Since the last decade, cloud-based electronic health records (EHRs) have gained significant attention to enable remote patient monitoring. The recent development of Healthcare 4.0 using the Internet of Things (IoT) components and cloud computing to access medical operations remotely has gained the researcher's attention from a smart city perspective. Healthcare 4.0 mainly consisted of periodic medical data sensing, aggregation, data transmission, data sharing, and data storage. The sensitive and personal data of patients lead to several challenges while protecting it from hackers. Therefore storing, accessing, and sharing the patient medical information on the cloud needs security attention that data should not be compromised by the authorized user's components of E-healthcare systems. To achieve secure medical data storage, sharing, and accessing in cloud service provider, several cryptography algorithms are designed so far. However, such conventional solutions failed to achieve the trade-off between the requirements of EHR security solutions such as computational efficiency, service side verification, user side verifications, without the trusted third party, and strong security. Blockchain-based security solutions gained significant attention in the recent past due to the ability to provide strong security for data storage and sharing with the minimum computation efforts. The blockchain made focused on bitcoin technology among the researchers. Utilizing the blockchain which secure healthcare records management has been of recent interest. This paper presents the systematic study of modern blockchain-based solutions for securing medical data with or without cloud computing. We implement and evaluate the different methods using blockchain in this paper. According to the research studies, the research gaps, challenges, and future roadmap are the outcomes of this paper that boost emerging Healthcare 4.0 technology. 

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Integration of Healthcare 4.0 and blockchain into secure cloud-based electronic health records systems

Instrumentation, Measurement and Analysis , Instrumentation, Measurement and Analysis , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

Instrumentation: Measurement and Analysis

Deepfake network is a prominent topic of research as an application to various systems about security measures. Although there have been many recent advancements in facial reconstruction, the greatest challenge to overcome has been the means of finding an efficient and quick way to compute facial similarities or matches. This work is created utilizing the rationale-augmented convolutional neural network (CNN) on MATLAB R2019a platform using the Kaggle DeepFake Video dataset with an accuracy of 95.77%. Hence, real-time deepfake facial reconstruction for security purposes is difficult to complete concerning limited hardware and efficiency. This research paper looks into rational augmented CNN state-of-the-art technology utilized for deepfake facial reconstruction via hardware such as webcams and security cameras in real time. Additionally, discuss a history of face reconstruction and provide an overview of how it is accomplished.

Deepfake detection using rationale-augmented convolutional neural network

The emergence of the Industry 4.0 revolution to upgrade the Internet of Things (IoT) standards provides the prominence outcomes for the future wireless communication systems called 5G. The development of 5G green communication systems suffers from the various challenges to fulfill the requirement of higher user capacity, network speed, minimum cost, and reduced resource consumption. The use of 5G standards for Industry 4.0 applications will increase data rate performance and connected device's reliability. Since the arrival of novel Covid-19 disease, there is a higher demand for smart healthcare systems worldwide. However, designing the 5G communication systems has the research challenges like optimum resource utilization, mobility management, cost-efficiency, interference management, spectral efficiency, etc. The rapid development of Artificial Intelligence (AI) across the different formats brings performance enhancement compared to conventional techniques. Therefore, introducing the AI into 5G standards will optimize the performances further considering the various end-user applications. We first present the survey of the terms like 5G standard, Industry 4.0, and some recent works for future wireless communications. The purpose is to explore the current research problems using the 5G technology. We further propose the novel architecture for smart healthcare systems using the 5G and Industry 4.0 standards. We design and implement that proposed model using the Network Simulator (NS2) to investigate the current 5G methods. The simulation results show that current 5G methods for resource management and interference management suffer from the challenges like performance trade-offs. 

