Spam e-mail has a significant negative impact on individuals and organizations, and is considered as a serious waste of resources, time and efforts. Spam detection is a complex and challenging task to solve. In litera...Spam e-mail has a significant negative impact on individuals and organizations, and is considered as a serious waste of resources, time and efforts. Spam detection is a complex and challenging task to solve. In literature, researchers and practitioners proposed numerous approaches for automatic e-mail spam detection. Learning-based filtering is one of the important approaches used for spam detection where a filter needs to be trained to extract the knowledge that can be used to detect the spam. In this context, Artificial Neural Networks is a widely used machine learning based filter. In this paper, we propose the use of a common type of Feedforward Neural Network called Multi-Layer Perceptron (MLP) for the purpose of e-mail spam identification, where the weights of this network model are found using a new nature-inspired metaheuristic algorithm called Biogeography Based Optimization (BBO). Experiments and results based on two different spam datasets show that the developed MLP model trained by BBO gets high generalization performance compared to other optimization methods used in the literature for e-mail spam detection.展开更多
When correcting a fault, adding a new concept or feature, or adapting a system to conform to a new platform, software engineers must first find the relevant parts of the code that correspond to a particular change. Th...When correcting a fault, adding a new concept or feature, or adapting a system to conform to a new platform, software engineers must first find the relevant parts of the code that correspond to a particular change. This is termed as concept or feature location process. Several techniques have been introduced which automate some or all of the process of concept location. Those techniques rely heavily on code comprehension as it is considered a prerequisite when attempting to maintain any software system. It provides a comprehensive overview of large body work which is beneficial to researchers and practitioners. This paper presents an overview of code comprehension categorization and consequence. A systematic literature survey of concept location enhancement techniques is also presented. Moreover, the paper presents an overview of the role of concept location in program comprehension and maintenance and discusses information retrieval techniques to advance concept location.展开更多
In this paper, we present a comparative study between informed and predictive prefetching mechanisms that were presented to leverage the performance gap between I/O storage systems and CPU. In particular, we will focu...In this paper, we present a comparative study between informed and predictive prefetching mechanisms that were presented to leverage the performance gap between I/O storage systems and CPU. In particular, we will focus on transparent informed prefetching (TIP) and predictive prefetching using probability graph approach (PG). Our main objective is to show the main features, motivations, and implementation overview of each mechanism. We also conducted a performance evaluation discussion that shows a comparison between both mechanisms performance when using different cache size values.展开更多
文摘Spam e-mail has a significant negative impact on individuals and organizations, and is considered as a serious waste of resources, time and efforts. Spam detection is a complex and challenging task to solve. In literature, researchers and practitioners proposed numerous approaches for automatic e-mail spam detection. Learning-based filtering is one of the important approaches used for spam detection where a filter needs to be trained to extract the knowledge that can be used to detect the spam. In this context, Artificial Neural Networks is a widely used machine learning based filter. In this paper, we propose the use of a common type of Feedforward Neural Network called Multi-Layer Perceptron (MLP) for the purpose of e-mail spam identification, where the weights of this network model are found using a new nature-inspired metaheuristic algorithm called Biogeography Based Optimization (BBO). Experiments and results based on two different spam datasets show that the developed MLP model trained by BBO gets high generalization performance compared to other optimization methods used in the literature for e-mail spam detection.
文摘When correcting a fault, adding a new concept or feature, or adapting a system to conform to a new platform, software engineers must first find the relevant parts of the code that correspond to a particular change. This is termed as concept or feature location process. Several techniques have been introduced which automate some or all of the process of concept location. Those techniques rely heavily on code comprehension as it is considered a prerequisite when attempting to maintain any software system. It provides a comprehensive overview of large body work which is beneficial to researchers and practitioners. This paper presents an overview of code comprehension categorization and consequence. A systematic literature survey of concept location enhancement techniques is also presented. Moreover, the paper presents an overview of the role of concept location in program comprehension and maintenance and discusses information retrieval techniques to advance concept location.
文摘In this paper, we present a comparative study between informed and predictive prefetching mechanisms that were presented to leverage the performance gap between I/O storage systems and CPU. In particular, we will focus on transparent informed prefetching (TIP) and predictive prefetching using probability graph approach (PG). Our main objective is to show the main features, motivations, and implementation overview of each mechanism. We also conducted a performance evaluation discussion that shows a comparison between both mechanisms performance when using different cache size values.
