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Topic Review
Identifying Key Issues in Climate Change Litigation
As climate change, environmental, social, and governance (ESG), along with sustainability, become increasingly crucial for businesses and society, there is a noticeable scarcity of information and transparency regarding corporate practices. Often, government agency enforcement actions lead to litigation and are ultimately resolved by court decisions. Moreover, in instances when there is perceived inadequacy in government enforcement, citizens frequently turn to the courts for preventive judgments against businesses or agencies.
  • 146
  • 21 Dec 2023
Topic Review
Machine Learning and Deep Learning Techniques
The rapid growth of e-commerce has significantly increased the demand for advanced techniques to address specific tasks in the e-commerce field.
  • 149
  • 21 Dec 2023
Topic Review
Memristor-Based Spiking Artificial Neural Networks
Arrays of memristive devices coupled with photosensors can be used for capturing and processing visual information, thereby realizing the concept of “in-sensor computing”. This is a promising concept associated with the development of compact and low-power machine vision devices, which is crucial important for bionic prostheses of eyes, on-board image recognition systems for unmanned vehicles, computer vision in robotics, etc. This concept can be applied for the creation of a memristor based neuromorphic analog machine vision systems.
  • 136
  • 21 Dec 2023
Topic Review
Multimodal Biometric Identification System
In the past two decades, many physical and behavioral biometric modalities have been under extensive research, such as fingerprints, palm prints, palms/Finger Textures, faces, irises, voice, gait and signature. All these modalities are vulnerable to presentation spoof attacks; hence, the level of provided security is compromised. Fingerprint- and palm-print-based biometric systems may be deceived by using gelatin or clay-made artificial fingerprint surfaces or images. Biometric systems using faces as a biometric modality may be attacked by using photographs, 3-D face models and recorded short clips. Iris-based biometric systems may encounter spoof attacks by employing iris images taken from enrolled users. Voice- and gait-based biometric systems may be attacked by feeding prerecorded audio and video to the recognition system, respectively. 
  • 192
  • 21 Dec 2023
Topic Review
Machine Learning for Software-Defined Networking-Based Intrusion Detection
Low-speed internet can negatively impact incident response by causing delayed detection, ineffective response, poor collaboration, inaccurate analysis, and increased risk. Slow internet speeds can delay the receipt and analysis of data, making it difficult for security teams to access the relevant information and take action, leading to a fragmented and inadequate response. All of these factors can increase the risk of data breaches and other security incidents and their impact on IoT-enabled communication.
  • 159
  • 21 Dec 2023
Topic Review
Recommendation Systems for e-Shopping
The interest in recommendation systems (RSs) has dramatically increased, as they have become main components of all online stores. The aims of an RS can be multifaceted, related not only to the increase in sales or the convenience of the customer, but may include the promotion of alternative environmentally friendly products or to strengthen policies and campaigns. In addition to accurate suggestions, important aspects of contemporary RSs are therefore to align with the particular marketing goals of the e-shop and with the stances of the targeted audience, ensuring user acceptance, satisfaction, high impact, and achieving sustained usage by customers.
  • 207
  • 21 Dec 2023
Topic Review
Data Completeness and Imputation Methods on Supervised Classifiers
Data completeness is one of the most common challenges that hinder the performance of data analytics platforms. Different studies have assessed the effect of missing values on different classification models based on a single evaluation metric, namely, accuracy. However, accuracy on its own is a misleading measure of classifier performance because it does not consider unbalanced datasets.
  • 153
  • 21 Dec 2023
Topic Review
Quality of OpenStreetMap Data
OpenStreetMap (OSM) is a potential source of geospatial open data for monitoring sustainable development goals (SDG) indicators. Improving the quality of these crowdsourcing data has significant implications for monitoring and achieving SDGs, such as zero hunger, sustainable cities, ensuring tenure security, and preserving biodiversity. The quality of OpenStreetMap (OSM) has been widely concerned as a valuable source for monitoring some sustainable development goals (SDG) indicators. Improving its semantic quality is still challenging. As a kind of solution, road type prediction plays an important role. However, most existing algorithms show low accuracy, owing to data sparseness and inaccurate description. 
  • 158
  • 19 Dec 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.
  • 242
  • 19 Dec 2023
Topic Review
Diabetic Retinopathy Detection by Deep-Learning Technique
Medical professionals can benefit greatly from deep-learning-based systems that automate the interpretation of retinal pictures and provide objective and consistent assessments of the severity of diabetic retinopathy (DR). Deep-learning (DL)-based screening methods can test a large diabetic population for DR. Deep-learning algorithms can monitor the course of diseases over time by evaluating successive retinal images.
  • 138
  • 19 Dec 2023
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