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Topic Review
Artificial Neural Networks for Navigation Systems
Several machine learning (ML) methodologies are gaining popularity as artificial intelligence (AI) becomes increasingly prevalent. An artificial neural network (ANN) may be used as a “black-box” modeling strategy without the need for a detailed system physical model. It is more reasonable to solely use the input and output data to explain the system’s actions. ANNs have been extensively researched, as artificial intelligence has progressed to enhance navigation performance. In some circumstances, the Global Navigation Satellite System (GNSS) can offer consistent and dependable navigational options. A key advancement in contemporary navigation is the fusion of the GNSS and inertial navigation system (INS). Numerous strategies have been put out to increase the accuracy for jamming, GNSS-prohibited environments, the integration of GNSS/INS or other technologies by means of a Kalman filter as well as to solve the signal blockage issue in metropolitan areas. A neural-network-based fusion approach is suggested to address GNSS outages. 
  • 1.0K
  • 21 Apr 2023
Topic Review
Deep Learning Algorithms in Agriculture
The field of agriculture is one of the most important fields in which the application of deep learning still needs to be explored, as it has a direct impact on human well-being. In particular, there is a need to explore how deep learning models can be used as a tool for optimal planting, land use, yield improvement, production/disease/pest control, and other activities. The vast amount of data received from sensors in smart farms makes it possible to use deep learning as a model for decision-making in this field. In agriculture, no two environments are exactly alike, which makes testing, validating, and successfully implementing such technologies much more complex than in most other industries. 
  • 1.0K
  • 18 Mar 2022
Topic Review
Explainable Artificial Intelligence for Smart Cities
The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans and envisioned the concept of smart cities using informed actions, enhanced user interpretations and explanations, and firm decision-making processes. The XAI systems can unbox the potential of black-box AI models and describe them explicitly.
  • 1.0K
  • 19 Apr 2023
Topic Review
Models for Evaluation Intrusion Detection Systems in IoT
Using the Internet of Things (IoT) for various applications, such as home and wearables devices, network applications, and even self-driven vehicles, detecting abnormal traffic is one of the problematic areas for researchers to protect network infrastructure from adversary activities. Several network systems suffer from drawbacks that allow intruders to use malicious traffic to obtain unauthorized access. Attacks such as Distributed Denial of Service attacks (DDoS), Denial of Service attacks (DoS), and Service Scans demand a unique automatic system capable of identifying traffic abnormality at the earliest stage to avoid system damage. Numerous automatic approaches can detect abnormal traffic. However, accuracy is not only the issue with current Intrusion Detection Systems (IDS), but the efficiency, flexibility, and scalability need to be enhanced to detect attack traffic from various IoT networks. 
  • 1.0K
  • 27 May 2022
Topic Review
Risk Analysis of Engineering Procurement and Construction
The lump sum turn key (LSTK) contract for engineering, procurement, and construction (EPC) projects is a typical contract type used in large-scale and complex plant projects. 
  • 1.0K
  • 21 Jun 2022
Topic Review
NNetEn Entropy
NNetEn is the first entropy measure that is based on artificial intelligence methods. The method modifies the structure of the LogNNet classification model so that the classification accuracy of the MNIST-10 digits dataset indicates the degree of complexity of a given time series. The calculation results of the proposed model are similar to those of existing methods, while the model structure is completely different and provides considerable advantages.
  • 999
  • 19 Jun 2023
Topic Review
Homomorphic Encryption for Privacy-Preserving Biometrics
The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics.
  • 998
  • 16 Jun 2023
Topic Review
Impact of Artificial Intelligence on Dental Education
Most dental educators have limited knowledge and skills to assess AI applications, as they were not trained to do so. Also, AI technology has evolved exponentially. Factual reliability and opportunities with OpenAI Inc.’s ChatGPT are considered critical inflection points in the era of generative AI. Updating curricula at dental institutions is inevitable as advanced deep-learning approaches take over the clinical areas of dentistry and reshape diagnostics, treatment planning, management, and telemedicine screening. With advances in AI language models, communication with patients will change, and the foundations of dental education, including essay, thesis, or scientific paper writing, will need to adapt. However, there is a growing concern about its ethical and legal implications, and further consensus is needed for the safe and responsible implementation of AI in dental education.
  • 987
  • 20 Feb 2023
Topic Review
Vision-Based Autonomous Vehicle Systems
Autonomous vehicle systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. Deep learning is fast becoming a successful alternative approach for perception-based AVS as it reduces both cost and dependency on sensor fusion.
  • 982
  • 12 Jul 2022
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.
  • 979
  • 21 Jun 2023
Topic Review
Re-Identification in Urban Scenarios
Multi-object Re-Identification (ReID), based on a wide range of surveillance cameras, is nowadays a vital aspect in modern cities, to better understand city movement patterns among the different infrastructures, with the primary intention of rapidly mitigate abnormal situations, such as tracking car thieves, wanted persons, or even lost children. Given an image or video of an object-of-interest (query), object identification aims to identify the object from images or video feed taken from different cameras. 
