GR-64 How could IoT assist healthcare system during COVID-19 or future pandemics?

The Internet of Things (IoT), a technology built upon sensors and devices, has shown great applicability among various domains, especially healthcare. This pandemic has critically impacted all parts of society including people, health centers, businesses, authorities, etc. Researchers are attempting to adopt different technologies to mitigate this virus faster and save more lives. Regarding the great benefits that Internet of Things (IoT) has brought into different areas within the healthcare domain, this technology has been performing several main tasks including diagnosing, monitoring, tracing, disinfecting, and vaccinating to combat this virus. Our research is conducted of the possible IoT solutions to mitigate the COVID-19 or even future pandemics. We have demonstrated the applicability of IoT technologies in three main COVID-19 phases including “early diagnosis, quarantine time, and after recovery.” Along with such applications, we also review the proposed IoT applications for the main tasks of IoT, which could be exponentially helpful for fighting against this virus.Advisors(s): Prof. Seyedamin Pouriyeh: supervisor Prof. Reza Meimandi Parizi: second supervisorTopic(s): IoT/Cloud/Networkin

Tribological characterization of laminated hybrid AA1050/TiC/Graphite composite bars

Hybrid composites (HC) refer to a type of material that combines aluminum (Al), titanium carbide (TiC), and graphite (Gr) at the nano level. These HC have shown promise in applications requiring high strength, wear resistance (WR), and tribological performance, such as automotive, aerospace, and industrial sectors. In this study, these HC are made using a combination of Powder metallurgy (PM) and accumulative press bonding (APB) processes have been developed. This is the first time that the wear resistance of a hybrid metal matrix composite fabricated with Gr as a solid lubricant has been done and thid is the novelty of this study. In fact, the presence of TiC nanoparticles (NP) provides improved mechanical properties, such as hardness (Hr), strength, and WR for HC. On the other hand, Gr acts as a solid nano-lubricant (NLU) in HC, reducing friction and WR during sliding contact. The presence of Gr-NP also helps to form a durable Gr-nanolayer on tribo surfaces and further improves the WR of HC. This study used a scanning electron microscope (SEM). The results demonstrated that incorporating TiC- NP reduced the WR rate and promoted NL development at extended sliding distances, creating a durable TiC/Gr HC on the TS. Finally, the improved WR of Al/TiC/Gr-HC can be attributed to the stability of the Gr-NL on the TS

Internet of Things for Current COVID-19 and Future Pandemics: an Exploratory Study

© 2020, Springer Nature Switzerland AG. In recent years, the Internet of Things (IoT) has gained convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems by incorporating technological, economic, and social prospects. It is evolving healthcare systems from conventional to more personalized healthcare systems through which patients can be diagnosed, treated, and monitored more easily. The current global challenge of the pandemic caused by the novel severe respiratory syndrome coronavirus 2 presents the greatest global public health crisis since the pandemic influenza outbreak of 1918. At the time this paper was written, the number of diagnosed COVID-19 cases around the world had reached more than 31 million. Since the pandemic started, there has been a rapid effort in different research communities to exploit a wide variety of technologies to combat this worldwide threat, and IoT technology is one of the pioneers in this area. In the context of COVID-19, IoT-enabled/linked devices/applications are utilized to lower the possible spread of COVID-19 to others by early diagnosis, monitoring patients, and practicing defined protocols after patient recovery. This paper surveys the role of IoT-based technologies in COVID-19 and reviews the state-of-the-art architectures, platforms, applications, and industrial IoT-based solutions combating COVID-19 in three main phases, including early diagnosis, quarantine time, and after recovery

Secure Smart Communication Efficiency in Federated Learning: Achievements and Challenges

Federated learning (FL) is known to perform machine learning tasks in a distributed manner. Over the years, this has become an emerging technology, especially with various data protection and privacy policies being imposed. FL allows for performing machine learning tasks while adhering to these challenges. As with the emergence of any new technology, there will be challenges and benefits. A challenge that exists in FL is the communication costs: as FL takes place in a distributed environment where devices connected over the network have to constantly share their updates, this can create a communication bottleneck. This paper presents the state-of-the-art of the conducted works on communication constraints of FL while maintaining the secure and smart properties that federated learning is known for. Overall, current challenges and possible methods for enhancing the FL models’ efficiency with a perspective on communication are discussed. This paper aims to bridge the gap in all conducted review papers by solely focusing on communication aspects in FL environments

Natural convection of rectangular cavity enhanced by obstacle and fin to simulate phase change material melting process using Lattice Boltzmann method

In recent years, the lattice Boltzmann method has become a powerful method for computational modeling of various complex fluid flow concerns, including the simulation of the melting process in phase change materials. In the present paper, the natural convection of phase change materials in a cavity is simulated, and the effect of adiabatic obstacle and fin is investigated by the lattice Boltzmann method. The obtained results are presented in different Rayleigh numbers (Ra = 103-105), and cavity angles (θ=-90to90) in three scenarios (without adiabatic fin and obstacle, with an adiabatic obstacle, and with adiabatic fin). The investigation across various cavity angles, with adiabatic obstacles and fins, demonstrates a consistent trend of effective melting process delay by up to 50%, underscoring the significant impact of these adiabatic features on PCM behavior. Adiabatic obstacles induce localized melting delays due to unmelted zones around them. Streamlines highlight vortices formed by obstacles, and elevated Nusselt numbers correlate with accelerated melting facilitated by adiabatic fins. Modifying the adiabatic fin height from Yf = 0.1 to Yf = 0.7 leads to a doubling of melting time at around 80% PCM melting. Conversely, decreasing fin height from 0.5 to 0.7 extends the complete melting time by approximately 10%, showcasing the influential role of fin height in shaping PCM melting behaviour

