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Topic Review
Relational Cues and Tailoring of e-Coach Dialogues
Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts.
  • 280
  • 12 Oct 2023
Topic Review
Vehicular Routing and Intelligent Transportation Systems
Urban areas all over the world, from New York's skyscraper-filled skyline to Casablanca's busy streets, have been coping with an exponential surge in vehicle traffic in recent years. This phenomena highlights the larger socioeconomic dynamics influencing current period as well as the world's rising obsession with autos. The effects of this traffic increase are being felt most acutely in emerging powerhouses and developed countries with their advanced industries and economies that are rapidly industrializing and urbanizing. A series of difficulties have arisen as a result of the growth in vehicle traffic. Cities are now frequently congested with traffic, turning once-smooth thoroughfares into figurative parking lots during rush hours. In addition to trying commuters' patience, congestion like this has real-world economic repercussions.  The need for transportation increases logically as cities grow in population with younger citizens. What is particularly alarming, though, is the glaring inconsistency in many urban areas: while the number of automobiles increases, there is a glaring delay in improving road infrastructure and bolstering safety measures. The promise of effortless urban mobility is in danger of becoming an uncontrollable nightmare due to this imbalance.
  • 280
  • 10 Nov 2023
Topic Review
Ransomware Attack Detection
Several malware variants have attacked systems and data over time. Ransomware is among the most harmful malware since it causes huge losses. In order to get a ransom, ransomware is software that locks the victim’s machine or encrypts his personal information. Numerous research has been conducted to stop and quickly recognize ransomware attacks.
  • 279
  • 29 Nov 2023
Topic Review
Breast Cancer Diagnosis Based on Deep Mutual Learning
Breast cancer (BC) is the most common kind of cancer in women, accounting for around 30% of all new cancer diagnoses; it is also the second most fatal malignancy after lung and bronchial cancers. Centered on deep convolutional neural networks, a new BC histopathological image category blind inpainting convolutional neural network (BiCNN) model has been developed. It was developed to cope with the two-class categorization of BC on the diagnostic image.
  • 279
  • 05 Jan 2024
Topic Review
Multi-Task Learning, Multi-Branch Networks, and Attention Mechanisms
Diabetic Retinopathy (DR) is one of the most common microvascular complications of diabetes. Diabetic Macular Edema (DME) is a concomitant symptom of DR. As the grade of lesion of DR and DME increases, the possibility of blindness can also increase significantly. To take early interventions as soon as possible to reduce the likelihood of blindness, it is necessary to perform both DR and DME grading. 
  • 279
  • 18 Jan 2024
Topic Review
Incremental Deep Learning for Defect Detection in Manufacturing
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedures to dynamically update model-based detection methods that use sequential streaming during the training phase.
  • 279
  • 23 Feb 2024
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.
  • 279
  • 12 Sep 2023
Topic Review
Cross-Parallel Vision Transformers for Medical Image Segmentation
Medical image segmentation primarily utilizes a hybrid model consisting of a Convolutional Neural Network and sequential Transformers. The latter leverage multi-head self-attention mechanisms to achieve comprehensive global context modelling. However, despite their success in semantic segmentation, the feature extraction process is inefficient and demands more computational resources, which hinders the network’s robustness. To address this issue, this research presents two innovative methods: PTransUNet (PT model) and C-PTransUNet (C-PT model). The C-PT module refines the Vision Transformer by substituting a sequential design with a parallel one. This boosts the feature extraction capabilities of Multi-Head Self-Attention via self-correlated feature attention and channel feature interaction, while also streamlining the Feed-Forward Network to lower computational demands.
  • 279
  • 18 Dec 2023
Topic Review
Matrix Factorization Recommendation Algorithm Based on Attention Interaction
Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that users are interested in are recommended to users.
  • 278
  • 26 Feb 2024
Topic Review
Image-Based Fault Monitoring in Additive Manufacturing
Fault monitoring in additive manufacturing (AM) refers to the systematic process of monitoring and detecting deviations, anomalies, or faults during printing to ensure the printed parts’ quality, integrity, and reliability. It involves continuously monitoring the AM process’s critical parameters, variables, or characteristics and comparing them against predetermined thresholds or expected values. The goal is to identify and address any faults or anomalies that may compromise the final part’s quality or performance. It involves using various techniques, such as in-process monitoring, real-time data analysis, and automated systems, to identify faults or deviations from desired specifications. By monitoring parameters such as temperature, pressure, laser power, material flow, layer deposition, or surface quality, fault monitoring allows for the early detection of defects, material inconsistencies, structural irregularities, or printing errors.
