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Topic Review
Ransomware Detection, Avoidance, and Mitigation Scheme
Ransomware attacks have emerged as a major cyber-security threat wherein user data is encrypted upon system infection. Latest Ransomware strands using advanced obfuscation techniques along with offline C2 Server capabilities are hitting Individual users and big corporations alike. This problem has caused business disruption and, of course, financial loss. 
  • 1.1K
  • 13 Jan 2022
Topic Review
Determination of the Live Weight of Farm Animals
In cattle breeding, regularly taking the animals to the scale and recording their weight is important for both the performance of the enterprise and the health of the animals. This process, which must be carried out in businesses, is a difficult task. Due to the drawbacks of direct measurement approaches, a variety of indirect measurement approaches have been proposed.
  • 1.1K
  • 26 Jul 2023
Topic Review
Finger-Vein-Based Identity Recognition
Finger vein recognition is a relatively new method of biometric authentication. It matches the vascular pattern in an individual’s finger to previously obtained data.
  • 1.1K
  • 19 May 2021
Topic Review
Simulators in Educational Robotics
Simulators are part of educational robotics, which easily and quickly enable the user to engage virtually with the development and programming of robots through GUIs. Using a simulator means that it is not necessary to deal exclusively with real robots that might have a significant cost. Hence, simulators are a useful tool that might save resources and assist the educational process.
  • 1.1K
  • 18 Mar 2021
Topic Review
Semantic Trajectory and Recommender Systems in Cultural Spaces
Semantic trajectories can efficiently model human movement for further analysis and pattern recognition, while personalised recommender systems can adapt to constantly changing user needs and provide meaningful and optimised suggestions. 
  • 1.1K
  • 22 Dec 2021
Topic Review
AI and Time Management: Boosting Productivity and Efficiency
In today's fast-paced world, time is a precious resource that needs to be managed efficiently to achieve maximum productivity. Artificial intelligence (AI) has emerged as a game-changer in this regard, providing individuals and institutions with powerful tools to optimize their time management. The research explores the various ways in which AI is helping individuals and institutions to boost their productivity and efficiency through better time management. The AI-based productivity tools, automated time tracking, predictive analytics, and personalized time management, highlighting the benefits and potential limitations of each approach were discussed.
  • 1.1K
  • 22 May 2023
Topic Review
Food-Waste-Reduction Based on IoT and Big Data
IoT technology through ICT infrastructure and smart devices combines to gather huge amounts of data in real-time, which is commonly known as big data. The big data generated by IoT devices will be stored in the big data storage system and will be used for analysis. The importance of Food Wastage Reduction (FWR) is related to the loss of all the natural resources in the supply chain, including expenditures related to the use of land, water supply, and energy consumption. The application of IoT to FWR systems is also examined where use RFID sensors as a key tool to monitor food waste for each individual in accordance with the proposed model, while describe the application of IoT-based technologies to agricultural supply chain management in developing countries.
  • 1.1K
  • 08 Dec 2023
Topic Review
Artificial Intelligence Techniques in Surveillance Video Anomaly Detection
The Surveillance Video Anomaly Detection (SVAD) system is a sophisticated technology designed to detect unusual or suspicious behavior in video surveillance footage without human intervention. The system operates by analyzing the video frames and identifying deviations from normal patterns of movement or activity. This is achieved through advanced algorithms and machine learning techniques that can detect and analyze the position of pixels in the video frame at the time of an event.
  • 1.1K
  • 10 May 2023
Topic Review
Deep Learning in SOC Estimation for Li-Ion Batteries
As one of the critical state parameters of the battery management system, the state of charge (SOC) of lithium batteries can provide an essential reference for battery safety management, charge/discharge control, and the energy management of electric vehicles (EVs). The SOC estimation of a Li-ion battery in the deep learning method uses deep learning theory of computer science to build a model that builds the approximate relationship between input data (voltage, current, temperature, power, capacity, etc.) and output data (SOC) by available data. According to different neural network structures, it can be classified as a single, hybrid, or trans structure. 
  • 1.1K
  • 02 Nov 2022
Topic Review
Visual Question Answering
Visual question answering (VQA) is a task that generates or predicts an answer to a question in human language about visual images. VQA is an active field combining two AI branches: Natural language processing (NLP) and computer vision. VQA usually has four components: vision featurization, text featurization, fusion model, and classifier. Vision featurization is a part of the multi-model responsible for extracting the vision features. Text featurization is another part of the VQA multi-model responsible for extracting text features. The combination of both features and their processes is the fusion component. The last component is the classifier that classifies the queries about the images and generates the answer.
  • 1.1K
  • 22 Sep 2023
Topic Review
Bio-Inspired Optimization Algorithms
The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. 
