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

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

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.

Abstract

Approximate Computing techniques are finding a central role in modern applications, by optimizing architectures to relax some computation but with a constrained inaccuracy. In many applications, the FFT algorithm is invariably applied and there is a need for approximate low energy hardware solutions to the FFT. The paper thus proposes an approximate, fixed-point, in-place, shared memory architecture for FFT. It is well observed that the energy at FFT I/Os is not strictly contiguous, hence the proposed FFT exploits this window to tune the error. The proposed FFT and its associated butterfly unit is constructed to efficiently incorporate approximate Toom–Cook multiplication. As said, a supporting function in error correction based on the sparsity patterns, is a feature of this design. The design synthesized at 32 n m shows on average, a 48.6% and 52.8% improvement in consumption of area and energy, respectively …

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

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 scalability of remote Internet of Things (IoT) deployments into verticals of smart cities relies primarily on the communication protocols and data platforms employed. Accordingly, the adoption of LoRaWAN, Sigfox, NB-IoT, etc. has risen in recent years. These protocols have been created to cater to the low power and long range requirements of IoT. In this paper, we evaluate one such protocol, Wi-SUN (Wireless Smart Ubiquitous Network), that additionally offers excellent redundancy owing to its use of a mesh topology. Wi-SUN is based on the IEEE 802.15.4g standard and uses license-free sub-GHz bands. However, IoT networks using any communication protocol require a knowledge of signal propagation and attenuation in real-world scenarios. Thus, we evaluated the path loss of Wi- SUN transmissions by analysing the RSSI values inside a typical city building and an urban outdoor habitat. Keywords—Path Loss,

Abstract

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

Abstract

SS02. 00002: Single and double touch mode capacitive pressure/force sensing technique and approach*

Abstract

Linear n-local networks are compatible with quantum-repeater-based entanglement distribution protocols. Different sources of imperfections such as error in entanglement generation, communication over noisy quantum channels, and imperfections in measurements result in decay of quantumness across such networks. From practical perspectives it becomes imperative to analyze the nonclassicality of quantum network correlations in the presence of different types of noise. The present discussion provides a formal characterization of non-n-local features of quantum correlations in a noisy network scenario. In this context, persistency of non-n-locality has been introduced. Such a notion helps in analyzing decay of non-n-local features of network correlations with increasing length of the linear network in the presence of one or more causes of imperfections.