  • 978
  • 24 Feb 2022
Topic Review
Natural Language Processing for the COVID-19 Pandemic
The COVID-19 pandemic is the most devastating public health crisis and has affected the lives of billions of people worldwide in unprecedented ways. Compared to pandemics of this scale in the past, societies are now equipped with advanced technologies that can mitigate the impacts of pandemics if utilized appropriately. However, opportunities are not fully utilized, particularly at the intersection of data science and health. Health-related big data and technological advances have the potential to significantly aid the fight against such pandemics, including the pandemic’s ongoing and long-term impacts. Specifically, the field of natural language processing (NLP) has enormous potential at a time when vast amounts of text-based data are continuously generated from a multitude of sources, such as health/hospital systems, published medical literature, and social media. Effectively mitigating the impacts of the pandemic requires tackling challenges associated with the application and deployment of NLP systems.
  • 978
  • 24 Nov 2022
Topic Review
Impact of Artificial Intelligence on the Job Market
This research explores the impact of artificial intelligence (AI) on the job market, including both its potential benefits and drawbacks. The research discusses how AI can automate repetitive tasks, improve accuracy, and assist workers in performing their jobs more effectively. However, the article also highlights concerns about job displacement, biases and discrimination, and the deskilling of workers. The research examines the impact of AI on different industries and types of jobs and discusses the need for workers to develop complementary skills and for employers to invest in AI technologies that work collaboratively with human workers. The research concludes by highlighting the importance of investing in education and training programs, ensuring ethical and transparent development and deployment of AI, and implementing appropriate policies to support workers who are displaced by AI.
  • 975
  • 22 May 2023
Topic Review
Solubility and Aggregation of Proteins
Protein solubility is based on the compatibility of the specific protein surface with the polar aquatic environment. The exposure of polar residues to the protein surface promotes the protein’s solubility in the polar environment. The application of 3D GAuss function allows identification of accordant/discordant regions in proteis. The discordant ones usually represent the localisation of biological activity. 
  • 974
  • 11 Oct 2021
Topic Review
Pothole Detection
Many datasets used to train artificial intelligence systems to recognize potholes, such as the challenging sequences for autonomous driving (CCSAD) and the Pacific Northwest road (PNW) datasets, do not produce satisfactory results. This is due to the fact that these datasets present complex but realistic scenarios of pothole detection tasks than popularly used datasets that achieve better results but do not effectively represents realistic pothole detection task. In an attempt to improve the detection accuracy of the pothole object detection problems, researchers have proposed varieties of object detection methods enhanced with super-resolution (SR) techniques that are employed to generate an enhanced image from a low-resolution image before performing object detection.
  • 973
  • 24 Jun 2022
Topic Review
Network Threat Detection with ML/DL in SDN-Based Platforms
A revolution in network technology has been ushered in by software defined networking (SDN), which makes it possible to control the network from a central location and provides an overview of the network’s security. Despite this, SDN has a single point of failure that increases the risk of potential threats. Network intrusion detection systems (NIDS) prevent intrusions into a network and preserve the network’s integrity, availability, and confidentiality. Much work has been done on NIDS but there are still improvements needed in reducing false alarms and increasing threat detection accuracy. Advanced approaches such as deep learning (DL) and machine learning (ML) have been implemented in SDN-based NIDS to overcome the security issues within a network.
  • 971
  • 14 Nov 2022
Topic Review
Concept of the Robo-Advisor with Digital Twin
The term “digital twin” (DT) refers to a digital representation of an individual that has the capability of integrating any digital data with virtually real-time data and generating advanced analytics for feedback, recommendation, and alternative solutions for users. 
  • 969
  • 11 May 2022
Topic Review
Machine Learning and Image Processing
Images constitute one of the most important forms of communication used by society and contain a large amount of important information. The human vision system is usually the first form of contact with media and has the ability to naturally extract important, and sometimes subtle, information, enabling the execution of different tasks, from the simplest, such as identifying objects, to the more complex, such as the creation and integration of knowledge. However, this system is limited to the visible range of the electromagnetic spectrum. On the contrary, computer systems have a more comprehensive coverage capacity, ranging from gamma to radio waves, which makes it possible to process a wide spectrum of images, covering a wide and varied field of applications. On the other hand, the exponential growth in the volume of images created and stored daily makes their analysis and processing a difficult task to implement outside the technological sphere. In this way, image processing through computational systems plays a fundamental role in extracting necessary and relevant information for carrying out different tasks in different contexts and application areas.
  • 968
  • 17 Oct 2023
Topic Review
Embedded Machine Learning
Embedded machine learning (EML) can be applied in the areas of accurate computer vision schemes, reliable speech recognition, innovative healthcare, robotics, and more. However, there exists a critical drawback in the efficient implementation of ML algorithms targeting embedded applications. Machine learning algorithms are generally computationally and memory intensive, making them unsuitable for resource-constrained environments such as embedded and mobile devices. In order to efficiently implement these compute and memory-intensive algorithms within the embedded and mobile computing space, innovative optimization techniques are required at the algorithm and hardware levels. 
  • 967
  • 01 Nov 2021
Topic Review
Edge Artificial Intelligence
Artificial Intelligence (Al) models are being produced and used to solve a variety of current and future business and technical problems. Therefore, AI model engineering processes, platforms, and products are acquiring special significance across industry verticals. For achieving deeper automation, the number of data features being used while generating highly promising and productive AI models is numerous, and hence the resulting AI models are bulky. Such heavyweight models consume a lot of computation, storage, networking, and energy resources. On the other side, increasingly, AI models are being deployed in IoT devices to ensure real-time knowledge discovery and dissemination. 
  • 966
  • 09 Feb 2023
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