Two measurement techniques for estimating the /spl alpha/ parameter of a laser, the frequency f/sub c/ for which the adiabatic and transient chirp of a laser have the same magnitude, and the dispersion coefficient D of an optical fiber are compared. The techniques rely on either a single measurement of the transfer function of a dispersive optical fiber using direct modulation of the laser, or two measurements of the fiber transfer function using external and direct modulation of the laser. Compared to the two measurement technique, the single measurement technique yields a smaller estimate of /spl alpha/ and a nearly identical estimate of f/sub c/, and can produce an unreliable estimate of D unless the frequency span in the parameter extraction procedure is sufficiently large.

Smart and connected health care is of specific significance in the spectrum of applications enabled the Internet of Things (IoT). Networked sensors, either embedded inside our living system or worn on the body, enable to gather rich information regarding our physical and mental health. In specific, the accessibility of information at previously unimagined scales and spatial longitudes combined with the new generation of smart processing algorithms can expedite an advancement in the medical field, from the current post-facto diagnosis and treatment of reactive framework, to an early-stage proactive paradigm for disease prognosis combined with prevention and cure as well as overall administration of well-being rather than ailment. This paper sheds some light on the current methods accessible in the Internet of Things (IoT) domain for healthcare applications. The proposed objective is to design and create a healthcare system centered on Mobile-IoT by collecting patient information from different sensors and alerting both the guardian and the doctor by sending emails and SMS in a timely manner. It remotely monitors the physiological parameters of the patient and diagnoses the illnesses swiftly.

This paper presents an innovative design and accurate approach to the measurement of flow rate for moderate flow applications. It also deduces linear relationship between flow rate and the change in resistance of the bend sensor used in the setup. The sensor apparatus is very simple to calibrate and install which is a fixed beam cantilever system with one moving end which would give a digital output. The displacement values of free end of the sensor are analysed using ANSYS Finite Element Analysis software.

When it comes to the development of 4G and 5G technologies, long-range IoT or machine-to-machine (M2M) communication can be achieved with the help of cellular infrastructure. In non-standalone (NSA) 5G infrastructure, cellular-IoT (C-IoT) devices are attached and authenticated by a 4G core network even if it is connected to a 5G base station. In an NSA-based 5G network, the presence of dual connectivity sometimes raises interoperability and authentication issues due to technological differences between LTE and 5G. An attacker explores these technological differences, introduces the threats, and performs various types of attacks like session hijacking at the interfaces and Man-in-the-Middle (MITM) attacks. With the introduction of these attacks, the attackers exploit the network resources and pinch out various critical information sources. To resolve this issue, the NSA-based C-IoT network must incorporate robust and seamless authentication and authorization mechanisms. This article presents the ML-AKA protocol that is used to enhance interoperability and trust between 4G and 5G networks by using a uniform key-sharing (UKS) mechanism. The proposed ML-AKA protocol is analyzed with the help of the AVISPA tool and validated with the use of Proverif. Further, the proposed protocol is compared with other existing protocols like EPS-AKA and UAKA-D2D, and the outcome shows that the proposed protocol significantly reduces the chances of MITM, DDOS and Spoofing attacks during the interoperability in the NSA-C-IoT network.