Explore the vast range of titles available.

This study aims to understand the impulse buying experience, which allows us to identify the factors that contribute to the construction of a gratifying shopping experience that subsequently triggers impulse buying, the consequences that result from this experience and to propose a conceptual model explaining the content of the impulse buying experience in a longitudinal perspective. By using a qualitative approach, this study considers the opinion of 21 buyers. The results show that there are many factors that contribute to impulse buying such as atmospheric factors, motivations and emotions. The results show also the consequences and their effect on future behavioral intentions.

In recent times, malware visualization has become very popular for malware classification in cybersecurity. Existing malware features can easily identify known malware that have been already detected, but they cannot identify new and infrequent malwares accurately. Moreover, deep learning algorithms show their power in term of malware classification topic. However, we found the use of imbalanced data; the Malimg database which contains 25 malware families don’t have same or near number of images per class. To address these issues, this paper proposes an effective malware classifier, based on costsensitive deep learning. When performing classification on imbalanced data, some classes get less accuracy than others. Cost-sensitive is meant to solve this issue, however in our case of 25 classes, classical cost-sensitive weights wasn’t effective is giving equal attention to all classes. The proposed approach improves the performance of malware classification, and we demonstrate this improvement using two Convolutional Neural Network models using functional and subclassing programming techniques, based on loss, accuracy, recall and precision.

In this research paper, we investigate the controllability in the α-norm of a coupled system of integrodifferential equations with state-dependent nonlocal conditions in generalized Banach spaces. We establish sufficient conditions for the system’s controllability using resolvent operator theory introduced by Grimmer, fractional power operators, and fixed-point theorems associated with generalized measures of noncompactness for condensing operators in vector Banach spaces. Finally, we present an application example to validate the proposed methodology in this research.