Multi-modal Human Fatigue Classification using Wearable Sensors for Human-Robot Teams

Our main objective of this study is to create a fatigue detection model using real-time data by using wearable sensors. The purpose of this research is to learn more about the way humans experience fatigue in a supervisory human-machine environment. The goal of this study is to evaluate machine learning algorithms that assess fatigue detection and to use robots for adapting its interactions. The environment itself consists of two different tasks to analyze Physical fatigue and Mental fatigue in two different task environments that are (i) Jigsaw puzzle-solving task, and (ii) Pick and Place task. Physical fatigue and mental fatigue are detected using wearable sensors: MYO armband and BioPac Bioharness. During the experiment, the Physiological metrics used are Heart rate, respiration rate, Heart rate variability, posture, breathing wave amplitude, and EMG. All these Physiological signals are collected simultaneously in a real-time task environment. The data collected by these physiological signals are then processed and machine learning and deep learning algorithms are used for further process in building a fatigue detection model

Effect of pregnancy-induced mass gain and footwear on postural stability

Pregnancy induces tremendous changes in the body, which increases the risk of falling. Falls are rarely as costly as when they happen during pregnancy, leading to tremendous healthcare, emotional, and societal costs. More than one in four women (27%) fall at least once during pregnancy. Despite overwhelming statistics, there is a dearth of interventions to minimize the risk of falling amongst pregnant women. Our goal was to quantify the effect of pregnancy-induced mass gain and footwear on postural stability throughout pregnancy, as a first step towards a deeper understanding of pregnancy-specific optimal postural strategies. Our main hypothesis was that both footwear and pregnancy mass affect postural stability.Postural stability was assessed on ten young healthy non-pregnant women and pregnancy was simulated by adding localized weights. Measurements were performed during four sessions (not pregnant, first, second, and third trimesters) wearing five types of footwear in randomized order: flats, sports, low heels, and sports and low heels with ankle brace. The center of pressure (COP) was determined for each instant in time and 22 COP-based postural stability indices (15 temporal and 7 spectral) were computed. The effect of pregnancy-induced mass gain and footwear on each index was assessed using repeated measures ANOVA.Pregnancy-induced mass gain and footwear have an influence on the postural stability of healthy young female subjects, independently of all other pregnancy-induced physical, hormonal, and psychological changes. Results demonstrated a decrease in mediolateral postural stability with mass gain and footwear such as heels. Ankle braces worn with sport shoes seem to increase postural stability. The decrease in postural stability is detected by a decrease in postural sway, due to a tighter postural adjustment and a rigidification of the posture. This rigidification of the posture results from muscle contraction, which would lead to muscle fatigue if performed continuously during a pregnancy.This study paves the way for a deeper understanding of postural strategies adopted by pregnant women while wearing different footwear, and thus for the development of efficient fall-avoidance strategies

WEB BASED MANAGEMENT SYSTEM FOR HOUSING SOCIETY

Web Based Management System for Housing Society plays a major role in our day-to-day life. We develop a global web dependent application using AngularJS, Node JS and MySQL, with Xampp as the server to make an effective management system. This system is designed to provide a user-friendly and efficient platform for managing all the details of daily notices, monthly meetings, events, payments, maids etc., This system mainly consists of three modules, they are: Admin, User and Security. Each module here serves specific features and functionalities present within society. Admin module provides the features for managing user, houses, security, maids, notices, events, payment and voting information where we can add and view the details required as per the features. User module has features like events, notices, payments and voting where we can view the information provided by admin and make an action according to that. Security module has features like visitors, maids, notices, events and provide information as per the specific feature

Power quality event classification using complex wavelets phasor models and customized convolution neural network

Origin and triggers of power quality (PQ) events must be identified in prior, in order to take preventive steps to enhance power quality. However it is important to identify, localize and classify the PQ events to determine the causes and origins of PQ disturbances. In this paper a novel algorithm is presented to classify voltage variations into six different PQ events considering the space phasor model (SPM) diagrams, dual tree complex wavelet transforms (DTCWT) sub bands and the convolution neural network (CNN) model. The input voltage data is converted into SPM data, the SPM data is transformed using 2D DTCWT into low pass and high pass sub bands which are simultaneously processed by the 2D CNN model to perform classification of PQ events. In the proposed method CNN model based on Google Net is trained to perform classification of PQ events with default configuration as in deep neural network designer in MATLAB environment. The proposed algorithm achieve higher accuracy with reduced training time in classification of events than compared with reported PQ event classification methods

DNA Bar-coding: A Novel Approach for Identifying an Individual Using Extended Levenshtein Distance Algorithm and STR analysis

DNA bar-coding is a technique that uses the short DNA nucleotide sequences from the standard genome of the species in order to find and group the species to which it belongs to. The species are identified by their DNA nucleotide sequences in the same way the items are recognized and billed in the supermarket using barcode scanner to scan the Universal Product Code of the items. Two items may look same to the untrained eye, but in both cases the barcodes are distinct. It was possible to create DNA-barcodes to characterize species by analysing DNA samples from fish, birds, mammals, plants, and invertebrates using Smith-waterman and Needleman-Wunsch algorithm. In this work we are creating human DNA barcode and implementing Extended Levenshtein distance algorithm along with STR analysis that uses less computation time compared to the previously used algorithms to measure the differential distance between the two DNA nucleotide sequences through which an individual can be identified

