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Topic Review
AI-Supported Programming Tasks
AI-assisted programming or development is defined as the utilization of machine learning models trained on the vast amount of available source code. Its purpose is to support various aspects of programming and, more broadly, software engineering implementation tasks. 
  • 154
  • 19 Feb 2024
Topic Review Peer Reviewed
Optimisation of Small-Scale Aquaponics Systems Using Artificial Intelligence and the IoT: Current Status, Challenges, and Opportunities
Environment changes, water scarcity, soil depletion, and urbanisation are making it harder to produce food using traditional methods in various regions and countries. Aquaponics is emerging as a sustainable food production system that produces fish and plants in a closed-loop system. Aquaponics is not dependent on soil or external environmental factors. It uses fish waste to fertilise plants and can save up to 90–95% water. Aquaponics is an innovative system for growing food and is expected to be very promising, but it has its challenges. It is a complex ecosystem that requires multidisciplinary knowledge, proper monitoring of all crucial parameters, and high maintenance and initial investment costs to build the system. Artificial intelligence (AI) and the Internet of Things (IoT) are key technologies that can overcome these challenges. Numerous recent studies focus on the use of AI and the IoT to automate the process, improve efficiency and reliability, provide better management, and reduce operating costs. However, these studies often focus on limited aspects of the system, each considering different domains and parameters of the aquaponics system. This paper aims to consolidate the existing work, identify the state-of-the-art use of the IoT and AI, explore the key parameters affecting growth, analyse the sensing and communication technologies employed, highlight the research gaps in this field, and suggest future research directions. Based on the reviewed research, energy efficiency and economic viability were found to be a major bottleneck of current systems. Moreover, inconsistencies in sensor selection, lack of publicly available data, and the reproducibility of existing work were common issues among the studies.
  • 354
  • 19 Feb 2024
Topic Review
Deep Learning Approach for Lung Cancer Diagnosis
Deep learning has emerged as a powerful tool for medical image analysis and diagnosis, demonstrating high performance on tasks such as cancer detection. As deep learning techniques continue to revolutionize the field of medical imaging, researchers have increasingly turned to large-scale databases to train and validate their algorithms. Many studies have been done to diagnose lung cancer using different datasets, both public and private. Each dataset has its own unique characteristics and challenges.
  • 256
  • 18 Feb 2024
Topic Review
Digital Twins in the Software Industry
Digital twins are a powerful consequence of digital transformation. In fact, they have been applied to many industries to enhance operations, predict needs, improve decision making, or optimize performance, even though the definition of digital twins is still evolving. Digital twins are already influencing and will significantly affect the software industry, revolutionizing various aspects of the software development lifecycle. 
  • 276
  • 18 Feb 2024
Topic Review
Commit Representations for JIT Vulnerability Prediction
Software systems are becoming increasingly complex and interdependent, with thousands of lines of code being added and modified daily. As a result, software vulnerabilities are becoming more prevalent and pose a significant threat to the security and reliability of software systems. With the evolution of software systems, their size and complexity are rising rapidly. Identifying vulnerabilities as early as possible is crucial for ensuring high software quality and security. Just-in-time (JIT) vulnerability prediction, which aims to find vulnerabilities at the time of commit, has increasingly become a focus of attention. 
  • 86
  • 18 Feb 2024
Topic Review
Dynamic Feedback-Driven Learning Optimization Framework
A novel approach named the Dynamic Feedback-Driven Learning Optimization Framework (DFDLOF), aimed at personalizing educational pathways through machine learning technology.
  • 170
  • 18 Feb 2024
Topic Review
Home Security and Automation with Voice Commands
With the rapid rise of digitalization in the global economy, home security systems have become increasingly important for personal comfort and property protection. The collaboration between humans, the Internet of Things (IoT), and smart homes can be highly efficient. Interaction considers convenience, efficiency, security, responsiveness, and automation.
  • 174
  • 18 Feb 2024
Topic Review
Encoder–Decoder Architecture and Kernel-Sharing Mechanism
As the application of unmanned aerial vehicles (UAVs) becomes more and more widespread, accidents such as accidental injuries to personnel, property damage, and loss and destruction of UAVs due to accidental UAV crashes also occur in daily use scenarios. To reduce the occurrence of such accidents, UAVs need to have the ability to autonomously choose a safe area to land in an accidental situation, and the key lies in realizing on-board real-time semantic segmentation processing.
  • 175
  • 18 Feb 2024
Topic Review
Ontological Modeling and Clustering Techniques for Service Allocation
In complex distributed IoT-based applications, multiple and heterogeneous IoT devices are deployed in a given environment. Those devices typically act as information input providers (e.g., sensor networks) or actuators. Edge computing arose as a solution to reduce the high demand for data traffic between IoT devices and the cloud that processes them. Moreover, several notions have been introduced to shape the gap between the cloud and edge, like fog or mist computing.
  • 111
  • 18 Feb 2024
Topic Review
Standards for Health Data Systems
The COVID-19 pandemic has highlighted the necessity for agile health services that enable reliable and secure information exchange, but achieving proper, private, and secure sharing of electronic medical records (EMRs) remains a challenge due to diverse data formats and fragmented records across multiple data silos, resulting in hindered coordination between healthcare teams, potential medical errors, and delays in patient care.
  • 115
  • 18 Feb 2024
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