Blended learning incorporates online learning experiences and helps students for meaningful learning through flexible online information and communication technologies, reduced overcrowded classroom presence, and planned teaching and learning experience. This study has conducted surveys of various tools, techniques, frameworks, and models useful for blended learning. This article has prepared a comprehensive survey of student, teacher, and management experiences in blended learning courses during COVID-19 and pre-COVID-19 times. The survey will be useful to faculty members, students, and management to adopt new tools and mindsets for positive outcomes. This work reports on implementing and assessing blended learning at two different universities

Internet of Things (IoT) has revolutionized the digital world by connecting billions of electronic devices over the internet. IoT devices play an essential role in the modern era when conventional devices become more autonomous and smart. On the one hand, high‐speed data transfer is a major issue where the 5G‐enabled environment plays an important role. On the other hand, these IoT devices transfer the data by using protocols based on centralized architecture and may cause several security issues for the data. Merging artificial intelligence to 5G wireless systems solves several issues such as autonomous robots, self‐driving vehicles, virtual reality, and engender security problems. Building trust among the network users without trusting third party authorities is the system's primary concern. Blockchain emerged as a key technology based on a distributed ledger to maintain the network's event logs. Blockchain provides a secure, decentralized, and trustless environment for IoT devices. However, integrating IoT and blockchain also has several challenges; for example, major challenge is low throughput. Currently, the ethereum blockchain network can process approximately 12 to 15 transactions per second, while IoT devices require relatively higher throughput. Therefore, blockchains are incapable of providing functionality for a 5G‐enabled IoT based network. The limiting factor of throughput in the blockchain is their network. The slow propagation of transactions and blocks in the P2P network does not allow miners and verifiers to fastly mine and verify new blocks, respectively. Therefore, network scalability is the major issue of IoT based blockchains. In this work, we solved the network scalability issue using blockchain distributed network while to increase the throughput of blockchain, this article uses the Raft consensus algorithm. Another most important issue with IoT networks is privacy. Unfortunately, the blockchain distributed ledgers are public and sensitive information is available on the network for everyone are private, but in such cases, third party editing is not possible without revealing the original contents. To solve privacy issues, we used zkLedger as a solution that is based on zero knowledge‐based cryptography.

Batteries of field nodes in a wireless sensor network pose an upper limit on the network lifetime. Energy harvesting and harvesting aware medium access control protocols have the potential to provide uninterrupted network operation, as they aim to replenish the lost energy so that energy neutral operation of the energy harvesting nodes can be achieved. To further improve the energy harvesting process, there is a need for novel schemes so that maximum energy is harvested in a minimum possible time. Multi-hop radio frequency (RF) energy transfer is one such solution that addresses these needs. With the optimal placement of energy relay nodes, multi-hop RF energy transfer can save energy of the source as well as time for the harvesting process. In this work we experimentally demonstrate multi-hop RF energy transfer, wherein two-hop energy transfer is shown to achieve significant energy and time savings with respect to the single-hop case. It is also shown that the gain obtained can be translated to energy transfer range extension.

Wake-up receiver (WuRx) is a promising hardware solution that extends the life of a sensor node by switching off its radio to reduce idle listening energy consumption. The existing passive WuRxs are RFID tag based, which incur high cost and complexity. In this paper, we study cost-effective and long range WuRx solutions for range-based wake-up (RW) as well as directed wake-up (DW). In particular, we consider the case of an RF energy harvesting wireless sensor node and investigate how a low-cost WuRx can be built using an RF energy harvester available at the node without compromising the harvesting sensitivity and efficiency. Experimental results show that our developed prototype can achieve a wake-up range of 1.16 m with +13 dBm transmit power. Further, our empirical study shows that at +30 dBm transmit power the wake-up distance of our developed RW module is > 9 m. High accuracy of DW is demonstrated by sending a 5-bit ID from a transmitter at a bit rate up to 33.33 kbps. Finally, we present optimized WuRx designs for RW and DW using Agilent advanced design system, which offer up to 5.69 times higher wake-up range for RW and energy savings per bit of about 0.41 mJ and 21.40 nJ, respectively, at the transmitter and the sensor node in DW.

One of the most common types of cancer in women is cervical cancer, a disease which is the most prevalent in poor nations, with one woman dying from it every two minutes. It has a major impact on the cancer burden in all cultures and economies. Clinicians have planned to use improvements in digital imaging and machine learning to enhance cervical cancer screening in recent years. Even while most cervical infections, which generate positive tests, do not result in precancer, women who test negative are at low risk for cervical cancer over the next decade. The problem is determining which women with positive HPV test results are more likely to have precancerous alterations in their cervical cells and, as a result, should have a colposcopy to inspect the cervix and collect samples for biopsy, or who requires urgent treatment. Previous research has suggested techniques to automate the dual-stain assessment, which has significant clinical implications. The authors reviewed previous research and proposed the cancer risk prediction model using deep learning. This model initially imports dataset and libraries for data analysis and posts which data standardization and basic visualization was performed. Finally, the model was designed and trained to predict cervical cancer, and the accuracy and performance were evaluated using the Cervical Cancer dataset.

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Due to recent advancements in quantum drones, the Internet of Quantum Drones (IoQDs), and Drone-to-Satellite connectivity, several advantages have been anticipated for real-time applications. This work examines quantum computing issues, including quantum data processing, techniques, circuits, and algorithms important for quantum drones or their networks. Here, we discussed the current research trends on quantum computing, quantum-safe computing, or post-quantum cryptography important to quantum networks, followed by the numerous advantages, limitations, future advancements, and research issues connected with quantum technologies, drones, and their network. This work has also prepared a taxonomy of quantum-related areas depending upon the logic of their learning, followed by a review of each of these areas. We review the most recent work over quantum algorithms used in various-quantum-related areas and networks, the role of quantum satellites for drone-based networks and communications, how quantum artificial intelligence and quantum machine learning are important for quantum drones, networks and futuristic applications, quantum attacks, quantum genetic algorithms, and the importance of post-quantum and quantum-safe cryptography. The challenges and research directions in these domains are explored as well. Lastly, this work presents an overview of the current state of knowledge in various promising technologies that are recently found to be important for quantum drones and networks.

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