This study proposes a tactile diagram pattern for visually impaired people to recognize color information. The pattern uses the principle of three primary colors, with different patterns representing red, blue, and ye...
详细信息
This article examines the incorporation of the Shopping Assistance Automatic Suggestion (SAAS) model into Virtual Reality (VR) environments in order to improve the online shopping experience. The SAAS model employs so...
详细信息
Low-cost navigation systems for ground vehicles often rely on the fusion with Global Positioning System (GPS) for improved state estimation. In this study a low-cost gyroscope is fused with a GPS for improved vehicle ...
Low-cost navigation systems for ground vehicles often rely on the fusion with Global Positioning System (GPS) for improved state estimation. In this study a low-cost gyroscope is fused with a GPS for improved vehicle heading angle estimation using several Artificial Intelligence (AI) based architectures that include Shallow Neural Networks (SNN), Multi-Layer Neural Networks (MLNN), and Adaptive Neuro- Fuzzy Inference Systems (ANFIS). The primary goal behind using AI based sensor fusion is to obtain a highly accurate vehicle heading estimation suitable for autonomous navigation applications. When available, the GPS signal is used to correct the vehicle's heading angle. The neural networks and ANFIS methods both use the difference between the GPS signal and the heading angle from the integrated gyroscope as inputs. The performance achieved is shown and analyzed. According to the results obtained, the MLNN provides the most accurate heading estimates.
Geothermal potential in Japan is estimated to be about 23 GW, which ranks in third worldwide. Japan aims to increase the installed capacity of geothermal power to 1.6 GW by 2030, but it is no more than 603 MW as of 20...
详细信息
The generation and replication of network traffic are essential tasks for testing, analyzing, simulating, and evaluating the behavior and efficiency of systems, protocols, applications, and network services. However, ...
详细信息
ISBN:
(数字)9798350330366
ISBN:
(纸本)9798350330373
The generation and replication of network traffic are essential tasks for testing, analyzing, simulating, and evaluating the behavior and efficiency of systems, protocols, applications, and network services. However, it faces various challenges and limitations when generating or replicating network traffic in a realistic, responsive, and scalable manner, using appropriate models. This work proposes a modeling of a program for generating and replicating network traffic, called Forensic Training Traffic Generator (ForTT-Gen), aims to address the challenge associated with generating and replicating network traffic generated by malware by creating files that can be used in the analysis of network packets inherent to forensic analysts' training. ForTT-Gen is a tool that can generate and replicate network traffic using a hybrid model that combines the replication of real data and the generation of synthetic data through statistical techniques. Experimental results demonstrate the model's ability to reliably. Accurately reproducing the statistical patterns of the original traffic, is evidenced by a determination coefficient of 1 and a Pearson coefficient of 0.9, all within a 0,58 confidence interval with 95% certainty.
Long-term data are essential for decision-making in the operation of constructed wetlands;however, such data are scarce. In the present study, a subsurface flow CW system was monitored over a 10-year period for the tr...
详细信息
Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for ...
详细信息
Nowadays, in order to decrease environmental impacts such as exhaustion of natural resources and CO2 discharge, the partial replacement of cement by fly ash and coarse aggregate by crushed fine aggregate in concrete h...
详细信息
Characteristic variability induced by process variation effect (PVE) is one of technological challenges in semiconductor industry. In this work, we computationally study electrical characteristic and power fluctuation...
详细信息
In this paper a new variant of the widely used Rapidly exploring Random Tree (RRT*) algorithm is proposed. The main goal of this variant is to improve the efficiency of the generated path, in both computation time and...
In this paper a new variant of the widely used Rapidly exploring Random Tree (RRT*) algorithm is proposed. The main goal of this variant is to improve the efficiency of the generated path, in both computation time and the quality of the path. In a previous work by the authors, an improved version RRT*N was proposed, where a normal probability distribution was used to control the generation of the random nodes. The proposed variant utilizes an intelligent fuzzy logic system (FLS) to control the generation of the random nodes and commands the robot to the required target introducing an intelligent fuzzy adaptive RRT*N path planning approach (FA-RRT*N). The proposed approach not only reduced the time required about 29.5 % of the time required by the RRT*, but also generally resulted in shorter path about 63% of the path generated by the traditional RRT * .
暂无评论