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A Quantitative Comparison of LIME and SHAP using Stamp-Based Distance Method on Image Data
http://doi.org/10.5626/JOK.2023.50.10.906
XAI(eXplainable AI), 인공신경망, MNIST, 도장 기반의 distance method, LIME, SHAP Abstract XAI, or eXplainable AI, is a technique used to explain artificial neural networks in a way that can be understood by humans. However, it is difficult to compare explanations and heat maps produced by XAI algorithms numerically as it is unclear how humans interpret them. This presents a challenge in determining which XAI algorithm is the most effective and accurate in providing explanations. Therefore, we introduced a stamp-based distance method to compare several XAI algorithms and identify the most accurate algorithm. The proposed method involves evaluating the quality of explanations generated by XAI algorithms applied to a deep learning model trained to detect the presence of stamps in the MNIST dataset. This evaluation was performed using statistical techniques to determine the effectiveness of each XAI algorithm. This paper evaluated performances of LIME and SHAP algorithms using the distance method, which compared explanations produced by each algorithm. Result revealed that LIME with the Felzenszwalb method provided more effective explanations than other LIME and SHAP algorithms.
Design and Implementation of Indoor Positioning System Using Particle Filter Based on Wireless Signal Intensity
http://doi.org/10.5626/JOK.2020.47.4.433
This paper proposes an Indoor Positioning System to track a user’s position indoors by using beacons’ wireless signal intensity. To overcome the non-linearity of an existing indoor positioning scheme using wireless signal intensity, a particle filter is used for a positioning algorithm, so the noise of the wireless signal intensity is not directly reflected on the positioning result. In the observation phase of the particle filter, the distance from a user’s smartphone is estimated based on the wireless signal intensity, and the similarity of each particle with an estimated ground truth is calculated through the predicted distance value. Also, our proposed positioning scheme uses the random walk technique (the Monte Carlo method) to calculate a position estimation value. Additionally, to solve the well-known local minimum problem of the particle filter, the particles estimated closest to the beacons according to the distance prediction values are given proximity weights, so the particles can quickly locate the user. The positioning error on the walking path is also corrected by considering the indoor map.
An Automatic Rhythm and Melody Composition System Considering User Parameters and Chord Progression Based on a Genetic Algorithm
In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.
Design and Implementation of DNS Name Autoconfiguration for Internet of Things Devices
As one of the most spotlighted research areas, these days, the Internet of Things (IoT) aims to provide users with various services through many devices. Since there exist so many devices in IoT environments, it is inefficient to manually configure the domain name system (DNS) names of such devices. Thus, for IPv6-based IoT environments, this paper proposes a scheme called the DNS Name Autoconfiguration (DNSNA) that autoconfigures an IoT device’s DNS name and manages it. In the procedure for generating and registering an IoT device’s DNS name, the standard protocols of the Internet Engineering Task Force (IETF) are used. Since the proposed scheme resolves an IoT device’s DNS name into an IPv6 address in unicast through a DNS server, it generates less traffic than multicast-based mDNS (Multicast DNS) which is a legacy DNS application for the DNS name service in the smart home. Thus, the proposed scheme is more appropriate in multi-hop IoT networks than mDNS. This paper explains the design of the proposed scheme and its service scenarios, such as smart home and smart road. It also explains the implementation and testing of the proposed scheme in the smart grid.
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