EVALUATION OF CAPTURING ARCHITECTURALLY SIGNIFICANT REQUIREMENTS METHODS

Every software development organization strives for customer satisfaction. It is universally accepted that the success of software development lies in the clear understanding of the client requirements. During requirement elicitation and analysis stage, the system analyst identifies the functional and non-functional requirements from the customer. Security, usability, reliability, performance, scalability and supportability are the significant quality attributes of a software system. These quality attributes are also referred as non-functional requirements. Only a few functional and quality attributes requirement help to identify and shape the software architecture. A software system's architecture is the set of prime design decisions made about the system. If the requirement influences the architectural design decision then, it is referred as Architecturally Significant Requirement (ASR). Identifying and specifying all the possible ASR are important tasks in the requirement elicitation and analysis stage.In this research, general problems that are faced while capturing and specifying ASR in requirement elicitation and analysis is studied. Among the different requirement elicitation techniques, use case diagram has been identified and enhanced to solve the problem of capturing and specifying ASR during the requirement elicitation and analysis phase Â&nbsp

BLOCKCHAIN TECHNOLOGY FOR DETECTING FRAUD IN PHARMACEUTICAL SUPPLY CHAIN MANAGEMENT

Aim: This paper mainly focused on proposing a new pharmaceutical supply chain management system based on block chain technology.    Results: A seven steps pharmaceutical supply chain management is designed based on blockchain technology. The patients are encouraged to access the technology for finding genuinity of the medicine and to reduce fraud detection.    Conclusion: Blockchain is used to make the system more efficient and effective and designing such genuine system with all necessary parameters can boost patient confidence during medication.  Keywords: Pharmaceutical supply chain management, blockchain technology, patients, medicin

DETECTION OF WHALES USING DEEP LEARNING METHODS AND NEURAL NETWORKS

Deep learning methods are a great machine learning technique which is mostly used in artificial neural networks for pattern recognition. This project is to identify the Whales from under water Bioacoustics network using an efficient algorithm and data model, so that location of the whales can be send to the Ships travelling in the same region in order to avoid collision with the whale or disturbing their natural habitat as much as possible. This paper shows application of unsupervised machine learning techniques with help of deep belief network and manual feature extraction model for better results

Health System for Exercise Rehabilitation Detection Retina Images and IoT Blockchain

Smart Healthcare which is based on deep learning is becoming increasingly popular because of its practical applications and has grown popular after its incorporation with IoT. Degenerative eye disease is the main factor of blindness in people of working age. Asian nations with large populations, like India and China, are on the edge of a diabetes epidemic. In terms of medical screening and diagnosis, a large number of diabetes patients posed a huge problem for skilled clinicians. The idea is to employ deep learning algorithms to detect blind spots in the eye and estimate the severity of the stage. We present an optimum approach for detecting blindness in retinal images based on recently released pre-trained EfficientNet models, as well as a comparative assessment of many innovative neural network models, in this study. On a benchmark dataset of retina images obtained by diagnostic imaging at various imaging phases, our EfficientNet-B5-based model assessment performs better than CNN and ResNet50 models

Formulation and evaluation of bi-layer floating tablets of ziprasidone HCl and trihexyphenidyl HCl

The purpose of this research study was to establish ziprasidone HCl NR 40 mg and trihexyphenidyl HCl SR 4mg in the form of bi-layer sustained release floating tablets. The tablets were prepared using sodium HPMC K4M / HPMC K15M as bio-adhesive polymers and sodium bicarbonate acting as a floating layer. Tablets were evaluated based on different parameters such as thickness, hardness, friability, weight variation, in vitro dissolution studies, content of active ingredient and IR studies. The physico-chemical properties of the finished product complied with the specifications. In vitro release from the formulation was studied as per the USP XXIII dissolution procedure. The formulations gave a normal release effect followed by sustained release for 12 h which indicates bimodal release of ziprasidone HCl from the matrix tablets. The data obtained was fitted to Peppas models. Analysis of n values of the Korsmeyer equation indicated that the drug release involved non-diffusional mechanisms. By the present study, it can be concluded that bi-layer tablets of ziprasidone HCl and trihexyphenidyl HCl will be a useful strategy for extending the metabolism and improving the bioavailability of Ziprasidone HCl and Trihexyphenidyl HCl.<br>O propósito deste trabalho foi preparar ziprasidona. HCl NR 40 mg e triexifenidila.HCl SR 4 mg na forma de comprimidos efervescentes bicamada de liberação controlada. Os comprimidos foram preparados utilizando HPMC K4M / HPMC K15M sódico como polímero bioadesivo e bicarbonato como camada efervescente. Os comprimidos foram avaliados quanto a diferentes parâmetros, como espessura, dureza, friabilidade, variação de peso, dissolução in vitro, conteúdo do ingrediente ativo e estudos de IV. As propriedades físico-químicas dos produtos finais cumprem as especificações. A liberação in vitro da formulação foi estudada de acordo com o procedimento de dissolução da USP XXIII. As formulações resultaram em liberação normal, seguida por liberação controlada por 12 h, o que indica a liberação bimodal de cloridrato de ziprasidona dos comprimidos matriz. Os dados obtidos se adequaram aos modelos de Peppas. A análise de valores de n da equação de Korsmeyer indicou que a liberação do fármaco envolveu mecanismos não difusionais. Por este estudo, pode-se concluir que os comprimidos bicamada de ziprasidona.HCl e de triexifenidila.HCl serão um bom caminho para estender o metabolismo e para melhorar a biodisponibilidade de ziprasidona.HCl e de triexifenidila.HCl