  • 1.1K
  • 24 Jul 2023
Topic Review
Machine Learning Algorithms in Manufacturing
The quality-control process in manufacturing must ensure the product is free of defects and performs according to the customer’s expectations. Maintaining the quality of a firm’s products at the highest level is very important for keeping an edge over the competition. To maintain and enhance the quality of their products, manufacturers invest a lot of resources in quality control and quality assurance. During the assembly line, parts will arrive at a constant interval for assembly. The quality criteria must first be met before the parts are sent to the assembly line where the parts and subparts are assembled to get the final product. Once the product has been assembled, it is again inspected and tested before it is delivered to the customer. Because manufacturers are mostly focused on visual quality inspection, there can be bottlenecks before and after assembly. The manufacturer may suffer a loss if the assembly line is slowed down by this bottleneck. To improve quality, state-of-the-art sensors are being used to replace visual inspections and machine learning is used to help determine which part will fail.
  • 1.1K
  • 19 Oct 2022
Topic Review
Methods and Algorithms for Crop-Row Detection
Crop row detection is one of the foundational and pivotal technologies of agricultural robots and autonomous vehicles for navigation, guidance, path planning, and automated farming in row crop fields. However, due to a complex and dynamic agricultural environment, crop row detection remains a challenging task. The surrounding background, such as weeds, trees, and stones, can interfere with crop appearance and increase the difficulty of detection. The detection accuracy of crop rows is also impacted by different growth stages, environmental conditions, curves, and occlusion. Therefore, appropriate sensors and multiple adaptable models are required to achieve high-precision crop row detection. 
  • 1.1K
  • 05 Jul 2023
Topic Review
Overview of Deep Learning-Based Visual Multi-Object Tracking
Multi-target tracking is an advanced visual work in computer vision, which is essential for understanding the autonomous driving environment. Due to the excellent performance of deep learning in visual object tracking, many state-of-the-art multi-target tracking algorithms have been developed.
  • 1.0K
  • 22 Nov 2022
Topic Review
Artificial Intelligence to Solve the IoT Security Challenges
The Internet of Things (IoT) is a well-known technology that has a significant impact on many areas, including connections, work, healthcare, and the economy. IoT has the potential to improve life in a variety of contexts, from smart cities to classrooms, by automating tasks, increasing output, and decreasing anxiety. Cyberattacks and threats, on the other hand, have a significant impact on intelligent IoT applications. Many traditional techniques for protecting the IoT are now ineffective due to new dangers and vulnerabilities. To keep their security procedures, IoT systems of the future will need artificial intelligence (AI)-efficient machine learning and deep learning. The capabilities of artificial intelligence, particularly machine and deep learning solutions, must be used if the next-generation IoT system is to have a continuously changing and up-to-date security system.
  • 1.0K
  • 16 Jun 2023
Topic Review
Phishing Email Detection Model Using Deep Learning
Email phishing is a widespread cyber threat that can result in the theft of sensitive information and financial loss. It uses malicious emails to trick recipients into providing sensitive information or transferring money, often by disguising themselves as legitimate organizations or individuals. As technology advances and attackers become more sophisticated, the problem of email phishing becomes increasingly challenging to detect and prevent.
  • 1.0K
  • 19 Oct 2023
Topic Review
Takagi–Sugeno Fuzzy-PI Controller Hardware
The intelligent system Field Programmable Gate Array (FPGA) is represented as Takagi--Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and floating-point). Two hardware designs are proposed; the first one uses a single clock cycle processing architecture, and the other uses a pipeline scheme. The bit accuracy was tested by simulation with a nonlinear control system of a robotic manipulator. The area, throughput, and dynamic power consumption of the implemented hardware are used to validate and compare the results of this proposal. The results achieved allow the use of the proposed hardware in applications with high-throughput, low-power, and ultra-low-latency requirements such as teleoperation of robot manipulators, tactile internet, or industry 4.0 automation, among others.
  • 1.0K
  • 29 Oct 2020
Topic Review
Wireless Sensors for Brain Activity
Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain.
  • 1.0K
  • 26 Jan 2021
Topic Review
Hidden Surface Determination
In 3D computer graphics, shown surface determination (also known as hidden surface removal (HSR), occlusion culling (OC) or visible surface determination (VSD)) is the process used to determine which surfaces and parts of surfaces are not visible from a certain viewpoint. A hidden surface determination algorithm is a solution to the visibility problem, which was one of the first major problems in the field of 3D computer graphics. The process of hidden surface determination is sometimes called hiding, and such an algorithm is sometimes called a hider. The analogue for line rendering is hidden line removal. Hidden surface determination is necessary to render an image correctly, so that one may not view features hidden behind the model itself, allowing only the naturally viewable portion of the graphic to be visible.
  • 1.0K
  • 26 Oct 2022
Topic Review
Tiny-YOLO-Based CNN Architecture for Applications in Human Detection
Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. Human detection technologies have advanced significantly due to the rapid development of deep learning techniques. Convolutional neural networks (CNNs) have become quite popular for tackling various problems, among which includes object detection.
  • 1.0K
  • 14 Oct 2022
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