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5th IECC 2023: Osaka City, Japan
- Proceedings of the 2023 5th International Electronics Communication Conference, IECC 2023, Osaka City, Japan, July 21-23, 2023. ACM 2023

- Shibao Li

, Longfei Li
, Yunwu Zhang
, Chenxu Ma
, Chenghzhi Wang
:
Sliding Window Kalman Filter-Based DCQCN for RDMA Congestion Control. 1-6 - Vo-Trung-Dung Huynh

:
Performance Enhancement Using Adjacent Partitioning Scheme-Based Partial Transmit Sequence for Filtered-OFDM-Based 5G Systems. 7-13 - Yang Liu

, Kui Xu
, Nan Ma
, Mi Zhang
, Chengqian Ma
, Yueyue Zhang
:
IRS-assisted anti-jamming communication based on action space smooth Q-learning. 14-21 - Yuan-Hsun Liao

, Hsiao-Hui Li
, Po-Chun Chang
, Chiao-Ti Hsu
, Ruo-An Wang
:
Design an Intelligent Candy Inspection System with AIoT. 22-26 - Eric Gamess

, Mausam Parajuli
:
Performance Evaluation of the Docker Technology on Different Raspberry Pi Models. 27-37 - Jianbiao Wan

, Kar-Peo Yar
, Chunling Du
, Malcolm Yoke Hean Low
:
Sensor Data Analytics for Tool Condition Anomaly Detection with Machine Learning Techniques. 38-45 - Mohana Preethi V

, M. Prabhakar
, N. Senthil Kumar
:
Performance Analysis of Asymmetric High Gain Multi-Input Converter Under Widely Fluctuating Inputs. 46-52 - Hao-Wei Yang

, Kai-Fu Yang
, Chao-Hung Huang
, Tzung-Je Tsai
:
How to Painlessly Upgrade Traditional Stores to High-quality E-commerce through Digital Transformation - From the Perspective of Uncertainty in E-commerce Marketing. 53-62 - Yoji Yamato

:
Study of Software Reconfiguration after Adapted Service Start. 63-68 - Chih-Chung Lin

, Yuan-Cheng Lai
, Ming-Huang Zheng
, Chen-Hao Wang
, Yan-Rong Chen
, Li-An Gao
:
The Candlestick-Tracking Trend Decision for Day Trading on Taiwan Index Futures Market. 69-77 - Hsiao-Hui Li

, Yuan-Hsun Liao
, Chiao-Ti Hsu
:
Using Artificial Intelligence to Achieve Health Promotion for the Elderly by Utilizing the Power of Virtual Reality. 78-83 - Sangkeum Lee, Sarvar Hussain Nengroo

, Hojun Jin
, Yoonmee Doh
, Chungho Lee
, Taewook Heo
, Dongsoo Har
:
Power Management in Smart Residential Building with Deep Learning Model for Occupancy Detection by Usage Pattern of Electric Appliances. 84-92

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