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Topic Review
Robotic-Systems for Improving Upper-Limb Spasticity
Spasticity is a motor disorder that causes stiffness or tightness of the muscles and can interfere with normal movement, speech, and gait. Traditionally, the spasticity assessment is carried out by clinicians using standardized procedures for objective evaluation. However, these procedures are manually performed and, thereby, they could be influenced by the clinician’s subjectivity or expertise. The automation of such traditional methods for spasticity evaluation is an interesting and emerging field in neurorehabilitation. One of the most promising approaches is the use of robot-aided systems.
  • 1.2K
  • 26 Oct 2020
Topic Review
Augmented Reality in Professional Training
Professional training is defined as a set of behaviors and acts with the purpose of increasing the employees’ professional skills to carry out a particular job in a better manner. Such a definition highlights three important features of professional training. First, its purpose is educational, which focuses on employee development (e.g., skill acquisition and knowledge growth) rather than performance improvement. Augmented reality (AR) is defined as a technology-enhanced environment where virtual objects (augmented components) can be overlaid into the real world. Azuma (1997) identified three technical features of AR: a combination of the real and virtual world, real-time interaction, and accurate 3D registration of virtual and real objects.
  • 1.2K
  • 27 Jan 2022
Topic Review
AI Agent Model for Extrinsic Emotion Regulation
Emotion regulation is the human ability to modulate one’s or other emotions to maintain emotional well-being. Despite its importance, only a few computational models have been proposed for facilitating emotion regulation. To address this gap, a computational model for intelligent agents has been proposed for facilitating emotion regulation in individuals. This model is grounded in a multidimensional emotion representation and on J. Gross’s theoretical framework of emotion regulation. In this apporach, an intelligent agent selects the most appropriate regulation strategies to reach or maintain an individual’s emotional equilibrium considering the individual’s personality traits and specific characteristics.
  • 1.2K
  • 11 Mar 2024
Topic Review
Machine Learning-Based Text Classification Comparison
The growth in textual data associated with the increased usage of online services and the simplicity of having access to these data has resulted in a rise in the number of text classification research papers. Text classification has a significant influence on several domains such as news categorization, the detection of spam content, and sentiment analysis. The classification of Turkish text is the research focus since only a few studies have been conducted in this context. Researchers utilize data obtained from customers’ inquiries that come to an institution to evaluate the proposed techniques. Classes are assigned to such inquiries specified in the institution’s internal procedures. The Support Vector Machine, Naïve Bayes, Long Term-Short Memory, Random Forest, and Logistic Regression algorithms were used to classify the data. The performance of the various techniques was then analyzed after and before data preparation, and the results were compared. The Long Term-Short Memory technique demonstrated superior effectiveness in terms of accuracy, achieving an 84% accuracy rate, surpassing the best accuracy record of traditional techniques, which was 78% accuracy for the Support Vector Machine technique. The techniques performed better once the number of categories in the dataset was reduced. Moreover, the findings show that data preparation and coherence between the classes’ number and the number of training sets are significant variables influencing the techniques’ performance.
  • 1.2K
  • 01 Sep 2023
Topic Review
The Urban Transit Routing Problem
The Urban Transit Routing Problem (UTRP) is a challenging problem in transportation planning that involves designing and optimizing transit route networks for urban areas. The objective is to find the most efficient routes for public transportation vehicles, considering factors such as travel time, passenger demand, transfer connections, vehicle capacities, operating costs, and environmental impacts. 
  • 1.2K
  • 21 Aug 2023
Topic Review
Short Video Classification Framework
The explosive growth of online short videos has brought great challenges to the efficient management of video content classification, retrieval, and recommendation. Video features for video management can be extracted from video image frames by various algorithms, and they have been proven to be effective in the video classification of sensor systems. 
  • 1.2K
  • 27 Nov 2023
Topic Review
Machine Learning in Agricultural Big Data
Agricultural Big Data is a set of technologies that allows responding to the challenges of the new data era. In conjunction with machine learning, farmers can use data to address problems such as farmers’ decision making, water management, soil management, crop management, and livestock management. Crop management includes yield prediction, disease detection, weed detection, crop quality, and species recognition. On the other hand, livestock management considers animal welfare and livestock production. 
  • 1.2K
  • 08 Apr 2022
Topic Review
Deep Learning Models to Predict Prosthetic Ankle Torque
Inverse dynamics from motion capture is the most common technique for acquiring biomechanical kinetic data. However, this method is time-intensive, limited to a gait laboratory setting, and requires a large array of reflective markers to be attached to the body. A practical alternative must be developed to provide biomechanical information to high-bandwidth prosthesis control systems to enable predictive controllers.
  • 1.2K
  • 25 Sep 2023
Topic Review
Machine Learning-based Driver Drowsiness Detection Using Visual Features
Drowsiness-related car accidents continue to have a significant effect on road safety. Many of these accidents can be eliminated by alerting the drivers once they start feeling drowsy. Image-based systems are the most commonly used techniques for detecting driver drowsiness. Facial parameters such as the eyes, mouth, and head can be used to identify many visual behaviors that fatigued people exhibit.
  • 1.2K
  • 06 Jun 2023
Topic Review
Oximetry for Obstructive Sleep Apnea
Scoring polysomnography for obstructive sleep apnea diagnosis is a laborious, long, and costly process. Machine learning approaches, such as deep neural networks, can reduce scoring time and costs.
