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Topic Review
The Dichotomy of Neural Networks and Cryptography
Neural networks and cryptographic schemes have come together in war and peace; a cross-impact that forms a dichotomy deserving a comprehensive review study. Neural networks can be used against cryptosystems; they can play roles in cryptanalysis and attacks against encryption algorithms and encrypted data. This side of the dichotomy can be interpreted as a war declared by neural networks. On the other hand, neural networks and cryptographic algorithms can mutually support each other. Neural networks can help improve the performance and the security of cryptosystems, and encryption techniques can support the confidentiality of neural networks. The latter side of the dichotomy can be referred to as the peace. 
  • 1.1K
  • 07 Jul 2022
Topic Review
Wireless Sensor Networks with Mobile Sink
With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications.
  • 1.1K
  • 05 Jan 2023
Topic Review
AUV Adaptive Sampling Methods
Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced.
  • 1.1K
  • 12 Nov 2020
Topic Review
Swarm Intelligence Based Load Balancing Techniques
Swarm Intelligence aims to combine relatively high approximate techniques to guide local optimization strategies in order to explore a solution space successfully and efficiently.
  • 1.1K
  • 28 Mar 2022
Topic Review
Compressive Sensing in Image/Video Compression
Compressive Sensing (CS) has emerged as a transformative technique in image compression, offering innovative solutions to challenges in efficient signal representation and acquisition. 
  • 1.1K
  • 08 Feb 2024
Topic Review
Deep-Learning-Based Approach to Keystroke-Injection Payload Generation
USB-based keystroke-injection attacks involve manipulating USB devices to inject malicious keystrokes into the target system. These attacks exploit the trust of USB devices and can bypass traditional security measures if they are taken into account and adapted to the systems designed to prevent such attacks. By impersonating a keyboard or using programmable USB devices, attackers can execute unauthorized commands or gain unauthorized access to sensitive information mimicking legitimate user keystrokes. Different attack vectors, such as BadUSB and rogue device attacks, have drawn attention to the potential risks and ramifications involved in these types of attacks. However, the emergence of advanced attack methods necessitates the development of more sophisticated countermeasures. These attacks pose a significant security risk and highlight the importance of implementing strong defenses to mitigate the potential impact of such exploits, especially those that can bypass keystroke dynamics systems using rogue USB devices with implants.
  • 1.1K
  • 17 Jul 2023
Topic Review
Stock Market Prediction Using Deep Reinforcement Learning
Stock market investment, a cornerstone of global business, has experienced unprecedented growth, becoming a lucrative, yet complex field. Predictive models, powered by cutting-edge technologies like artificial intelligence (AI), sentiment analysis, and machine learning algorithms, have emerged to guide investors in their decision-making processes.
  • 1.1K
  • 22 Nov 2023
Topic Review
Time-Series Forecasting Models
The time-series forecasting method is a suitable pricing solution for Digital Signage Advertising (DSA), as it improves the pricing decision by modeling the changes in the environmental factors and audience attention level toward signage for optimal pricing. However, it is difficult to determine an optimal price forecasting model for DSA with the increasing number of available time-series forecasting models in recent years. Based on the 84 research articles reviewed, the data characteristics analysis in terms of linearity, stationarity, volatility, and dataset size is helpful in determining the optimal model for time-series price forecasting.
  • 1.1K
  • 03 Nov 2021
Topic Review
Cloud Computing Failure Prediction
To date, despite the significant improvement in the performance of the hardware elements of the cloud infrastructure, the failure rate remains substantial. Moreover, the cloud is not as reliable as the cloud service providers, such as Amazon AWS and Ali Cloud, claimed, which is more than 99.9%. For example, multiple instances of failure have been reported, such as the failure of Amazon’s cloud data servers in early October 2012, which resulted in the collapse of Reddit, Airbnb, and Flipboard, the loss of Amazon AWS S3 on 28 February 2017, and the crash of Microsoft cloud services on 22 March 2017. Such failures show that cloud service providers are not as reliable as they claim.
  • 1.1K
  • 06 Apr 2022
Topic Review
Balanced Learning for Road Crack Segmentation
Road crack segmentation based on high-resolution images is an important task in road service maintenance. The undamaged road surface area is much larger than the damaged area on a highway. This imbalanced situation yields poor road crack segmentation performance for convolutional neural networks.
  • 1.1K
  • 22 Jul 2022
Topic Review
Contextual Route Recommendation System
The traffic composition in developing countries comprises of variety of vehicles which include cars, buses, trucks, and motorcycles. Motorcycles dominate the road with 77.5% compared to other types. Meanwhile, route recommendation such as navigation and Advanced Driver Assistance Systems (ADAS) is limited to particular vehicles only. Traffic condition prediction aims to discuss the proper method to result a better prediction analysis. Route recommendation aims to explore the existing work on how to provide the best route for users. The two domains would be the parts of our framework to result contextual route recommendations in heterogeneous traffic flow.
