Abstract This paper describes the use of data analytics tools for predicting fatigue strength steels. Several physics-based as well data-driven approaches have been used to arrive at correlations between various properties alloys and their compositions manufacturing process parameters. Data-driven are significant interest materials engineers especially in arriving extreme value such cyclic fatigue, where current state-of-the-art physics based models severe limitations. Unfortunately, there...

Detection of true human emotions has attracted a lot interest in the recent years. The applications range from e-retail to health-care for developing effective companion systems with reliable emotion recognition. This paper proposes heart rate variability (HRV) features extracted photoplethysmogram (PPG) signal obtained cost-effective PPG device such as Pulse Oximeter detecting and recognizing on basis physiological signals. HRV both time frequency domain are used classification emotions....

Identification of pulmonary diseases comprises accurate auscultation as well elaborate and expensive function tests. Prior arts have shown that lead to abnormal lung sounds such wheezes crackles. This paper introduces novel spectral spectrogram features, which are further refined by Maximal Information Coefficient, leading the classification healthy sounds. A balanced sound dataset, consisting publicly available data collected with a low-cost in-house digital stethoscope used. The...

Mobile smartphones have revolutionized the concept of mobile phones as different apps are built to offer various interesting applications in healthcare, gaming, etc. rather than using phone only for voice services. The application developers take advantage onboard sensors, web connectivity and powerful processing units develop such apps. In this paper, we present an approach where direct acoustic coupling technique is employed quickly conveniently convert into high quality digital...

Analysis of heart sounds is a popular research area for non invasive identification several diseases.This paper proposes set 88 time-frequency features along with five different methodologies classifying normal and abnormal sounds.State the art approach was applied segregating fundamental sounds.Apart from baseline two class classifier, separate classifiers long short were also explored in order to get rid dependency on duration recordings.Finally, three classifier deal noisy data present...

Abstract This paper presents prediction of shelf-life ‘ Kesar ’ cultivar mangoes stored under specified conditions based on their respiration rate and ripeness levels. A deep-CNN was fine-tuned 1524 image data different to classify the levels as ‘unripe’, ‘early-ripe’, ‘partially-ripe’ ‘ideally-ripe’. CO 2 (RR CO2 ) further calculated using principle enzyme kinetics establish a correlation between RR Support Vector Regression model employed predict shelf life storage conditions, thereby...

The alarming statistics of Diabetes Mellitus (DM) Type 2 as the most common and prevalent disease in India world over [1] has fuelled research direction non-invasive continuous monitoring this disease. This paper describes a demonstration an inexpensive mobile-phone based android application which can collect Photoplethysmogram (PPG) from fingertip via built-in camera flash transfer it to high-end cloud server for early detection DM. Additionally, allows DM patients aid assisting short...

Abstract Ideally, ripe fruits offer appropriate nutritional content and best quality in terms of taste flavour. Prediction climacteric acts as the main marketing indicator for from consumer perspective thus renders it a genuine industrial concern all stakeholders fruit supply chain. However, building fruit-specific individual model prediction ripeness level remains an existing challenge due to scarcity sufficient labeled experimental data each fruit. This paper describes development generic...

Automatic classification of normal and abnormal heart sounds is a popular area research. However, building robust algorithm unaffected by signal quality patient demography challenge. In this paper we have analysed wide list Phonocardiogram (PCG) features in time frequency domain along with morphological statistical to construct discriminative feature set for dataset-agnostic cardiac patients. The large open access database, made available Physionet 2016 challenge was used selection, internal...

We present the development of a non-enzymatic glucose sensor integrated within packaging beverages, such as fruit juices, using modified gold electrodes. The primary aim this research is to enable real-time and non-invasive concentration detection in beverages like apple juice through electrochemical techniques. modification involved cyclic voltammetry-based deposition nanoparticles onto bare electrode surface. response, reusability, sensitivity towards are presented. Performance evaluation...

Robotic platforms are becoming increasingly important and have their utility cost completely justified during missions which require substituting humans. In this paper, we present our ongoing work in developing a multi-sensor robotic platform intended for deploying an indoor environment hazardous situations. The prime objective of such portable robots will be to conduct surveillance provide perception its surroundings the human-in-loop ascertain uncertain environment. Therefore, needs...

Eccrine sweat is an ideal surrogate diagnostic biofluid for physiological and metabolic biomarkers wearable biosensor design. Its periodic non-invasive availability candidate analytes such as glucose cortisol along with limited correlation blood plasma of significant research interest. An insilico model eccrine can assist in the development biosensors. In this regard, molecular modelling be employed to observe most fundamental interactions. Here, we determine a suitable building sweat. The...

Conventional towed arrays have been built with large diameters to allow separation of the boundary layer from array elements so that effect turbulent flow has less impact on signal noise ratio performance array. These arrays, therefore, tend be bulky and heavy. The successful development AUV USV required focus much smaller diameter light-weight arrays. Acoustic Research Laboratory (ARL) Tropical Marine Science Institute, National University Singapore, arising a recent requirement, developed...

Robot audition systems are expected to support a variety of civilian and rescue applications in hazardous situations. Sensed data can only be interpreted meaningfully when referenced the location sensor, making localization an important area research. In this paper, we have developed sound source system for our Fire Bird VI robot. Localization algorithms like cross correlation (CC), phase transform (PHAT) maximum-likelihood (ML) explored find direction arrival (DOA) by estimating time delay...

This paper presents a demo proposal of standalone smartphone application that can automatically analyse the signal quality PCG, as it is recorded on low-cost smartphone-based digital stethoscope. Features, related to inherent pattern autocorrelated envelope, have been used for classifying and discarding noisy portions from continuous PCG. Our has successfully deployed Nexus 5 tested several clean PCG signals with sensitivity 78.91% specificity 70.83%.

Simulation of various manufacturing processes such as heat treatments is rapidly gaining importance in the industry for process optimization, enhancing efficiency and improving product quality. Case carburization followed by quenching one significant treatment commonly used automotive industry. The equations to be solved simulation these are non-linear differential require use computationally intensive numerical techniques e.g. 3D Finite Element Modelling. Using models solving optimization...

Phonocardiogram (PCG) or auscultation via a stethoscope forms the basis of preliminary medical screening. But PCG recorded in an uncontrolled environment is inherently noisy. In this paper we have derived novel features from spectral domain and autocorrelation waveforms. These are used to identify quality recording accepting only diagnosable recordings for further analysis. proved be robust irrespective variations devices data collection protocols employed ensure consistent quality. A freely...

ABSTRACT Selecting suitable glucose-binding proteins (GBPs) is vital for biosensor development medical diagnostics and quality control in the food industry. Biosensors offer advantages such as high specificity, selectivity, fast response time, continuous measurement, cost-effectiveness. The current work utilized a combination of molecular docking, dynamics (MD) simulations, free energy calculations to develop high-throughput bioinformatics pipeline select GBP candidates from an extensive...

Eccrine sweat has emerged as a biomarker rich biofluid, motivating research in the development of wearable sensors for detection various analytes such glucose. Given trace quantities these analytes, computational model to investigate impact solvents, interference species, and temperature conditions will aid highly specific sensitive biosensors. We present comprehensive molecular incorporating candidate bioreceptor, target ligand, gold substrate an eccrine solution. This considers both...

The future of biosensing holds great promise as technological advancements continue to redefine our approach healthcare and personal well-being. Biosensors are devices that detect analyze biological information the key elements this transformative journey. Future wearables will not only track traditional metrics like heart rate activity but also offer sophisticated biomarkers for various analytes, enabling early detection diseases personalized treatment plans. Glucose is one such...