Measuring testability early in the development life cycle especially at design phase is a criterion of crucial

One of the important practical applications of object detection and image classification can be for security enhancement. If dangerous objects e.g. knives can be identified automatically, then a lot of violence can be prevented. For this purpose, various different algorithms and methods are out there that can be used. In this paper, four of them have been investigated to find out which can identify knives from a dataset of images more accurately. Among Bag of Words, HOG-SVM, CNN and pre-trained Alexnet CNN, the deep learning CNN methods are found to give best results, though they consume significantly more resources.

CONTXEXT:-Success of any Software depends on the successful implementation of all of the Requirements. The paper is about successful implementation of requirement engineering (RE) practices in the context of global software development (GSD). OBJECTIVE:Development of requirement implementation model (RIM) which can address the challenges and success factors in successful implementation of the requirements elicited through efficient RE practices. METHOD: -Systematic literature review (SLR) and empirical research study will be used for the aforesaid objective. SLR is based on a planned protocol and is more thorough and systematic than ordinary literature survey. EXPECTED OUTCOMES: -The expected results of this study will be RIM that will help vendor organizations for better elicitation, analysing, specifying, manage and validate requirements.

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Schnakenberg model is known as one of the influential model used in several biological processes. The proposed model is an autocatalytic reaction in nature that arises in various biological models. In such kind of reactions, the rate of reaction speeds up as the reaction proceeds. It is because when a product itself acts as a catalyst. In fact, model endows fractional derivatives that got great advancement in the investigation of mathematical modeling with memory effect. Therefore, in the present paper, the authors develop a scheme for the solution of fractional order Schnakenberg model. The proposed model describes an auto chemical reaction with possible oscillatory behavior which may have several applications in biological and biochemical processes. In this work, the authors generalized the concept of integer order Schnakenberg model to fractional order Schnakenberg model. We provided the approximate solution for the underlying generalized nonlinear Schnakenberg model in the sense of Caputo differential operator via Laplace Adomian decomposition method (LADM). Furthermore, we established the general scheme for the considered model in the form of infinite series by the aforementioned technique. The consequent results obtained by the proposed technique ensure that LADM is an effective and accurate techniques to handle nonlinear partial differential equations as compared to the other available numerical techniques. Finally, the obtained numerical solution is visualized graphically by MATLAB to describe the dynamics of desired solution.

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