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Topic Review
Denial of Service Attacks in the Smart Grid
The smart grid is the current energy management and distribution trend: it merges cyber–physical systems (CPS) infrastructure with information and communication technologies (ICT) to ensure efficient power generation, smart energy distribution in real-time, and optimisation. It also allows for greater integration of alternative energy sources such as solar and wind power, which are heavily reliant on weather patterns. Smart grid applications include extraction of business value, smart charging of electric vehicles, smart distribution, generation and storage of energy, grid optimization, grid self-healing with fault protection technology, and many others. Denial-of-Service (DoS) attacks, in particular, have become critical threats to the smart grid because they target the availability of the grid infrastructure and services: in the context of smart grids, this includes both “ensuring timely and reliable access to and use of information” and “ensuring access to enough power”.
  • 1.2K
  • 28 Jan 2023
Topic Review
Human-Computer Interaction System of Talking-Head Generation
Virtual human is widely employed in various industries, including personal assistance, intelligent customer service, and online education, thanks to the rapid development of artificial intelligence. An anthropomorphic digital human can quickly contact people and enhance user experience in human–computer interaction. 
  • 1.2K
  • 12 Jan 2023
Topic Review
ANN in Intelligent Attendance System
Determining the rate of student attendance is an important task in determining the completion of the courses. Despite the success of the technology, it is unfortunate that in many academic institutions, the current systems used to detect student absences. Furthermore, one of the crucial problems in the attendance system does not count student background for continuing in the courses. In this paper, we propose an intelligent approach for calculating student attendance based on their Grade Point Average (GPA) and their activities, this approach uses Artificial Neural Network (ANN) for calculating the attendance rating accurately, meaning the system provide a new rating for each student based on their background. The aim of this research is developing an attendance system for motivation students taking attendance or taking high grade in the class. The result of this approach helps the instructor to allow students who have more activities with more absents to continue in the courses if not the students have low activity should taking high attendance. This system will more efficient for monitoring students for replacing absent to activity.
  • 1.2K
  • 28 Oct 2020
Topic Review
Firewall for Securing Smart Healthcare Environment
Firewalls today represent the first line of defense against major attacks, affecting both traditional and modern networks, and enforcing the protection of inside networks from external (and untrusted) networks. The application of an effective set of security practices and policies may indeed keep those systems safe and save entire businesses. Firewalls have a very important function of protecting, filtering, and controlling all traffic sent and received from the computer, Local Area Network (LAN), or Wide Local Area Network (WLAN) internal networks from unauthorized intrusions or external attacks.
  • 1.2K
  • 08 Oct 2021
Topic Review
Navigation Systems for the Visually Impaired
The visually impaired suffer greatly while moving from one place to another. They face challenges in going outdoors and in protecting themselves from moving and stationary objects, and they also lack confidence due to restricted mobility. Due to the recent rapid rise in the number of visually impaired persons, the development of assistive devices has emerged as a significant research field.
  • 1.2K
  • 07 Nov 2022
Topic Review
AI-Based Wormhole Attack Detection Techniques
The popularity of wireless sensor networks for establishing different communication systems is increasing daily. A wireless network consists of sensors prone to various security threats. These sensor nodes make a wireless network vulnerable to denial-of-service attacks. One of them is a wormhole attack that uses a low latency link between two malicious sensor nodes and affects the routing paths of the entire network. This attack is brutal as it is resistant to many cryptographic schemes and hard to observe within the network. 
  • 1.2K
  • 12 Aug 2022
Topic Review
Machine Learning in Gastroenterology/Endoscopy
Over time, machine learning (ML), a component of artificial intelligence (AI), has been implemented in a variety of medical specialties, such as radiology, pathology, gastroenterology, neurology, obstetrics and gynecology, ophthalmology, and orthopedics, with the goal of improving the quality of healthcare and medical diagnosis. In clinical gastroenterology practice, due to technological developments, estimates show that AI could have the ability to create a predictive model; for instance, it could develop an ML model that can stratify the risk in patients with upper gastrointestinal bleeding, establish the existence of a specific gastrointestinal disease, define the best treatment, and offer prognosis and prediction of the therapeutic response. In this context, by applying ML or deep learning (DL) (AI using neural networks), clinical management in gastroenterology can begin to focus on more personalized treatment centered on the patient and based on making the best individual decisions, instead of relying mostly on guidelines developed for a specific condition. Moreover, the goal of implementing these AI-based algorithms is to increase the possibility of diagnosing a gastrointestinal disease at early stage or the ability to predict the development of a particular condition in advance. Because both AI and gastroenterology encompass many subdomains, the interaction between them might take on various forms. In recent years, we have witnessed a large explosion of research in attempts to improve various fields of gastroenterology, such as endoscopy, hepatology, inflammatory bowel diseases, and many others, with the aid of ML. We also note that, because of the requirement to diagnose more patients with gastrointestinal cancers at an early stage of the disease, which is associated with curative treatment and better prognosis, many studies were developed to address improvement of the detection of these tumors with the aid of AI. The term ML, introduced for the first time in 1959 by Arthur Samuel from the IBM company, refers to an IT domain whereby a computer system can acquire the ability to “learn” by using data without specific programming and can therefore develop a predictive mathematical algorithm based on input data, using recognition of “features”. The ML “model” is subsequently able to adapt to new situations in which it becomes able to predict and make decisions.
  • 1.2K
  • 02 Feb 2021
Topic Review
Rain Fade Models
Developing a rain fade model involves mathematical analysis of rain attenuation phenomena by reasoning and cause-based interaction.
