Performance Evaluation of Deep Learning Autoencoder in Single and Multi-Carrier Systems

An entire system of Single Carrier Communication and Orthogonal Frequency Division Multiplexing is modelled using an autoencoder. The model employs Deep Neural Networks (DNNs) as the transmitter and receiver, responsible for tasks such as encoding, modulation, demodulation, and decoding. The effectiveness of this approach is demonstrated by its ability to outperform traditional communication systems in real-world scenarios that involve channel and interference effects, as measured by the Block Error Rate. AI-enabled wireless systems can overcome limitations of traditional communication systems by learning from wireless spectrum data and optimizing performance for new wireless applications. The aim of this paper is to examine how autoencoder-based deep learning can enhance the performance of a communication system that employs Single Carrier and OFDM. The architecture effectively addresses channel impairments and improves overall performance. The simulation results suggest that even when the autoencoder's channel layer is affected by impairments, autoencoders still outperform traditional communication systems in terms of BLER performance

Design of Turbo Trellis Coding Modulation Scheme of Rate 4/9 for Rician Fading Channel

When the fading channels are encountered during data communication, errors are likely to occur at the receiving end due to multipath propagation. Researchers have been consistently striving to develop Error Correction Schemes that can effectively handle these errors and ensure error-free data reception at the receiver end. Of particular interest are the Forward Error Correction Schemes that can be implemented at the transmitter end itself. However, the implementation of error correction coding through these schemes incurs additional costs in terms of bandwidth expansion, as extra bits need to be added to facilitate error correction. Fortunately, there exists one coding scheme called Trellis Coded Modulation (TCM), which addresses this issue. TCM selects a modulation scheme based on the rate of the convolutional coding scheme. However, this coding technique has limitations in correcting the number of errors, leading to the development of Turbo Coding. This scheme utilizes two coders at the transmitter, arranged in either serial or parallel configuration, and a suitable decoder at the receiver. A design of Turbo Coding scheme has been presented in this paper, that employs convolutional coders having rate 2/3, in a serially concatenated configuration, providing an effective rate of 4/9. This turbo coding scheme is then applied to TCM scheme in order to preserve the bandwidth. Therefore, if using the convolutional coding scheme of rate 2/3, the modulation scheme is 8-QAM and in order to preserve bandwidth after coding, using the Turbo coding scheme of rate 4/9, then the modulation scheme will be 512-QAM. The simulations have been conducted in MATLAB and the error correcting capabilities of the designed scheme in comparison with convolutional coding scheme using the constituent convolutional encoder have also been compared. It has been observed that in the Rician fading channel conditions, the Turbo Trellis Coding Modulation Scheme provides approximately 5 dB gain compared to the convolutional coding scheme

Implementation of Intelligent Smart Heart Health Monitoring System using IOT

There are a lot of severe diseases that are associated with humans, but one of them is cardiac arrest, which, in general terms, we call a heart attack. The already existing heart rate monitoring systems are not mobile, are expensive, and take a little longer to give out the results. So, in this work, we will go for a system called Heart Rate Monitoring system using an ECG sensor and a Raspberry Pi, which actually represents the acquisition and interpretation of a human heart’s data collected with the help of sensors, anywhere and everywhere on the earth, through IOT. We generally consider heart rate while noting the status of the heart, but the oxygen level and body temperature also play a major role in determining the exact heart status. So, the hardware required to implement this heart rate monitoring model consists of different health sensors and a Raspberry Pi configured in a way to communicate with the guardian and the respective doctors over the Internet through an available smart mobile phone. In this work, the sensors configured with the hardware collect the required information about the patient’s health, which includes parameters such as the patient’s heart rate, body temperature, and SPo2 levels. Then, using the collected information from the sensors, the patient’s heart activity is actively observed. Thus, the patient himself or herself can easily identify his or her heart condition with the help of collected data anywhere on the earth through the internet. An alert indicating that their heart status is not good is displayed to the caretakers on the mobile, which shows a message called "abnormal condition to the patient" given the condition that the collected sensors’ values are beyond the threshold information through the GSM module, and also the GPS location of the patient will be sent to the caretakers as well as to the doctors

A STUDY OF PRESCRIPTION AUDIT IN OUTPATIENT DEPARTMENT OF A TERTIARY CARE TEACHING HOSPITAL IN INDIA: AN OBSERVATIONAL STUDY

Background: The quality of life can be improved by enhancing the standards of the medical treatment at all levels of the healthcare delivery system. A medical audit oversees the observance of these standards.  Prescription Audit offers the most comprehensive overview of performance, detailing parameter as per the check list of prescription audit. Aim: To monitor, evaluate and suggest modifications (if necessary) in the prescribing practices of medical practitioners. Methods: The observational study was conducted over a period of 6 months and data were collected from 1093 prescriptions collected from outpatient department of a tertiary care teaching hospital in India. Results: Total 1093 prescriptions were evaluated for the Audit, out of which 56.4% were Male & 43.6% were Female cases. Majority of the study subjects belonged to the age group of 40-59 years (32.4%). During the study mainly twelve parameter were assessed according to the checklist provided by the Hospital with total 1093 samples of prescription audit, only 2.2 % (280) cases had the non –compliance, 64.5% (8464) cases had compliance and 33.3% (4372) not applicable to this parameters. Conclusion: The results obtained from the study shows the prevailing prescribing habits at our institution. Many of the prescribing trends from this study are a cause of concern and need attention. This study reveals that the auditing of prescription in terms of rationality, it remains poor. The value of such audits in generating and testing hypotheses on inappropriate prescribing will definitely create an intervention to improve prescribing habits and ultimately patient care will be improved. Keywords: Prescription Auditing, Outpatient department, Tertiary care teaching hospital, Compliance & non-compliance. Â

A study on issues and challenges of information technology act 2000 in India

Purpose: This article focused on the jurisprudence of cyber law, how cybercrime is categorized in relation to regular crime, and the jurisdictional problems it raises. In India, the Information and Technology Act of 2000 primarily governs cybercrime. The Information and Technology Act of 2000's implementation problems and difficulties are also identified in this study. Research Methodology: The study's objectives were to understand the many cybercrimes that occur in India as well as the problems and obstacles related to them. The study is based on secondary data, and it analyses and interprets data from the last three years. The primary information was gathered through press publications, crime bureaus of investigation, etc. Results: In the past three years, the nation has reported over 16 lakh cybercrime incidences, and more than 32,000 FIRs have been filed in India since 2020. 8,829 instances were reported in Uttar Pradesh in 2021, down from 11,097 in 2020. Karnataka saw a decrease in instances from 10,741 in 2020 to 8,136 in 2021. 10,730 cybercrimes against women were reported in India in 2021. Out of this, the majority of instances were related to disseminating obscene sexual content or cyberpornography. 1,896 similar instances were reported in 2021. Limitations: This study is based on secondary information only. The data was collected from only secondary sources and from the last three years only Contribution:  The policymakers, educators, and the general public will benefit from this study's explanation of cybercrimes in India. Additionally, it draws attention to the difficulties with the 2010 Indian Information Act