Jornal de Ciência da Computação e Biologia de Sistemas

Plastics are the most widely used synthetic polymers. Due to their non-degradative nature, synthetic polymers have become an environmental eyesore. Biodegradable plastics like Polyhydroxyalkanoates (PHAs) comprise a group of natural biodegradable polyesters that are synthesized by microorganisms. Polyhydroxyalkanoates were firstly discovered in prokaryotes as carbon and energy storage materials. Plastics are utilized in almost every sector. Plastics being xenobiotic are recalcitrant to microbial degradation. Polyhydroxyalkanoates have gained major importance due to their structural diversity and close analogy to plastics. Polyhydroxyalkanoates have promising properties such as high biodegradability in different environments. Polyhydroxyalkanoates can be degraded by many microorganisms using intracellular or extracellular PHA depolymerases. PHA depolymerases are very diverse in sequence and substrate specificity but share a common α/β-hydrolase fold and a catalytic triad, which is also found in other α/β-hydrolases. Polyhydroxyalkanoates, a biodegradable plastic, was produced in microorganisms and was first discovered by Lemoigne in 1925. It has a relatively high melting point and it gets crystallized rapidly. It has high melting temperature (175°C) and relatively high tensile strength (30-35 MPa).

Polyhydroxyalkanoates database is a single repository of genes and its genomic information is responsible for Polyhydroxyalkanoates to synthesize biodegradable plastics. It is based on genomic characterization of intermediates of Polyhydroxyalkanoates (CAB genes, responsible for biodegradable plastic synthesis) metabolic pathway.

With the advent of school shootings across the United States including the murders of seventeen Marjory Stoneman Douglas High school students and teachers; school administrators, faculty, parents, and students have extensive security and safety concerns about individuals entering and exiting school grounds. A biometric technology widely used to authenticate individuals as part of campus security and safety is facial recognition.

Facial recognition overcomes one of the significant drawbacks with biometric systems since it does not require direct contact or proximity to sensors to identify personnel on the school campus. How effective facial recognition systems are in monitoring individuals’ existence on campus in large part depends on student’s cooperation and attitudes supporting this biometric technology. This paper explores the perceptions of high school students towards biometric monitoring using facial recognition with their concerns over privacy and safety.

This study utilizes quantitative methods to investigate how students’ opinions formed in High school about facial recognition based on beliefs about informational privacy and their appraisal of school safety conditions on campus. This study provides guidance into student views and opinions on biometric monitoring that could be present throughout their high school facilities.

The results indicated that aspects of facial recognition provide concern about students’ informational privacythat includes the operations, administration, and management of a biometric monitoring system by the school’s faculty and staff. The implications on school systems as the result of this study suggests that school policymakers and state representatives need to carefully consider and be aware of students’ perceptions on safety and privacy in consideration of school security using facial recognition.

Machine Learning is the backbone and most essential ingredient for working in the field of Artificial Intelligence as well as working in advance technologies. Some of the models which we already using are RNN, SPPNET. In this research paper we will be getting to know about the New Neural Model called Renshaw Model with its advantages and the web platform which makes the life easier for the user to work and understand the neural networks through machine learning. Usage of Cloud services and as well the usage of API will also be defined. The web platform is developed to tackle the issue of complexity storage, and security issue. This platform is basically running in three different formats and according to the user professionality the execution takes place. Researchers in the field of artificial intelligence can contribute and change the dimensions of the execution by designing and executing their code in swagger.api.