  • 1.2K
  • 27 May 2021
Topic Review Video
Metaverse-Related Technologies and Applications
The definition of the Metaverse is a virtual space where users can interact with one another, and with their environment, via 3D digital objects and virtual avatars, in a complex manner that mimics the real world, holding things developed using artificial intelligence techniques; therefore, creating digital humans is essential to the development of the Metaverse and other Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR) applications.
  • 1.2K
  • 05 Feb 2024
Topic Review Peer Reviewed
Large Language Models and Logical Reasoning
In deep learning, large language models are typically trained on data from a corpus as representative of current knowledge. However, natural language is not an ideal form for the reliable communication of concepts. Instead, formal logical statements are preferable since they are subject to verifiability, reliability, and applicability. Another reason for this preference is that natural language is not designed for an efficient and reliable flow of information and knowledge, but is instead designed as an evolutionary adaptation as formed from a prior set of natural constraints. As a formally structured language, logical statements are also more interpretable. They may be informally constructed in the form of a natural language statement, but a formalized logical statement is expected to follow a stricter set of rules, such as with the use of symbols for representing the logic-based operators that connect multiple simple statements and form verifiable propositions.
  • 1.2K
  • 31 May 2023
Topic Review
Journalistic Knowledge Platform
A Journalistic Knowledge Platform (JKP) is an information system that employ artificial intelligence and big data techniques such as machine learning and knowledge graphs to manage and support the knowledge work needed in all stages of news production. JKPs automate the process of annotating metadata and support daily workflows like news production, archiving, monitoring, management and distribution. JKPs harvest and analyse news and social media information over the net in real time, leverage encyclopaedic sources, and provide journalists with both meaningful background knowledge and newsworthy information. JKPs can provide a digitalisation path towards reduced production costs and improved information quality while adapting the current workflows of newsrooms to new forms of journalism and readers’ demands.
  • 1.2K
  • 20 Jun 2022
Topic Review
Rainfall Prediction System
Rainfall prediction is one of the challenging tasks in weather forecasting process. Accurate rainfall prediction is now more difficult than before due to the extreme climate variations.
  • 1.2K
  • 18 May 2022
Topic Review
Multi-Omics Model for Cancer Genetics
In the coming age of omics technologies, next gen sequencing, proteomics, metabolomics, and other high throughput techniques will become the usual tools in biomedical cancer research. However, their integrative approach is not trivial due to the broad diversity of data types, dynamic ranges and sources of experimental and analytical errors characteristic of each omics.
  • 1.2K
  • 02 Jun 2021
Topic Review
Singing Voice Detection
Singing voice detection or vocal detection is a classification task that determines whether there is a singing voice in a given audio segment. This process is a crucial preprocessing step that can improve the performance of other tasks such as automatic lyrics alignment, singing melody transcription, singing voice separation, vocal melody extraction, and many more.
  • 1.2K
  • 25 Jan 2022
Topic Review
Machine Learning in Cereal Crops Disease Detection
Cereals are an important and major source of the human diet. They constitute more than two-thirds of the world’s food source and cover more than 56% of the world’s cultivatable land. These important sources of food are affected by a variety of damaging diseases, causing significant loss in annual production. In this regard, detection of diseases at an early stage and quantification of the severity has acquired the urgent attention of researchers worldwide. One emerging and popular approach for this task is the utilization of machine learning techniques.
  • 1.2K
  • 03 Mar 2022
Topic Review
Resource Allocation Schemes for 5G Network
Resource allocation is an important aspect of any cellular network environment. It plays a significant part in maintaining friendly access for end-users, business partners, and customers of cellular-based applications. Resource allocation has great benefits for the cellular network environment.
  • 1.2K
  • 21 Oct 2021
Topic Review
Efficient Real-Time Decision Making in IoT
Efficient Real-Time Decision Making in IoT(the Internet of Things) is about using real-time sensor data, using fresh sensor data that represent the current real-world status to minimize.          
  • 1.2K
  • 09 Feb 2022
Topic Review
Artificial Intelligent in Education
The application of Artificial Intelligence or AI in education has been the subject of academic research. The field examines learning wherever it occurs, in traditional classrooms or at workplaces so to support formal education and lifelong learning. It combines interdisciplinary AI and learning sciences (such as education, psychology, neuroscience, linguistics, sociology and anthropology) in order to facilitate the development of effective adaptive learning environments and various flexible, inclusive tools. Nowadays, there are several new challenges in the field of education technology in the era of smart phones, tablets, cloud computing, Big Data, etc., whose current research questions focus on concepts such as ICT-enabled personalized learning, mobile learning, educational games, collaborative learning on social media, MOOCs, augmented reality application in education and so on. Therefore, to meet these new challenges in education, several fields of research using AI have emerged over time to improve teaching and learning using digital technologies.
  • 1.2K
  • 03 Mar 2022
Topic Review
Multimedia Steganalysis
Steganography techniques aim to hide the existence of secret messages in an innocent-looking medium, where the medium before and after embedding looks symmetric. Steganalysis techniques aim to breach steganography techniques and detect the presence of invisible messages. 
  • 1.2K
  • 08 Feb 2022
Topic Review
Three-Dimensional Printing
Additive manufacturing with an emphasis on 3D printing has recently become popular due to its exceptional advantages over conventional manufacturing processes. However, 3D printing process parameters are challenging to optimize, as they influence the properties and usage time of printed parts. Therefore, it is a complex task to develop a correlation between process parameters and printed parts’ properties via traditional optimization methods. A machine-learning technique was recently validated to carry out intricate pattern identification and develop a deterministic relationship, eliminating the need to develop and solve physical models. In machine learning, artificial neural network (ANN) is the most widely utilized model, owing to its capability to solve large datasets and strong computational supremacy.
  • 1.2K
  • 17 Feb 2021
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