Securing Web Applications from malware attacks using hybrid feature extraction

In this technological era, many of the applications are taking the utilization of services of internet in order to cater to the needs of its users. With the rise in number of internet users, there's a substantial inflation within the internet attacks. Because of this hike, Web Services give rise to new security threats. One among the major concerns is the susceptibility of the internet services for cross site scripting (XSS). More than three fourths of the malicious attacks are contributed by XSS. This article primarily focuses on detection and exploiting XSS vulnerabilities. Generally, improper sanitization of input results in these type of susceptibilities. This article primarily focuses on fuzzing, and brute forcing parameters for XSS vulnerability. In addition, we've mentioned the planned framework for contradicting XSS vulnerability

Securing Web Applications from malware attacks using hybrid feature extraction

In this technological era, many of the applications are taking the utilization of services of internet in order to cater to the needs of its users. With the rise in number of internet users, there's a substantial inflation within the internet attacks. Because of this hike, Web Services give rise to new security threats. One among the major concerns is the susceptibility of the internet services for cross site scripting (XSS). More than three fourths of the malicious attacks are contributed by XSS. This article primarily focuses on detection and exploiting XSS vulnerabilities. Generally, improper sanitization of input results in these type of susceptibilities. This article primarily focuses on fuzzing, and brute forcing parameters for XSS vulnerability. In addition, we've mentioned the planned framework for contradicting XSS vulnerability

Exploring Nucleophagy and Inflammation in the Tumor Microenvironment

Nuclear stress and inflammation are intimately tied in tumorigenesis and cancer cell survival. Here, I explore immune environments across various types of cancers and nucleophagy, a mechanism by which cancer cells respond to nuclear stress. Nucleophagy, a selective form of autophagy, is an intracellular catabolic process involved in the degradation of nuclear material. A mechanistic understanding of nucleophagy remains limited due to a lack of chemical or genetic regulators that can modulate the process. I describe a high content drug screen that identifies a panel of drugs that bi-directionally regulate autophagy marker MAP1LC3B nuclear localization in a renal cancer cell line. I investigate the effects of two hit compounds from the screen on the degradation of nuclear envelope protein Lamin B1 under normal and nuclear stress conditions. Novel chemical tools from the screen allow for deeper exploration of the players involved in nucleophagy. Nuclear envelope degradation in cancer cells is often accompanied by DNA damage and chromatin rearrangement, which leads to inflammation in the tumor microenvironment (TME). Though the contribution of immune infiltration on cancer prognosis is widely recognized, a precise characterization of the immune environment across different tumors and tumor states remains incomplete. The recent advent of immunotherapy for pediatric cancers calls for a better understanding of immune cell interactions in the TME. Here, I analyze controlled-access whole transcriptomic and exome sequencing datasets to map the immune landscape of pediatric kidney cancers, specifically Wilms tumors. This analysis is the first precise characterization of the immune environment for pediatric kidney cancers. Investigating the immune landscape may offer predictive insight into pediatric cancer prognosis and immunotherapy response as well as guide future personalized medicine approaches

Construction and Materials Best Practices for Concrete Sidewalks: Phase II - Long-Term Performance and Hot Weather Placement Effects

This report summarizes the investigation of construction practices and materials to develop durable concrete sidewalks which can resist scaling damage caused by exposure to freezing environment and deicer application. Over 16 months, a field study accompanied by laboratory testing was conducted to identify factors that affect the performance and durability of sidewalks. The variables considered for the study are concrete mix design, placement and finishing practices, curing methods, and deicer application. The placement of the sidewalks took place in late July 2021, to investigate the impact of hot weather concreting practices on the performance of sidewalks. Forty-eight sidewalk panels were placed behind Robert Brack Structural Engineering Laboratory at University of Massachusetts Amherst (UMass). During the sidewalk placement, cylinders and rectangular prisms were placed for laboratory testing. Thirty-two rectangular prisms were subjected to same curing method as the corresponding sidewalks for scaling resistance test in laboratory via BNQ NQ 2621-900. The results of this study indicate that mixture design formulation, curing method, de-icing method, and temperature based concreting practices impact the performance of scaling in concrete sidewalks. Recommendations incorporating these variables are presented in this report with accompanying testing standards and procedures

FORMULATION DEVELOPMENT AND EVALUATION OF SUSTAINED RELEASE GASTRORETENTIVE TABLET OF EMTRICITABINE

Objective: The study aims for the design and evaluation of floating tablets of emtricitabine (EMT), post oral administration to sustain the release and enhance gastric residence time (GRT). Methods: EMT is a nucleoside reverse-transcriptase inhibitor for the prevention and treatment of human immunodeficiency virus (HIV) infection. The investigation was considered to formulate a floating tablet of EMT with various agents. The formulation included with various concentrations of hydroxypropyl methylcellulose (HPMC) k4m, ethylcellulose, microcrystalline cellulose, polyvinylpyrrolidone (PVP) by wet granulation method. Various parameters for the prepared formulations were evaluated for weight variation, thickness, hardness, friability, floating lag time (FLT), total floating time (TFT), swelling index, in vitro drug release, and fourier-transform infrared spectroscopy (FTIR) studies. Results: The best formulation F1 exhibited 88.28% release in 24 h duration, with a floating lag time of 7 min and swelling index of 52.1% and drug content was determined to be 98.27%. The release mechanism was determined to be first order with higuchi release kinetics displaying diffusion along with the dissolution of the EMT from the tablet by non fickian mechanism. Conclusion: EMT tablets showed an increased GRT with a sustained release for 24 h thereby allowing a better window for absorption consequently improve the therapeutic effect of the drug