Analysis of the Phytochemical Content of Jatropha gossypifolia L.

The use of plants to cure diseases is an age-old practice. The medicinal value of plants lies in chemical substances that produce physiological actions on the human body. Medicinal plants have traditionally occupied an important position in the health area of rural, urban and tribal India. The most important plant of ‘Eurphorbiaceae’ family i.e. one of the largest families of angiosperm is ‘Jatropha gossypifolia’. Commonly it is known as ‘bellyache bush’. It’s majorly found in parts of Africa and America. Its leaves are predominantely used for antihypertensive, anti-inflammatory, antimicrobial, antianemic, antidiabetic, and antihemorrhagic. In the recent research work, the leaves of J. gossypifolia L. were used in various solvents such as Petroleum ether, Chloroform, Acetone, Alcohol and Water. The results confirmed the presence of saponin, tannin, flavonoid, organic acid, glycosides, diterpene, alkaloids, steroids, xanthoprotein, and starch. The overview of the study showed the presence of various secondary metabolites with medicinal value. Key words : Phytochemical, Euphorbiaceae, Jatropha gossipifolia, Saponin, Flavonoi

Machine Learning Algorithms for Heart Disease Prediction

Cardiovascular disease, otherwise known as heart disease, encompasses many diseases that affect the heart. Heart disease prediction is among the most complicated tasks in medical field. In the modern age, about one person dies every minute as a result of heart disease. In addition to many factors that contribute to heart disease, it's necessary at this point in time to acquire accurate, reliable, and sensible approaches to make an early diagnosis so that the disease may be managed appropriately. Due to the complexity of finding out the heart condition, the prediction process must be automated to avoid risks related to it and to alert the patient at an early stage. In the healthcare domain, data mining is commonly used to analyze huge, complex medical data and predict heart disease. Researchers apply a variety of data mining and machine learning approaches to analyse huge complex medical data and predict heart disease. In this study, various heart disease attribute are presented, and model is developed on the basis of supervised learning algorithm as K-nearest neighbor, Decision Tree, Random Forest, Logistic Regression, SVM, Light GBM and Naïve bayes. This Paper makes use of heart condition dataset available in Kaggle repository. The purpose of this study is to anticipate heart disease risk in patients. The results show that K-nearest neighbor provides the most accurate result

Design and testing of a real-time audio-quality feedback system for weather broadcasts and a framework for a weather broadcast transmission technology switch

Forecasting weather and forewarning the public with weather alerts help save lives and property immensely. Audio alert transmissions for weather radio continue to be the most dependable of the multiple techniques used for alerting the public about extreme weather conditions because they are not prone to local infrastructure failure. For a dependable working of this weather alert mechanism, it is important that the weather radio reception should have good clarity of audio. To keep a check on the quality of audio reception, the Mean Opinion Score (MOS) method could be used. It has traditionally been used in telephony quality analysis for decades. However, in case of weather radio, there is no dedicated listener 24/7. The MOS method involves a listener using a scoring system for reporting audio quality. A good MOS method analysis requires an objective skilled listener. Without listening skills and listener training the MOS scoring could be skewed and of little use. If the listener experiences poor audio quality or loss of audio detected at the receive end, steps could be taken to mitigate the situation. Our paper focuses on the design and testing of one such audio-quality forensics system (AQFS) that uses measurements of network, radio and equipment parameters to monitor audio quality. Transmitter stations today have multiple connectivity options and using AQFS as a monitoring system could alert the transmission operators to switch to alternate technology during failures. We have added control features to the AQFS to perform this switching automatically that we have also tested. In this paper, we discuss the design of our system, report our findings and test results.Journal ArticlePre-printPermission granted to the University of West Florida to display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder

Test bed development for s security engineered SCADA laboratory

Supervisory Control and Data Acquisition (SCADA) systems and Industrial Control Systems (ICS) are critical for infrastructure operations, production processes, automation systems, and other automated control systems. SCADA systems are vulnerable to cyber physical attacks from many vectors. The attack surface varies widely. The problem is complicated by the inherent focus on performance, reliability, and safety rather than cybersecurity. The Secure SCADA Framework establishes a security engineered approach evolving SCADA and ICS systems towards a more cybersecure posture. The encapsulating and integrating concepts of the Secure SCADA Framework require development and analysis of implementations achieving the eight framework goals. This work provides a solution for research, design, development, and evaluation of components of a Secure SCADA System. A Security Engineered SCADA Laboratory requires a test bed with which engineering and science designs can be developed. This paper presents a test bed which can model and collect data on simulated attacks, analyze data to evaluate performance, and provide the foundations for a Security Engineered SCADA Laboratory.Conference PaperPublishedPermission granted to the University of West Florida to display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder

Quality Analysis of Streaming Audio over Mobile Networks

This paper utilizes open source software to analyze the quality of audio streamed over mobile cellular networks. Industry conventions have been developed to assess audio quality such as the Mean Opinion Score or MOS scale described in the International Telecommunications Union ITU P.800.1 document. The MOS scale is a subjective assessment based on the listener’s experience. To eliminate the use of a trained audio listener we automate an estimated MOS calculation by measuring the packet loss, average latency and jitter over the network transport path. The network under test is a pilot network to replace the dedicated analog circuit from the broadcast center to a radio transmitter. We intend to automate the logging of an objective quality assessment using MOS, cellular router and decoder measurements with confirmation using automatically generated visual representations of sample audio received. These visual representations will aid in manual confirmation of poor MOS scores with audio samples available for more in-depth review.Final article publishedJournal ArticlePermission granted to the University of West Florida to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder

Applying a Verified Trusted Computing Base to Cyber Protect a Vulnerable Traffic Control Cyber-Physical System

Traffic control systems were developed with operational performance, reliability, and safety in mind. Traffic control systems were designed well before the heavy integration of advanced communications including radio frequency (RF), the Internet and cellular transmissions. These technologies were integrated to provide more control and enable the traffic systems to become adaptive to real-time traffic flow and environmental conditions. These advances increase the opportunity for attackers to affect traffic system operations, sometimes creating a congestion which essentially halts traffic. The Secure SCADA Framework presents eight objectives which would increase the cyber resilience of an existing vulnerable cyber physical system, such as a traffic control system [1]. This approach retains the current operational performance, reliability, and safety. The concept of using a Trusted Computing Base (TCB) in a cyber-physical system is one goal of the eight presented for the Secure SCADA Framework. The SCADA TCB (STCB) project designs, develops, and verifies a core set of hardware, software, and firmware which operate in conjunction to establish a high level of security protecting a traffic control system. This research defines the requirements of a traffic control system, establishes a security policy, develops a trusted computing base, identifies and designs attacks on the system, and meets the development life-cycle requirements to proceed with implementation, verification, and testing.Conference PaperOtherPermission granted to the University of West Florida to digitize and/or display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder