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Topic Review
Dementia Severity Scale Based on MRI
In the clinical treatment of Alzheimer’s disease, one of the most important tasks is evaluating its severity for diagnosis and therapy. However, traditional testing methods are deficient, such as their susceptibility to subjective factors, incomplete evaluation, low accuracy, or insufficient granularity, resulting in unreliable evaluation scores. 
  • 853
  • 11 Aug 2023
Topic Review
Risk Traceability Using Blockchain Technology
Regulatory authorities, consumers, and producers alike are alarmed by the issue of food safety, which is a matter of international concern. The conventional approaches utilized in food quality management demonstrate deficiencies in their capacity to sufficiently address issues related to traceability, transparency, and accountability. The emergence of blockchain technology (BCT) has provided a feasible approach to tackle the challenge of regulating food safety. 
  • 852
  • 22 Nov 2023
Topic Review
Generative AI
Generative AI models harness the capabilities of neural networks to discern patterns and structures within existing datasets and create original content. These AI models draw inspiration from human neuronal processes, learning from data inputs to create new output that matches learned patterns.
  • 852
  • 22 Feb 2024
Topic Review
KinectGaitNet
Gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports training. The main advantages of identifying a person by their gait include unobtrusiveness, acceptance, and low costs. Researchers proposes a convolutional neural network KinectGaitNet for Kinect-based gait recognition. The 3D coordinates of each of the body joints over the gait cycle are transformed to create a unique input representation. The proposed KinectGaitNet is trained directly using the 3D input representation without the necessity of the handcrafted features. The KinectGaitNet design allows avoiding gait cycle resampling, and the residual learning method ensures high accuracy without the degradation problem.
  • 851
  • 20 Apr 2022
Topic Review
Commonsense-Guided Inductive Relation Prediction with Dual Attention Mechanism
Inductive relationship prediction for knowledge graphs, as an important research topic, aims to predict missing relationships between unknown entities and many practical applications. Most of the existing approaches to this problem use closed subgraphs to extract features of target nodes for prediction; however, there is a tendency to ignore neighboring relationships outside the closed subgraphs, which leads to inaccurate predictions. In addition, they ignore the rich commonsense information that can help filter out less compelling results.
  • 849
  • 07 Mar 2024
Topic Review
A Taxonomic Survey of Physics-Informed Machine Learning
Physics-informed machine learning (PIML) refers to the emerging area of extracting physically relevant solutions to complex multiscale modeling problems lacking sufficient quantity and veracity of data with learning models informed by physically relevant prior information.
  • 847
  • 20 Jun 2023
Topic Review
Agricultural Image Segmentation
The Segment Anything Model (SAM) is a versatile image segmentation model that enables zero-shot segmentation of various objects in any image using prompts, including bounding boxes, points, texts, and more. However, studies have shown that the SAM performs poorly in agricultural tasks like crop disease segmentation and pest segmentation. To address this issue, the agricultural SAM adapter (ASA) is proposed, which incorporates agricultural domain expertise into the segmentation model through a simple but effective adapter technique.
  • 846
  • 27 Sep 2023
Topic Review
Industry 4.0, Cyber-Physical Systems and Smart Cyber-Physical Systems
Modern society is experiencing a significant transformation. Thanks to the digitization of society and manufacturing, mainly because of a combination of technologies, such as the Internet of Things, cloud computing, machine learning, smart cyber-physical systems, etc., which are making the smart factory and Industry 4.0 a reality. Most of the intelligence of smart cyber-physical systems is implemented in software.
  • 845
  • 11 Aug 2023
Topic Review
Multimodal Approach for Pilot Mental State Detection
The safety of flight operations depends on the cognitive abilities of pilots. The process of identifying mental states typically involves four steps: collecting data, cleaning it, selecting relevant features, and making predictions. The first step involves capturing signals from the brain and converting them into digital form. Then, to ensure accurate analysis, any extraneous noise or artifacts present in the data are removed through preprocessing. Next, specific characteristics of the data are selected and extracted in preparation for classification. These extracted features are then used by a classifier to make predictions about which class the data belongs to. As this process specifically relates to electrocardiogram (ECG) data, the following provides a summary of previous research on the three stages of mental state detection: preprocessing, feature extraction, and classification.
  • 845
  • 12 Sep 2023
Topic Review
HVAC Data-Driven Maintenance
Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment. The adoption of Internet of Things (IoT) sensors integrated into HVAC systems has paved the way for data-driven predictive maintenance (PdM) grounded in real-time operational metrics.
  • 845
  • 27 Oct 2023
Topic Review
Application Profiling System Architecture
Along with the rise of cloud and edge computing has come a plethora of solutions that regard the deployment and operation of different types of applications in such environments. Infrastructure as a service (IaaS) providers offer a number of different hardware solutions to facilitate the needs of the growing number of distributed applications. It is critical in this landscape to be able to navigate and discover the best-suited infrastructure solution for the applications, taking into account not only the cost of operation but also the quality of service (QoS) required for any given application. The proposed solution has two main research developments: (a) the creation and optimisation of multidimensional vectors that represent the hardware usage profiles of an application, and (b) the assimilation of a machine learning classification algorithm, in order to create a system that can create hardware-agnostic profiles of a vast variety of containerised applications in terms of nature and computational needs and classify them to known benchmarks. Given that benchmarks are widely used to evaluate a system’s hardware capabilities, having a system that can help select which benchmarks best correlate to a given application can help an IaaS provider make a more informed decision or recommendation on the hardware solution, not in a broad sense, but based on the needs of a specific application.
