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Topic Review
Indoor Hydroponic Greenhouses
Indoor hydroponic greenhouses are becoming increasingly popular for sustainable food production. On the other hand, precise control of the climate conditions inside these greenhouses is crucial for the success of the crops. Time series deep learning models are adequate for climate predictions in indoor hydroponic greenhouses, but a comparative analysis of these models at different time intervals is needed.
  • 284
  • 26 Jun 2023
Topic Review
An Overview of the User Requirements Notation
Semi-formal software techniques have been very successful in industry, government institutions and other areas such as academia. Arguably, they owe a large part of their success to their graphical notation, which is more human-oriented than their counterpart text-based and formal notation techniques. However, ensuring the consistency between two or more models is one of the known challenges of these techniques.
  • 239
  • 26 Jun 2023
Topic Review
Smartphone Security and Privacy
There is an exponential rise in the use of smartphones in government and private institutions due to business dependencies such as communication, virtual meetings, and access to global information. These smartphones are an attractive target for cybercriminals and are one of the leading causes of cyber espionage and sabotage. A large number of sophisticated malware attacks as well as advanced persistent threats (APTs) have been launched on smartphone users. These attacks are becoming significantly more complex, sophisticated, persistent, and undetected for extended periods. Traditionally, devices are targeted by exploiting a vulnerability in the operating system (OS) or device sensors. Nevertheless, there is a rise in APTs, side-channel attacks, sensor-based attacks, and attacks launched through the Google Play Store.
  • 725
  • 25 Jun 2023
Topic Review
Deep Learning for Alzheimer’s Disease
Alzheimer’s and related diseases are significant health issues of this era. The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. 
  • 261
  • 25 Jun 2023
Topic Review
Foot-Detection Approach Based on Seven-Foot Dimensions
Unsuitable shoe shapes and sizes are a critical reason for unhealthy feet, may severely contribute to chronic injuries such as foot ulcers in susceptible people (e.g., diabetes patients), and thus need accurate measurements in the manner of expert-based procedures.
  • 271
  • 25 Jun 2023
Topic Review Video Peer Reviewed
Geometry-Based Deep Learning in the Natural Sciences
Nature is composed of elements at various spatial scales, ranging from the atomic to the astronomical level. In general, human sensory experience is limited to the mid-range of these spatial scales, in that the scales which represent the world of the very small or very large are generally apart from our sensory experiences. Furthermore, the complexities of Nature and its underlying elements are not tractable nor easily recognized by the traditional forms of human reasoning. Instead, the natural and mathematical sciences have emerged to model the complexities of Nature, leading to knowledge of the physical world. This level of predictiveness far exceeds any mere visual representations as naively formed in the Mind. In particular, geometry has served an outsized role in the mathematical representations of Nature, such as in the explanation of the movement of planets across the night sky. Geometry not only provides a framework for knowledge of the myriad of natural processes, but also as a mechanism for the theoretical understanding of those natural processes not yet observed, leading to visualization, abstraction, and models with insight and explanatory power. Without these tools, human experience would be limited to sensory feedback, which reflects a very small fraction of the properties of objects that exist in the natural world. As a consequence, as taught during the times of antiquity, geometry is essential for forming knowledge and differentiating opinion from true belief. It not only provides a framework for understanding astronomy, classical mechanics, and relativistic physics, but also the morphological evolution of living organisms, along with the complexities of the cognitive systems. Geometry also has a role in the information sciences, where it has explanatory power in visualizing the flow, structure, and organization of information in a system. This role further impacts the explanations of the internals of deep learning systems as developed in the fields of computer science and engineering.
  • 812
  • 21 Jun 2023
Topic Review
Troubleshooting Chatbots Applied to ATM Technical Maintenance Support
The banking industry has been employing artificial intelligence (AI) technologies to enhance the quality of its services. AI algorithms, such as natural language understanding (NLU), have been integrated into chatbots to improve banking applications. 
  • 423
  • 21 Jun 2023
Topic Review
Risk Determination versus Risk Perception
Researchers review the progress in developing a science of interdependence applied to the determinations and perceptions of risk for autonomous human–machine systems based on a case study of the Department of Defense’s (DoD) faulty determination of risk in a drone strike in Afghanistan; the DoD’s assessment was rushed, suppressing alternative risk perceptions.
  • 236
  • 21 Jun 2023
Topic Review
Digital Activism and Social Media Conspiracies During COVID-19
Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was first reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. During this novel outbreak, it has been analyzed that some of social media users used bots to spread fake news and manipulate data about COVID-19.
  • 168
  • 21 Jun 2023
Topic Review
Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots
The ability to sense airborne pollutants with mobile robots provides a valuable asset for domains such as industrial safety and environmental monitoring. Oftentimes, this involves detecting how certain gases are spread out in the environment, commonly referred to as a gas distribution map, to subsequently take actions that depend on the collected information. Since the majority of gas transducers require physical contact with the analyte to sense it, the generation of such a map usually involves slow and laborious data collection from all key locations.
  • 192
  • 20 Jun 2023
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