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This paper proposes a CanSat system with a vehicle tracking function based on Jetson Nano, a high-performance small computer capable of operating artificial intelligence algorithms. The CanSat system consists of a CanSat and a ground station. The CanSat falls in the atmosphere and transmits the data obtained through the installed sensors to the ground station using wireless communication. The existing CanSat has the limitation of being simple data collectors, literally carrying out the mission of transmitting the collected data to the ground station as it is. The Jetson Nano-based CanSat proposed in this paper uses a pre-trained neural network model to detect the location of a vehicle in each image taken from the air in real time, and then uses a 2-axis motor to move the camera to track the vehicle. The performance of the proposed CanSat system is evaluated by measuring the accuracy and speed of vehicle tracking using self-produced image dataset. [ABSTRACT FROM AUTHOR]

The MCTS algorithm is frequently used in game AI. The commonly used tree policy is the UCT algorithm. In this paper, we propose the use of MLPT (Multi-Level Priority List) algorithm as a tree policy to ensure performance and optimize it for different game fields. MLPT selects the first available node from the top-level children of the node and adjusts its priority based on the outcome. As a result, when starting bet was 2% of the current amount, the average reward ratio was 101.237%, standard deviation was 0.0815, and winning rate was 51.739%. In games played until bankruptcy, the winning rate was 97.8% with 47.7 wins and 60.2 losses. MLPT provided the most stable profits compared to other tree policies and showed that it was a stable bet with a higher number of wins. The proposed MLPT algorithm outperforms existing methods by providing stable bets. [ABSTRACT FROM AUTHOR]

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process. [ABSTRACT FROM AUTHOR]

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field. [ABSTRACT FROM AUTHOR]

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method. [ABSTRACT FROM AUTHOR]

Object recognition is to identify the location and class of a specific object by analyzing the given image when a specific image is input. One of the fields in which object recognition technology is actively applied in recent years is autonomous vehicles, and this paper describes the trend of image-based object recognition artificial intelligence technology in autonomous vehicles. The image-based object detection algorithm has recently been narrowed down to two methods (a single-step detection method and a two-step detection method), and we will analyze and organize them around this. The advantages and disadvantages of the two detection methods are analyzed and presented, and the YOLO/SSD algorithm belonging to the single-step detection method and the R-CNN/Faster R-CNN algorithm belonging to the two-step detection method are analyzed and described. This will allow the algorithms suitable for each object recognition application required for autonomous driving to be selectively selected and R&D. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers. [ABSTRACT FROM AUTHOR]

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test. [ABSTRACT FROM AUTHOR]

The recent software education in middle schools is focused on physical computing, unplugged learning and pilot training. However, they are struggling in many ways, including cost, inducement of interest, motivation, and concentration. Also, the lack of systematic classroom design could make negative effect to students' understanding of classes or academic performance. In this paper, we intend to study the method of algorithm education using Chatbot system, which will increase efficiency of software education, with less burdensome in terms of cost, and also could be able to used as an assist tool in various classes. In class scenarios that require the understanding of coding mechanisms such as function application, algorithm design, and program coding, students can learn by themselves through the Chatbot system, which has a positive effect on student learning. [ABSTRACT FROM AUTHOR]