A Comparative and Analytical Review of Iot-Enabled Smart Accidental Management Systems

One of the most important issues that emerging nations are addressing is road accidents. It is important to develop smart accidental management systems with low cost and efforts to prevent accidents and causalities. The amalgamation of Intelligent Transportation Systems (ITS) and Information and Communications Technology (ICT) is expected to dramatically change how people experience driving by enabling cutting-edge traffic monitoring and incident detection strategies. This analysis focuses on various components of SAMS, such as sensor networks, communication protocols, data processing techniques, and decision-making algorithms. It examines how these components work together to create a connected infrastructure capable of detecting and responding to accidents promptly. The review highlights the role of data analytics in enhancing accident prediction and prevention. By processing and analyzing enormous real-time data from cameras, sensors, and other sources, IoT-driven SAMS can identify patterns and anomalies, allowing for proactive measures to avoid accidents in various settings, including transportation, industries, and public spaces

The Scattering amplitude for Rationally extended shape invariant Eckart potentials

We consider the rationally extended exactly solvable Eckart potentials which exhibit extended shape invariance property. These potentials are isospectral to the conventional Eckart potential. The scattering amplitude for these rationally ex- tended potentials is calculated analytically for the generalized mth (m = 1, 2, 3, ...) case by considering the asymptotic behavior of the scattering state wave functions which are written in terms of some new polynomials related to the Jacobi polyno- mials. As expected, in the m = 0 limit, this scattering amplitude goes over to the scattering amplitude for the conventional Eckart potential.Comment: 8 pages. Latex, No fi

TRADITIONAL HERBAL REMEDIES FOR HEALTH CARE: A REVIEW

The global health scenario is facing new challenges due to global warming and economic down-turn that are now threatening health development. It is therefore crucial that all systems of medicine whether conventional or traditional are beneficial and not deleterious to the health and well-being of the people must play their respective roles in promoting health, in preventing disease, in curing the sick, and in rehabilitating the infirm. It is through these concerted efforts that tangible gains can be achieved. Herbal medicines constitute the main component of traditional medicine, which have been used since thousands of years. They have made significant contribution to human health through their health pro-motive, curative and rehabilitative properties and in the prevention of illnesses. Indeed, many herbal remedies used traditionally have become modern medicines through drug development. Long tradition use of many herbal remedies and experiences passed on from generation to generation has brought about reliance by the people on herbal medicines. It is envisaged that this publication will be instrumental in revitalizing primary health care in empowering community participation in self-care, in promoting the application of appropriate technology that is socially and culturally acceptable to the people, in making the health system more people-centered, and in improving equitable access to national health systems

Malware Detection and Analysis Tools

The huge amounts of data and information that need to be analyzed for possible malicious intent are one ofthe big and significant challenges that the Web faces today. Malicious software, also referred to as malware developed by attackers, is polymorphic and metamorphic in nature which can modify the code as it spreads.In addition, the diversity and volume of their variants severely undermine the effectiveness of traditional defenses that typically use signature-based techniques and are unable to detect malicious executables previously unknown. Malware family variants share typical patterns of behavior that indicate their origin and purpose. The behavioral trends observed either statically or dynamically can be manipulated by usingmachine learning techniques to identify and classify unknown malware into their established families. Thissurvey paper gives an overview of the malware detection and analysis techniques and tools