Reactive Magnetron Sputter Deposition of Titanium Oxynitride TiNxOy Coatings: Influence of Substrate Bias Voltage on the Structure,Composition, and Properties

Protection of Metals and Physical Chemistry of Surfaces - TiOxNy films were grown onto 316L stainless steel substrate using radiofrequency (rf) magnetron sputtering from a pure titanium nitride...     

Analysis of malware propagation behavior in Social Internet of Things

Social Internet of Things (SIoT) is an evolution of the Internet of Things, where objects interact socially with each other in the sense that they can independently establish new relationships, offer, or discover services, in order to accomplish their tasks with minimum involvement of the user. This additional convenience comes at the expense of higher risk of speeding up malware propagation through the dynamically created relationships. Because of the undesirable effects of malware (eg, disruption of device operation), it is essential to understand their spreading behavior in order to minimize their negative impacts. In this paper, we analyze malware propagation behavior in SIoT and investigate different parameters that influence spreading of malware. Toward that end, a simulator has been developed to simulate the spreading process of malware in SIoT. Many propagation scenarios were analyzed using the proposed simulator. Simulation results show that adding more relationships in the SIoT or increasing the number of owned objects per user has increased malware spreading rate. For example, the time to infect all objects is faster by 45% when objects communicate through four relationships compared with the case when objects communicate through only two relationships in SIoT. We also investigated ways to restrict the malware spreading. Results show that preventing objects from establishing dynamic social relationship slows down the infection by 40% compared with the next best scenario (ie, blocking co‐location relationships), which means more time for vendors to patch up their products.     

NapWell: An EOG-based Sleep Assistant Exploring the Effects of Virtual Reality on Sleep Onset

Virtual Reality - We present NapWell, a Sleep Assistant using virtual reality (VR) to decrease sleep onset latency by providing a realistic imagery distraction prior to sleep onset. Our proposed...     

Mechanically Agitated Fluidized Bed Drying of Cohesive Particles at Low Air Velocity

The drying of micrometer-sized, cohesive particles belonging to the group C type materials according to Geldart's classification is always challenging. An agitated fluid bed dryer (AFBD) of pilot-scale capacity was designed to study the effect of the type of agitator and its speed, gas velocity, and inlet temperature and feed loading on the hydrodynamic performance of the AFBD. Key hydrodynamic parameters such as pressure drop have a profound influence on determining the fluidization characteristics. The pressure drop across the AFBD system was expressed in terms of flow coefficient, ξ, which can be conveniently used as a design parameter. The choice of agitator has an even greater influence on the drying kinetics and the results have been summarized, paving the way for a more efficient spiral agitator of the helical ribbon type.