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Topic Review
AI and Neural Network Algorithms
Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into the daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a num- ber of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Researchers investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors.
  • 431
  • 13 Sep 2022
Topic Review
A Patch-Based CNN Built on the VGG-16 Architecture
Facial recognition is a prevalent method for biometric authentication that is utilized in a variety of software applications. This technique is susceptible to spoofing attacks, in which an imposter gains access to a system by presenting the image of a legitimate user to the sensor, hence increasing the risks to social security. Consequently, facial liveness detection has become an essential step in the authentication process prior to granting access to users. A patch-based convolutional neural network (CNN) with a deep component for facial liveness detection for security enhancement was developed, which was based on the VGG-16 architecture.
  • 689
  • 13 Sep 2022
Topic Review
Detection-Based Vision-Language Understanding
Given a query language, a Detection-based Vision-Language Understanding (DVLU) system needs to respond based on the detected regions (i.e.,bounding boxes). With the significant advancement in object detection, DVLU has witnessed great improvements in recent years, such as Visual Question Answering (VQA) and Visual Grounding (VG).
  • 549
  • 09 Sep 2022
Topic Review
VGG-C Transform Model to Predict Alzheimer’s Disease
Alzheimer’s disease (AD) is a chronic neurobiological brain disorder that continuously kills brain cells and causes deficits in memory and thinking skills, eventually accelerating the loss of the ability to perform even the most basic tasks. Early detection and automatic AD classification have emerged, resulting in large-scale multimodal neuroimaging results. Other methods of AD research include MRI, positron emission tomography (PET), and genotype sequencing results. Analyzing different modalities to make a decision is time consuming.
  • 384
  • 09 Sep 2022
Topic Review
Blockchain in the Healthcare Sector
The emergence of blockchain technology makes it possible to address disparate distributed system security concerns in formerly ridiculous practices. A key factor of this ability is the decentralization of the symmetrically distributed ledgers of blockchain. Such decentralization has replaced several security functionalities of centralized authority with the use of cryptographic systems. That is, public or asymmetric cryptography is the key part of what makes blockchain technology possible. The blockchain experience introduces the chance for the healthcare field to implement these knowhows in their electronic records. This adoption supports retaining and sharing the symmetrical patient records with the appropriate alliance of hospitals and healthcare providers in a secure decentralized system, using asymmetric cryptography like hashing, digitally signed transactions, and public key infrastructure. These include specialized applications for drug tracking, applications for observing patients, or Electronic Health Records (EHR). Therefore, it is essential to notice that the principled awareness of the healthcare professionals is the leading point of the right perception ethics. 
  • 834
  • 09 Sep 2022
Topic Review
Link Lifetime Prediction in Vehicular Ad Hoc Networks
In urban mobility, Vehicular Ad Hoc Networks (VANETs) provide a variety of intelligent applications. By enhancing automobile traffic management, these technologies enable advancements in safety and help decrease the frequency of accidents. The transportation system can now follow the development and growth of cities without sacrificing the quality and organisation of its services thanks to safety apps that include collision alerts, real-time traffic information, and safe driving applications, among others. Applications can occasionally demand a lot of computing power, making their processing impractical for cars with limited onboard processing capacity. Offloading of computation is encouraged by such a restriction. However, because vehicle mobility operations are dynamic, communication times (also known as link lifetimes) between nodes are frequently short. VANET applications and processes are impacted by such communication delays (e.g., the offloading decision when using the Computational Offloading technique). Making an accurate prediction of the link lifespan between vehicles is therefore challenging.
  • 423
  • 09 Sep 2022
Topic Review
Spatiality Sensitive Learning for Cancer Metastasis Detection
Metastasis detection in lymph nodes via microscopic examination of histopathological images is one of the most crucial diagnostic procedures for breast cancer staging. The manual analysis is extremely labor-intensive and time-consuming because of complexities and diversities of histopathology images. Deep learning has been utilized in automatic cancer metastasis detection in recent years. Due to the huge size of whole-slide images, most existing approaches split each image into smaller patches and simply treat these patches independently, which ignores the spatial correlations among them.
  • 356
  • 08 Sep 2022
Topic Review
Novel Pooling Methods for Convolutional Neural Networks
Neural network computational methods have evolved over the past half-century. In 1943, McCulloch and Pitts designed the first model, recognized as the linear threshold gate. Hebbian developed the Hebbian learning rule approach for training the neural network. However, would the Hebbian rule remain productive when all the input patterns became orthogonal? The existence of orthogonality in input vectors is a crucial component for this rule to execute effectively. To meet this requirement, a much more productive learning rule, known as the Delta rule, was established. Whereas the delta rule poses issues with the learning principles outlined above, backpropagation has developed as a more complicated learning approach. Backpropagation could learn an infinite layered structure and estimate any commutative function. A feed-forward neural network is most often trained using backpropagation (FFNN).
  • 491
  • 08 Sep 2022
Topic Review
Fog and IoT Driven Healthcare
Technological advancements have made it possible to monitor, diagnose, and treat patients remotely. The vital signs of patients can now be collected with the help of Internet of Things (IoT)-based wearable sensor devices and then uploaded on to a fog server for processing and access by physicians for recommending prescriptions and treating patients through the Internet of Medical Things (IoMT) devices. 
  • 783
  • 07 Sep 2022
Topic Review
An Overview of the Fundamental Vaccine Safety Concepts
The rapid development of effective vaccines against COVID-19 is an extraordinary achievement. However, no medical product can ever be considered risk-free. Several countries have a pharmacovigilance system that detects, assesses, understands, and prevents possible adverse effects of a drug. To benefit from such huge data sources, specialists and researchers need advanced big data analysis tools able to extract value and find valuable insights
  • 436
  • 06 Sep 2022
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