  • 277
  • 14 Aug 2023
Topic Review
Detecting Misalignment State of Angle Cocks
As one of the key components in the braking system, the angle cock is the switch of the train ventilation duct, which realizes the braking through the air transmission between carriages, so that the train can achieve the purpose of regulating speed or stopping.
  • 277
  • 05 Sep 2023
Topic Review
CV and AI in Seaport Parking Space Allocation
Urban expansion has ushered in a landscape of opportunities and challenges across housing, transportation, education, health, and the economy. In response to these evolving dynamics, the application of artificial intelligence (AI) and computer vision (CV) technologies has emerged as a transformative solution. While smart traffic monitoring and advanced parking distribution systems have eased urban pressures, optimizing mobility remains pivotal in the context of burgeoning smart cities.
  • 277
  • 20 Sep 2023
Topic Review
Real-Time Intelligent Detection System for Illegal Wearing
Ensuring personal safety and preventing accidents are critical aspects of power construction safety supervision. However, current monitoring methods are inefficient and unreliable as most of them rely on manual monitoring and transmission, which results in slow detection and delayed warnings regarding violations.
  • 276
  • 27 Jul 2023
Topic Review
Imaging Techniques Used in Fish Bioimages
Detecting skeletal or bone-related deformities in model and aquaculture fish is vital for numerous biomedical studies. In biomedical research, model fish with bone-related disorders are potential indicators of various chemically induced toxins in their environment or poor dietary conditions. In aquaculture, skeletal deformities are affecting fish health, and economic losses are incurred by fish farmers. 
  • 276
  • 09 Jan 2024
Topic Review
Intelligent Question Answering System
Intelligent question answering system is an innovative information service system which integrates natural language processing, information retrieval, semantic analysis and artificial intelligence. The system mainly consists of three core parts, which are question analysis, information retrieval and answer extraction. Through these three parts, the system can provide users with accurate, fast and convenient answering services.
  • 275
  • 20 Aug 2024
Topic Review
Inpainting Methods
Image inpainting is sometimes called an inverse problem, and usually these types of problems are ill-posed. The problem of inpainting consists in finding the best approximation to fill in the region inside the source image and comparing it with the ground truth. All the algorithms that tackle this problem begin with the assumption that there must be some correlation between the pixels present inside the image, either from a statistical or from a geometrical perspective.
  • 274
  • 20 Feb 2024
Topic Review
Facial Expression Recognition System Using Convolutional Neural Network
Recognizing facial expressions plays a crucial role in various multimedia applications, such as human–computer interactions and the functioning of autonomous vehicles. An individual’s facial expressions (FEs) or countenance convey their psychological reactions and intentions in response to a social or personal event. These expressions convey non-verbal stealth messages. With technological advancements, human behavior can be understood through facial expression recognition (FER). To express emotions, humans use facial expressions as their primary nonverbal communication method.
  • 273
  • 17 Nov 2023
Topic Review
DiabeticSense
Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood glucose level surveillance. Current invasive techniques, such as finger-prick tests, often result in discomfort, leading to infrequent monitoring and potential health complications. Researchers was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named DiabeticSense, an affordable digital health device for early detection, to encourage immediate intervention. The device employed electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differed between diabetic and non-diabetic individuals. The system merged vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions.
  • 273
  • 29 Dec 2023
Topic Review
Facial Expression Recognition Using Local Sliding Window Attention
There are problems associated with facial expression recognition (FER), such as facial occlusion and head pose variations. These two problems lead to incomplete facial information in images, making feature extraction extremely difficult. 
  • 273
  • 25 Dec 2023
Topic Review
Emotion Recognition Systems
Emotion recognition systems (ERS) are an emerging technology with immense potential, exemplifying the innovative utilization of artificial intelligence (AI) within the context of the fourth industrial revolution (IR 4.0). Given that personalization is a key feature of the fifth industrial revolution (IR 5.0), ERS has the potential to serve as an enabler for IR 5.0. Furthermore, the COVID-19 pandemic has increased the relevance of this technology as work processes were adapted for social distancing and the use of face masks. Even in the post-pandemic era, many individuals continue to wear face masks. Therefore, ERS offers a technological solution to address communication challenges in a masked world. The existing body of knowledge on ERS primarily focuses on exploring modalities or modes for emotion recognition, system development, and the creation of applications utilizing emotion recognition functions.
  • 273
  • 14 Nov 2023
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