The effect of initial pressure on the thermal behavior of the silica aerogel/PCM/CuO nanostructure inside a cylindrical duct using molecular dynamics simulation

Amidst escalating fuel expenses and growing concerns over greenhouse gas pollution, the adoption of renewable alternative energy sources has become increasingly imperative. In response, scientists are fervently dedicated to identifying energy-saving solutions that are readily adaptable. Notably, silica aerogels have demonstrated remarkable efficacy in temperature management under both hot and cold conditions, while phase change materials are renowned for their capacity to store thermal energy. The study examines the effect of initial pressure on the thermal performance of silica aerogel/PCM/CuO nanostructure in a cylindrical duct. This was investigated using MD simulations and the LAMMPS software. The study will investigate several elements, such as density, velocity, temperature patterns, heat flux, thermal conductivity, and charge time or discharge time of the simulated structure. According to the results, with an increase in the initial pressure, the maximum density increases from 0.0838 atom/Å3 to 0.0852 atom/Å3, and the maximum velocity decreases from 0.0091 Å/fs to 0.0081 Å/fs. Also, the findings show that, by increasing the initial pressure, the temperature decreases from 931.42 K to 895.63 K, and thermal conductivity and heat flux decrease to 1.56 W/m.K and 56.66 W/m2 with increasing the initial pressure to 5 bar. Finally, the results show that charging time increases to 6.34 ns at 5 bar. The increase in charging time with increasing initial pressure may be attributed to the reduced mobility of particles within the structure as a result of the higher pressure. The findings of this study can help for a better understanding of energy-saving solutions, advanced thermal management systems, and the design of efficient energy storage technologies tailored to specific pressure-related operating conditions

The effect of different variables and using of the internal adiabatic wall in the construction and performance of thermosiphon heat pipes: Experimental investigation

Heat pipes are a practical and powerful tool for recovering thermal energy and conserving energy sources. Thermosiphon is one of the most widely used devices that can transfer large amounts of heat at high rates between hot and cold sources without the use of external energy. The amount of vacuum in the pipe, the percentage of fluid filling, the type of operating fluid, the pipe’s length and the quantity of heat flux are the factors affecting the efficiency and effectiveness of the thermosiphon heat pipe. In this paper, the effects of different variables in the construction of heat pipes such as working fluid, pipe length, the use of mesh screen wick structure and the use of internal adiabatic wall on the thermosiphon heat pipes performance are investigated. The results show that using of an internal adiabatic wall eliminates and reduces limitations such as boiling, evaporator drying, thermosiphon flooding and vapor pressure and significantly improves the heat pipe’s performance. So that, the effective thermal conductivity (K) is increased up to 350% using the internal adiabatic wall. However, in some nanofluids, such as water/multi-walled carbon nanotubes (MWCNT), with increasing the nanofluid’s mass fraction, the startup speed in heat pipes with internal adiabatic wall is reduced by up to 20%

Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance

COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards finding a cure, and different policies have been amended to mitigate the spread of the virus. While Machine Learning (ML) methods have been widely used in other domains, there is now a high demand for ML-aided diagnosis systems for screening, tracking, predicting the spread of COVID-19 and finding a cure against it. In this paper, we present a journey of what role ML has played so far in combating the virus, mainly looking at it from a screening, forecasting, and vaccine perspective. We present a comprehensive survey of the ML algorithms and models that can be used on this expedition and aid with battling the virus

Bonding evolution of composites fabricated via electrically assisted press bonding

Reducing fuel consumption and increasing efficiency is one of the solutions that humanity has adopted to reduce costs caused by fuel consumption in all industries, including the transportation industry. An effective solution to improve practical fuel consumption is to reduce weight. In principle, press bonding (PB), which is done using a press and is a solid-state welding process, can create a bond between parts with different materials and produce materials with lighter weight and more strength. But it should also be noted that the plasticity of some materials is very low, and these materials are incapable of machinability. Electrical assistance is a potential solution that can solve this problem by increasing the flow tension and reducing the forming force. In this study, aluminum alloy 1060 bars were electrically press bonded at electricity current levels 0 Å up to 300 Å. The effect of pressing parameters on the bonding strength, such as amount of electricity current level and plastic strain, was investigated using a peeling test. Results show that more adhesive among the layers (bonding strength) was attained by growing current and reducing thickness. Scanning electron microscope (SEM) was investigated the peeling surface of samples versus the different thickness reduction ratios and electric currents. The Joule heating effect in the electrically-assisted in press bonding (EAPB) process decreases the forming strength of bars and increases the bond strength of bonded bars by about three times. Using SEM, the peeling surface of samples and the fracture surface around the interface after the tensile test were studied to investigate the bonding quality