  • 1.1K
  • 28 Mar 2022
Topic Review
Sustainable Food Production
Fault diagnosis and prognosis methods are the most useful tools for risk and reliability analysis in food processing systems. Proactive diagnosis techniques such as failure mode and effect analysis (FMEA) are important for detecting all probable failures and facilitating the risk analysis process. However, significant uncertainties exist in the classical-FMEA when it comes to ranking the risk priority numbers (RPNs) of failure modes. Such uncertainties may have an impact on the food sector’s operational safety and maintenance decisions.
  • 1.1K
  • 28 Mar 2022
Topic Review
Using Colored Petri Net for Accounting System
Many learners who are not familiar with the accounting terms find blended learning very complex to understand with respect to the computerized accounting system, the journal entries process, and tracing the accounting transaction flows of accounting system. A simulation-based model is a viable option to help instructors and learners make understanding the accounting system components and monitoring the accounting transactions easier. This entry briefly introduce a colored Petri net (CPN)-based model.
  • 1.1K
  • 28 Mar 2022
Topic Review
Machine Learning Used to Combat COVID-19
Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19.
  • 1.1K
  • 20 Sep 2022
Topic Review
Remote Keyless Using Pre-Trained Deep Neural Network
Keyless systems have replaced the old-fashioned methods of inserting physical keys into keyholes to unlock the door, which are inconvenient and easily exploited by threat actors. Keyless systems use the technology of radio frequency (RF) as an interface to transmit signals from the key fob to the vehicle.
  • 1.1K
  • 10 Nov 2022
Topic Review
Energy Consumption Patterns in Urban Buildings
Energy has been one of the most important topics of political and social discussion in recent decades. A significant proportion of the country’s revenues is derived from energy resources, making it one of the most important and strategic macro policy and sustainable development areas. Energy demand modeling is one of the essential strategies for better managing the energy sector and developing appropriate policies to increase productivity. With the increasing global demand for energy, it is necessary to develop intelligent forecasting methods and algorithms. Different economic and non-economic indicators can be used to estimate the energy demand, including linear and non-linear statistical methods, mathematics, and simulation models.
  • 1.1K
  • 28 Apr 2022
Topic Review
Background of Machine/Deep Learning Approaches on Mental Health
Mental health can be seen as a person’s emotional, psychological, and social well-being. It can be harmed by various mental health conditions, which negatively influence a person’s intellectual capacity, emotions, and social relationships. Machine learning (ML) is a subfield of artificial intelligence (AI) that deals with three problems: classification, regression, and clustering. It utilizes data and algorithms to mimic how people learn while progressively improving accuracy in various tasks.
  • 1.1K
  • 08 Feb 2023
Topic Review
Artificial Intelligence in Alzheimer’s Disease
Alzheimer’s disease (AD) represents most of the dementia cases and stands as the most common neurodegenerative disease. A shift from a curative to a preventive approach is imminent, and we are moving towards the application of personalized medicine, whereas we can shape the best clinical intervention for each patient at a given point. This new step in medicine requires the most recent tools and the analysis of huge amounts of data where the application of artificial intelligence (AI) plays a critical part in the depiction of disease-patient dynamics, critical to reach early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. 
  • 1.1K
  • 02 Mar 2022
Topic Review
Universal Functions Originator
Universal Functions Originator, or just UFO, is a new multi-purpose machine learning (ML) computing system that explains everything as pure mathematical equations. These expressions could be simple or highly complicated linear/nonlinear equations. Although the purpose of this technique is similar to that of classical symbolic regression (SR) algorithms, UFO works differently and it has its own mechanism, search space, and building strategy. For example, in UFO, each equation term (of intercepts, weights, exponents, arithmetic operators, and analytic functions) has its own search space and cannot be mixed with others. Also, UFO can be executed by any optimization algorithm, while SR algorithms require some special tree-based optimization algorithms; like genetic programming (GP).
  • 1.1K
  • 24 Oct 2022
Topic Review
Deep Learning in Water Leak Detection
The escalating global water usage and the increasing strain on major cities due to water shortages highlights the critical need for efficient water management practices. In water-stressed regions worldwide, significant water wastage is primarily attributed to leakages, inefficient use, and aging infrastructure. Undetected water leakages in buildings’ pipelines contribute to the water waste problem. 
  • 1.1K
  • 22 Nov 2023
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