  • 837
  • 20 Dec 2022
Topic Review
Deep Learning Using Explainable Artificial Intelligence and Clustering
Explainable artificial intelligence (XAI) is a field of Artificial Intelligence (AI) that seeks to offer insights into black-box models and their predictions. Trust, performance, legal (regulation), and ethical considerations are some reasons researchers advocate for XAI.
  • 837
  • 23 Nov 2023
Topic Review
Controlling Upper Limb Prostheses Using Sonomyography
A ground-breaking study by Zheng et al. investigated whether ultrasound imaging of the forearm might be used to control a powered prosthesis, and the term “sonomyography” (SMG) was coined by the group. Ultrasound signals have recently garnered the interest of researchers in the area of HMIs because they can collect information from both superficial and deep muscles and so provide more comprehensive information than other techniques. Due to the great spatiotemporal resolution and specificity of ultrasound measurements of muscle deformation, researchers have been able to infer fine volitional motor activities, such as finger motions and the dexterous control of robotic hands.
  • 834
  • 27 Feb 2023
Topic Review
Explainable AI for Health Care
Artificial intelligence (AI) have facilitated its widespread adoption in primary medical services, addressing the demand–supply imbalance in healthcare. Vision Transformers (ViT) have emerged as state-of-the-art computer vision models, benefiting from self-attention modules. However, compared to traditional machine learning approaches, deep learning models are complex and are often treated as a “black box” that can cause uncertainty regarding how they operate. Explainable artificial intelligence (XAI) refers to methods that explain and interpret machine learning models’ inner workings and how they come to decisions, which is especially important in the medical domain to guide healthcare decision-making processes. 
  • 833
  • 18 Jan 2024
Topic Review
Wrist-Based Electrodermal Activity Monitoring for Stress Detection
With the most recent developments in wearable technology, the possibility of continually monitoring stress using various physiological factors has attracted much attention. By reducing the detrimental effects of chronic stress, early diagnosis of stress can enhance healthcare. Machine Learning (ML) models are trained for healthcare systems to track health status using adequate user data. Insufficient data is accessible.
  • 832
  • 22 Dec 2023
Topic Review
Strawberry Ripeness Classification
Image analysis-based artificial intelligence (AI) models leveraging convolutional neural networks (CNN) take a significant role in evaluating the ripeness of strawberry, contributing to the maximization of productivity. However, the convolution, which constitutes the majority of the CNN models, imposes significant computational burdens. Additionally, the dense operations in the fully connected (FC) layer necessitate a vast number of parameters and entail extensive external memory access. Therefore, reducing the computational burden of convolution operations and alleviating memory overhead is essential in embedded environment.
  • 832
  • 07 Feb 2024
Topic Review
Ion-Movement-Based Synaptic Device for Brain-Inspired Computing
As the amount of data has grown exponentially with the advent of artificial intelligence and the Internet of Things, computing systems with high energy efficiency, high scalability, and high processing speed are urgently required. Unlike traditional digital computing, which suffers from the von Neumann bottleneck, brain-inspired computing can provide efficient, parallel, and low-power computation based on analog changes in synaptic connections between neurons. Synapse nodes in brain-inspired computing have been typically implemented with dozens of silicon transistors, which is an energy-intensive and non-scalable approach. Ion-movement-based synaptic devices for brain-inspired computing have attracted increasing attention for mimicking the performance of the biological synapse in the human brain due to their low area and low energy costs.
  • 831
  • 27 May 2022
Topic Review
Existing Approaches for Single-Image Super-Resolution
Deep learning has been introduced to single-image super-resolution (SISR). These techniques have taken over the benchmarks of SISR tasks. Nevertheless, most architectural designs necessitate substantial computational resources, leading to a prolonged inference time on embedded systems or rendering them infeasible for deployment.
  • 830
  • 04 Jul 2023
Topic Review
Semantic Image Segmentation with Scantly Annotated Data
Semantic image segmentation is the task of assigning to each pixel the class of its enclosing object or region as its label, thereby creating a segmentation mask. The success of deep networks for the semantic segmentation of images is limited by the availability of annotated training data. The manual annotation of images for segmentation is a tedious and time-consuming task that often requires sophisticated users with significant domain expertise to create high-quality annotations over hundreds of images.
  • 828
  • 18 Jul 2022
Topic Review
Cards Against Calamity Learning Game: Civics, Negotiation, Sustainability
Learning games for instruction constitute a progressively important and mutually universal challenge for academics, researchers, and software engineers worldwide. Gaming offers immersive space for interaction and co-creation of successful negotiation and conflict management, civic learning and sustainable development attributes in higher education and workplace context. 
  • 828
  • 16 Nov 2022
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