  • 1.2K
  • 11 Oct 2023
Topic Review
Regional-to-Local Point-Voxel Transformer
Semantic segmentation of large-scale indoor 3D point cloud scenes is crucial for scene understanding but faces challenges in effectively modeling long-range dependencies and multi-scale features. Researchers present RegionPVT, a novel Regional-to-Local Point-Voxel Transformer that synergistically integrates voxel-based regional self-attention and window-based point-voxel self-attention for concurrent coarse-grained and fine-grained feature learning. The voxel-based regional branch focuses on capturing regional context and facilitating inter-window communication. The window-based point-voxel branch concentrates on local feature learning while integrating voxel-level information within each window.
  • 1.2K
  • 20 Oct 2023
Topic Review
Deep Learning Approaches for Distance Estimation
Visual impairment (VI) is a significant public health concern that affects people of all ages and is caused by a range of factors, including age-related eye diseases, genetic disorders, injuries, and infections. Therefore, governments of different countries are attempting to design various assistive living facilities for individuals with visual impairments. Machine learning techniques have greatly improved object recognition accuracy in computer vision [8]. This has led to the development of sophisticated models that can recognize objects in complex environments. 
  • 1.2K
  • 16 Oct 2023
Topic Review
A Benchmark Dataset for Wearable Low-Light Pedestrian Detection
Detecting pedestrians in low-light conditions is challenging, especially in the context of wearable platforms. Infrared cameras have been employed to enhance detection capabilities, whereas low-light cameras capture the more intricate features of pedestrians. With this in mind, a low-light pedestrian detection (called HRBUST-LLPED) dataset by capturing pedestrian data on campus using wearable low-light cameras is introduced.
  • 1.2K
  • 19 Dec 2023
Topic Review
Machine Learning Methods
Machine learning (ML) has a well-established reputation for successfully enabling automation through its scalable predictive power.
  • 1.2K
  • 15 Nov 2022
Topic Review
AI on Smart City Technologies
As the global population grows, and urbanization becomes more prevalent, cities often struggle to provide convenient, secure, and sustainable lifestyles due to the lack of necessary smart technologies. Fortunately, the Internet of Things (IoT) has emerged as a solution to this challenge by connecting physical objects using electronics, sensors, software, and communication networks. This has transformed smart city infrastructures, introducing various technologies that enhance sustainability, productivity, and comfort for urban dwellers. By leveraging Artificial Intelligence (AI) to analyze the vast amount of IoT data available, new opportunities are emerging to design and manage futuristic smart cities. 
  • 1.2K
  • 09 Jun 2023
Topic Review
Compression of Neural Networks
Researchers propose the value-locality-based compression (VELCRO) algorithm for neural networks. VELCRO is a method to compress general-purpose neural networks that are deployed for a small subset of focused specialized tasks.
  • 1.2K
  • 08 Nov 2021
Topic Review
Deep Anomaly Detection for In-Vehicle Monitoring
Deep learning approaches to the detection of visual data instances that markedly digress from regular sequences have been mostly focusing on outdoor video-surveillance scenarios, mainly regarding abnormal behaviour and suspicious or abandoned object detection. However, with the increasing importance of public and shared transportation for urban mobility, it becomes imperative to provide autonomous intelligent systems capable of detecting abnormal behaviour that threatens passenger safety. In-vehicle monitoring becomes particularly relevant for Shared Autonomous Vehicles, which do not have a driver responsible for assuring the well-being and safety of passengers; such vehicles must be accompanied by reliable autonomous in-vehicle surveillance systems.
  • 1.2K
  • 17 Oct 2022
Topic Review
Deep-Learning-Based Approach to Keystroke-Injection Payload Generation
USB-based keystroke-injection attacks involve manipulating USB devices to inject malicious keystrokes into the target system. These attacks exploit the trust of USB devices and can bypass traditional security measures if they are taken into account and adapted to the systems designed to prevent such attacks. By impersonating a keyboard or using programmable USB devices, attackers can execute unauthorized commands or gain unauthorized access to sensitive information mimicking legitimate user keystrokes. Different attack vectors, such as BadUSB and rogue device attacks, have drawn attention to the potential risks and ramifications involved in these types of attacks. However, the emergence of advanced attack methods necessitates the development of more sophisticated countermeasures. These attacks pose a significant security risk and highlight the importance of implementing strong defenses to mitigate the potential impact of such exploits, especially those that can bypass keystroke dynamics systems using rogue USB devices with implants.
  • 1.2K
  • 17 Jul 2023
Topic Review
Artificial Intelligence-Assisted Programming Tasks
Artificial intelligence (AI)-assisted programming can enable software engineers to work more efficiently and effectively with the existing software tools such as OpenAI ChatGPT, Github Copilot, DeepMind AlphaCode, Amazon Codewhisperer, Replit Ghostwriter, Microsoft IntelliCode and Codedium, especially in situations where complex algorithms are being used that involve large amounts of code (i.e., Big Code regime). It also strikes a balance between productivity and ensuring safety, security, and reliability within the programming development environment. There are two main categories of AI-assisted programming tasks related to software naturalness: generation and understanding. The former includes code generation, code completion, code translation, code refinement, and code summarization. The latter is concerned with understanding code and includes defect detection and clone detection.
  • 1.2K
  • 03 Jul 2023
Topic Review
Internet-of-Things-Based Smart Monitoring System
With technological advancements, smart health monitoring systems are gaining growing importance and popularity. Today, business trends are changing from physical infrastructure to online services. With the restrictions imposed during COVID-19, medical services have been changed. The concepts of smart homes, smart appliances, and smart medical systems have gained popularity. The Internet of Things (IoT) has revolutionized communication and data collection by incorporating smart sensors for data collection from diverse sources.
  • 1.2K
  • 29 May 2023
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