In this letter, we present a new ATM scalable multicast algorithm called SRAM that can provide reliable data transfer services. This algorithm employs the RM cell consolidation mechanism for ABR point-to-multipoint connections which resolves the feedback implosion problem without increasing the number of connections according to the number of receivers. We compare the proposed scheme with other...

Multicast (1:N) is now supported by a number of networks and communication protocols. A problem in this context is how to provide fully reliable data transmission to the receiver group (or speciied subgroup) in a heterogeneous environment. To achieve this an algorithm is required which is independent of any underlying network and multicast scheme. In this paper we present such an algorithm whic...

When it comes to COVID-19, access reliable data is vital. It crucial for the scientific community use reported by independent territories worldwide. This study evaluates reliability of pandemic disclosed 182 countries We collected and assessed conformity COVID-19 daily infections, deaths, tests, vaccinations with Benford’s law since beginning coronavirus pandemic. commonly accepted that frequen...

Many emerging applications are based on multimedia group communication. Mul-ticast communication is a transmission mode that is now supported by a variety of local and wide area networks. Many group applications require a full reliable data transfer to all receivers. A problem in this context is how to provide a full reliable data transmission to a large number of receivers while still exploiti...

The somatic growth of individuals governs many aspects a species’ life history and is an important parameter in the assessment populations. Population parameters are typically derived by relating length to their age, with ages commonly estimated from bands formed calcified structures such as vertebrae or dorsal fin spines. However, routinely utilized aging methods may not be reliable for elasmo...

Machine learning (ML) algorithms are nowadays widely adopted in different contexts to perform autonomous decisions and predictions. Due the high volume of data shared recent years, ML more accurate reliable since training testing phases precise. An important concept analyze when defining concerns adversarial machine attacks. These attacks aim create manipulated datasets mislead algorithm decisi...