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Donggyu Min,Sunghun Chung,Chulho Lee,Wenjing Duan 한국경영정보학회 2023 한국경영정보학회 학술대회논문집 Vol.2023 No.11
Despite the widespread use of artificial intelligence (AI) in mobile healthcare apps, the need for more transparency in AI algorithms hinders their effectiveness by preventing users from understanding the reasons behind AI-based information provision. To address this challenge, various types of explainable AI (XAI) are adopted to offer transparent explanations of AI. Despite significant debates surrounding AI intervention, limited research has been devoted to whether and how various XAI types affect user behavior differently. In this study, we conducted a randomized field experiment to investigate the effectiveness of three XAI algorithms: 1) feature importance, 2) feature attribution, and 3) counterfactual explanation in promoting users' health behavior. Drawing on the self-regulated learning theory, we expect that XAI focusing on counterfactual explanation increases strategic planning and outcome expectancy, resulting in better self-regulation behavior. Our findings indicate that counterfactual explanation significantly improves users' action planning behavior, leading to a 16.5% increase in workout duration and a 3.49% increase in health records compared to the control group. Our results are salient for users with a high level of AI susceptibility due to age, goal weight loss, and AI outcome. Our finding sheds light on the potential of algorithmic explanations to improve the effectiveness of AI interventions in the healthcare industry, with practical implications for designing more transparent and user-friendly healthcare apps.
Delay Optimal CSMA With Linear Virtual Channels Under a General Topology
Donggyu Yun,Dongmyung Lee,Se-Young Yun,Jinwoo Shin,Yung Yi IEEE 2016 IEEE/ACM transactions on networking Vol.24 No.5
<P>In the past few years, an exciting progress has been made on CSMA (Carrier Sense Multiple Access) algorithms that achieve throughput and utility optimality for wireless networks. However, most of these algorithms are known to exhibit poor delay performance making them impractical for implementation. Recently, several papers have addressed the delay issue of CSMA and yet, most of them are limited, in the sense that they focus merely on specific network scenarios with certain conditions rather than general network topology, achieve low delay at the cost of throughput reduction, or lack rigorous provable guarantees. In this paper, we focus on the recent idea of exploiting multiple channels (actually or virtually) for delay reduction in CSMA, and prove that it is per-link delay order-optimal, i.e., O(1)-asymptotic-delay per link, if the number of virtual channels is logarithmic with respect to mixing time of the underlying CSMA Markov chain. The logarithmic number is typically small, i.e., at most linear with respect to the network size. In other words, our contribution provides not only a provable framework for the multiple-channel based CSMA, but also the required explicit number of virtual-multi-channels, which is of great importance for actual implementation. The key step of our analytic framework lies in using quadratic Lyapunov functions in conjunction with (recursively applying) Lindley equation and Azuma's inequality for obtaining an exponential decaying property in certain queueing dynamics. We believe that our technique is of broader interest in analyzing the delay performance of queueing systems with multiple periodic schedulers.</P>
Indoor Path Recognition Based on Wi-Fi Fingerprints
Donggyu Lee,Jaehyun Yoo 사단법인 항법시스템학회 2023 Journal of Positioning, Navigation, and Timing Vol.12 No.2
The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.
Donggyu Choi,Jongwook Jang 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
After surgery, patients find it difficult to use the operating organs or move their bodies. Patients who don"t want a stuffy hospital life want to return to their daily lives as soon as possible, and need a recovery for it. Hospitals are introducing ERAS(Enhanced Recovery After Surgery) or the quick recovery effect of patients. ERAS means that all rehabilitation and pharmacological treatment methods for strengthening recovery before and after surgery are designed in a systematic order to perform treatment. It has been confirmed that the recovery rate varies from person to person depending on symptoms, age and gender, but is faster than the conventional method. However, the current ERAS process requires medical staff to check the patient"s performance for themselves, and there is a significant loss of human resources. Thus, in this paper, a study was conducted on the development of contents that could be checked unattended against the rehabilitation movement of ERAS without the verification process by the medical team.