In this paper we present a study of deep learning models for single image super-resolution (SISR), through the some latest methods used in neural networks super-resolution, exploring many and proposed. Moreover, presents global complete technical benchmark state-of-the-art machine algorithms based on reference metrics (PSNR SSIM) field visualization perception. This involved 53 different tested 7 datasets established as vision domain (Set5, Set14, BSD100, Urban100, DIV2K, Manga109, DIV8K)....

Design and development of context-aware Information Systems (ISs) is particularly complex, owing to the increasing dependency people on computing support for making simple decisions or performing their daily tasks. Thus, need designing more attractive, adaptable proactive systems persistent. In this paper, we present a state art approaches that are compared classified. Furthermore, work tries IS by proposing context model defining modeling requirements at suitable level abstraction...

In mobile computing developers will need to develop applications that interact with the end user. Context-aware notify or ask users what they want based on have sensed a user profile. Event-driven detects conditions of interest and notifies them accordingly. this paper we discuss importance challenges in designing event-driven through comparison between some metamodels propose an event metamodel instantiate productive comprehensible models.

Wireless sensor networks (WSNs) are extensively used in several fields, especially for monitoring and gathering physical information. The nodes could be static or mobile depending on the application requirements. Mobility arises major challenges routing. It radically changes routing path, while WSNs peculiarities make reuse of designed protocols difficult other types networks. In this paper, we present a Context-Aware protocol based particle swarm optimization (PSO) random waypoint (RWP)...

Wireless sensor networks (WSN) are mostly utilized in many applications. Indeed, WSN is composed of sensors to evaluate some physical phenomena. However, the information brought by still missed if we don't know exact location event. Several localization algorithms have been proposed order locate nodes WSN. The categorized into range-based and range-free techniques. techniques use either distance or time calculate coordinates unknown nodes. Nevertheless, those kinds need additional...

This paper introduces a deep learning-based approach (DLBA) tailored for fault detection and condition monitoring in industrial machinery.The presented DLBA architecture is assessed utilizing dataset derived from CNC milling machine, as part of the University Michigan's System-level Manufacturing Automation Research Testbed (SMART).The results underscore substantial efficacy LSTM model, evidenced by precision 94% an F1 score 95%.These findings serve robust foundation identification machining...

Recently, the development of wireless sensor networks (WSNs) is spreading rapidly. WSNs are highly distributed self-organized systems which comprise a large number resource constrained nodes. Developers face many challenges from communication, memory, limited energy… Also, mobility has become major concern for WSN researchers. Indeed, Mobile (MWSN) consist mobile nodes that can move on their own and also interact with physical environment. Developing applications MWSN complicated process...