Abstract

PP10. 00010: Structural engineering methods to combine the diaphragm and cantilevers for flexible capacitive pressure sensor*

Abstract

Plantar pressure or foot pressure analysis is a predominant tool for biomedical assessment of posture, gait, and other activities. The distribution and magnitude of pressure can provide fruitful information to diagnose or predict any risk of foot disorders or impairments. This paper presents the design and fabrication of a low-cost, flexible pressure sensor (FLEPS) mat for assessing plantar pressure variations. We have designed a 32 × 32 velostat-based piezoresistive pressure sensor array with dimensions of 330 mm × 330 mm and an active sensing area of 284 mm × 284 mm. Each sensor pixel is of size 5 mm × 5 mm with a pitch of 4 mm. To enhance the resolution and the visual quality of the heat map obtained, we have used different interpolation techniques like the nearest neighbor, bilinear, and bicubic for the received data and transformed the 32 × 32 array to a 100 × 100-pixel array. It was observed that the bicubic interpolation technique gives a better image quality but takes more computation time than the other two interpolation techniques. Index Terms—Flexible pressure sensor, Interpolation, Piezore- sistive, Plantar pressure, Velostat.

Abstract

The continuous monitoring of maternal vital signs, particularly during labor, can be of critical importance for the health of the child and mother. We present a compact wearable electronic system that measures, in real-time, maternal heart rate using electrocardiography (ECG) signals. The heart rate is determined using moving average filters to remove the noises in the signal and using autocorrelation for the detection of periodic signals. We use electromyography (EMG) signals for calculating uterine contractions using the root mean sum of filtered signal values. The resulting system can identify heart rate in a female subject with an accuracy of ± 2.9bpm, and uterine contraction intensity within ± 5 units compared to values obtained from a gold-standard CTG machine. The system is accurate, low-cost, and portable, so that it can be deployed at primary healthcare centers in low-income countries. The system can also be

Abstract

Bayesian Optimization (BO) is used to find the global optima of black box functions. In this work, we propose a practical BO method of function compositions where the form of the composition is known but the constituent functions are expensive to evaluate. By assuming an independent Gaussian process (GP) model for each of the constituent black-box function, we propose EI and UCB based BO algorithms and demonstrate their ability to outperform vanilla BO and the current state-of-art algorithms. We demonstrate a novel application of the proposed methods to dynamic pricing in revenue management when the underlying demand function is expensive to evaluate.

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With the Integrated Circuits becoming pervasive in all key industries and applications, PUF’s has gained immense popularity for securing the IC’s by providing unique identification code to each chip. Designing a highly efficient PUF with optimal values of uniqueness and reliability is a significant challenge. Uniqueness depends on process variations during chip fabrication, and reliability depends on the chip’s ability to resist changes to supply voltage and temperature variations. Multiple PUF designs that employ reliability enhancement circuits and security algorithms achieve these design characteristics. Nonetheless, these techniques are design overheads. This paper presents a novel Physical Unclonable Function (PUF) based on the ProHys switch. It deals with hysteresis and proteresis mode of operation, which are complementary to each other. The Prohys PUF befittingly satisfies both uniqueness and reliability

Abstract

In the channel code detection problem, given a sequence of noise-affected codewords generated by an unknown code, the aim is to identify the correct channel code from the given set of potential codes. This problem has many applications in military spectrum surveillance and in cognitive radios. In this paper, we consider the situation when the set of potential channel codes consists of two linear block codes and propose a deep learning based classification approach for the corresponding code detection problem. In this work, we propose data processing strategies suitable for linear block codes that reduce the amount of data required to train the deep neural network classifier. This however comes at the cost of having a lower probability of detection. For the proposed data processing strategies, we analytically obtained the optimal probability of correct detection that one can hope to achieve using any neural …

Abstract

In Himalayas, the high-elevational mountains have warmed more rapidly in recent decades than other areas of the globe. Himalayan timberline is climate dependent and sensitive to changes, thus can provide biological proof of global warming. The present analysis changes in timberline elevations over four decades and corresponding climatic parameters (temperature and precipitation) in the Western Himalayan region (Himachal Pradesh). Landsat-2 Multispectral Scanner (MSS) and Landsat-8 were used to evaluate the long-term (1976–2015) timberline dynamics. The climate data APHRODITE was used to calculate the annual mean temperature and annual precipitation along the spatially distinct timberline locations. The mean elevation of timberline position has shifted vertically 145 m with a rate of ~37 m per decade (@ 3.7 m per year) over the past four decades, however majority of timberline remained

Abstract

Systems of differential equations with polynomial right-hand sides are very common in applications. In particular, when restricted to the positive orthant, they appear naturally (according to the law of mass-action kinetics) in ecology, population dynamics, as models of biochemical interaction networks, and models of the spread of infectious diseases. On the other hand, their mathematical analysis is very challenging in general; in particular, it is very difficult to answer questions about the long-term dynamics of the variables (species) in the model, such as questions about persistence and extinction. Even if we restrict our attention to mass-action systems, these questions still remain challenging. On the other hand, if a polynomial dynamical system has a weakly reversible single linkage class (WR1 ) realization, then its long-term dynamics is known to be remarkably robust: all the variables are persistent (i.e., no species goes extinct), irrespective of the values of the parameters in the model. Here we describe an algorithm for finding WR1 realizations of polynomial dynamical systems, whenever such realizations exist.

Abstract

The leading order production of an SM singlet-like scalar has primarily been realized through the gluon fusion process by mixing with the SU(2)_L scalar doublet of the model. The dominant part of the physical state, i.e., the singlet component, does not have any role in its direct production. Focusing on such a state with a mass smaller than the SM-like Higgs scalar, we calculate the dominant next-to-leading (NLO) order corrections to its production cross-section. With these improved cross-sections, the present and future LHC limits may become somewhat more stringent

Abstract

Identification of cancer subtypes based on molecular knowledge is crucial for improving the patient diagnosis, prognosis, and treatment. In this work, we integrated copy number variations (CNVs) and transcriptomic data of Kidney Papillary Renal Cell Carcinoma (KIRP) using a network diffusion strategy to stratify cancers into clinically and biologically relevant subtypes. We constructed GeneNet, a KIRP specific gene expression network from RNA-seq data. The copy number variation data was projected onto GeneNet and propagated on the network for clustering. We identified robust subtypes that are biologically informative and significantly associated with patient survival, tumor stage and clinical subtypes of KIRP. We performed a Singular Value Decomposition (SVD) analysis of KIRP subtypes, which revealed the genes/silent players related to poor survival. A differential gene expression analysis between