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.
Scheduling an application in data grid was significantly complex and very challenging because of its heterogeneous in nature of the grid system. When the Divisible Load Theory (DLT) model had emerged as a powerful model for modeling data-intensive grid problem, Task Data Present (TDP) model was proposed based on it. This study presented a new Adaptive TDP (ATDP) for scheduling the intensive grid applications. New closed form solution for obtaining the load allocation was derived while computation speeds and communication links are heterogeneous. Experimental results showed that the proposed model can balance the load efficiently
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