/pdf/5g-standards-for-the-industry-4-0-enabled-communication-en3wfbb4.pdf

5G standards for the Industry 4.0 enabled communication systems using artificial intelligence: perspective of smart healthcare system

The depletion of fossil fuel and the increase of energy demand in the world make renewable energy become an alternative energy source. Among these green energies, the wind energy is one of the popular energy sources since decades ago. Recently, there are small wind turbine developments which are suitable for urban and suburban application. However, the efficiency of the wind turbine is the main concern for all researchers due to the uncertainty of wind speed and direction in urban area.
In this paper, a new power augmented shroud integrated with vertical axis wind turbine (VAWT) is introduced. This power augmented shroud is able to improve the performance of the VAWT significantly by increasing the wind speed, channel the flow to better angle of attack for the VAWT and reduce the negative torque of the wind turbine. Hence, it improves the self-starting of the VAWT, and increase the coefficient of power.
The numerical method is used to simulate the wind flow for the power augmented shroud with a single bladed NACA 0015 airfoil VAWT by commercial computational fluid dynamic (CFD) software ANSYS FLUENT 14.0. In this 2D simulation, the shear stress transport (SST) k- turbulence model with the sliding mesh method was used with the tip speed ratio of 5.1 for the wind turbine. The result is verified by re-simulate the experiment published by Sandia National Laboratories.
The simulation result shows that the new design of power augmented shroud is able the increase the coefficient of power significant for the VAWT which is about 115.56% compare to the bare VAWT. Therefore, for urban area application, this power augmented shroud can solve the low efficiency problem for the VAWT.

The design and flow simulation of a power-augmented shroud for urban wind turbine system / Wong Kok Hoe

A cross-flow wind turbine has a high torque coefficient at a low tip speed ratio; therefore, it is a good candidate for a self-starting turbine. This study aims to investigate the best configuration between guide vanes and cross-flow vertical axis wind turbine. The experiment test was carried out to determine the turbine with the highest power coefficient. The cross-flow turbine has 14, 18, and 22 blades with using 6,10 and 14 blades of guide vane (GV) was developed in this study, employing 15°, 25°, 35°, 45°, 55°, 65°, and 75° of tilt angles in fifth different wind speed conditions 4 m/s, 6 m/s, 7.5 m/s, 9.20 m/s, and 11 m/s. The turbine has 22 blades with 14 GV blades at 55° of tilt angle blades producing more remarkable turbine performance improvement than other blades. The highest power coefficient (CP) of cross-flow using 14 GV blades at 55° was 0.0162 at 0.289 TSR, which increased around 59% of the turbine's performance using GV.

Study the influence of using guide vanes blades on the performance of cross-flow wind turbine

Influence of tilt angle and the number of guide vane blades towards the Savonius rotor performance

China's rapidly growing economy, population, and energy consumption are all threatening its future environmental sustainability. China faces many ecological challenges, and its reliance on coal is at the heart of most of the country's ecological troubles. Most of China's air pollution emissions come from the industrial and electricity sectors, and the human health costs of China's air pollution are very high. China is the largest global polluter, with more than 25 per cent of total global carbon dioxide (CO2) emissions, green development could help mitigate climate change and enhance global welfare. Over the past decades, the demand for energy sources has increased by 150% in China, which has made China among the most energy-consuming countries. Most of China's energy consumption comes from coal energy, which accounts for about 78% of all energy sources in China in 2011. China is one of the world's largest wind energy sources, according to data released by the World Wind Energy Association (WWEA), with about 34% of the world's wind energy sources. According to the road map implemented by the Chinese government by exploiting and generating wind energy sources and benefiting from the rapid economic development that China witnessed late, according to this plan by 2020, China is expected to produce about 250 gigawatts (GW). By 2030, production may reach 400 GW of electrical energy generated from wind energy, and by 2050, production may reach 1,000 GW.

Kou Ziming

Papers

Study the influence of using guide vanes blades on the performance of cross-flow wind turbine

Influence of tilt angle and the number of guide vane blades towards the Savonius rotor performance

Outlook of Renewable Energy (Wind Energy) in China