder that employs error tolerance to reveal the potential of the framework. With simple modifications and timing error detection-only circuitry, the convent