2020 International Conference on Information and Communication Technology Convergence (ICTC)最新文献_第4页

A study on the modeling of the IoT-based motion pattern analysis system to exterminating harmful wild animals 基于物联网的有害野生动物扑杀运动模式分析系统建模研究

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289298

Hyung-Do Yoon, SoYoung Kim, Yea Sol Jang, M. Ghil, W. Rha, Y. Seok

{"title":"A study on the modeling of the IoT-based motion pattern analysis system to exterminating harmful wild animals","authors":"Hyung-Do Yoon, SoYoung Kim, Yea Sol Jang, M. Ghil, W. Rha, Y. Seok","doi":"10.1109/ICTC49870.2020.9289298","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289298","url":null,"abstract":"The damage of crops caused by harmful wild animals is not limited to individual farmland, but has been expanded to villages, regions, and even countries of interest. In other words, it goes beyond the damage of farmland and leads to social problems such as village appearance and road kill. Therefore, it is urgent to prepare a solution for controlling the population of harmful wild animals and managing an appropriate level of population. An IoT and AI-based intelligent harmful wild animal extermination system is needed that can be applied to farmhouses, orchards, airports and military boundaries through big data analysis algorithms of harmful wild animals (boar, elk, bird, mole), real-time wired/wireless data processing and performance monitoring research. Research was conducted on the construction of a system for extermination harmful wild animals and upgrading the real-time response system as an operating system. The core technology consists of multi IoT sensing technology, big data and AI analysis technology. In addition, the system consists of a main control device, a node device (long range), a control server, AI analysis SW, and a smartphone app.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128052579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The Empirical Evaluation of Models Predicting Bike Sharing Demand 共享单车需求预测模型的实证评价

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289176

Seung Han Choi, Mijin Han

引用次数: 4

An Image-based Human Physical Activities Recognition in an Indoor Environment 室内环境下基于图像的人体运动识别

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289314

F. Ullah, Asif Iqbal, Ajmal Khan, Rida Gul Khan, Laraib Malik, K. Kwak

{"title":"An Image-based Human Physical Activities Recognition in an Indoor Environment","authors":"F. Ullah, Asif Iqbal, Ajmal Khan, Rida Gul Khan, Laraib Malik, K. Kwak","doi":"10.1109/ICTC49870.2020.9289314","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289314","url":null,"abstract":"In this paper, we propose real-time image-based recognition of human activities from series of images considering different human actions performed in an indoor environment.The proposed image-based human activity recognition(IHAR)system can be utilized for assisting the life of disabled persons, surveillance and human tracking, human computer interaction,and efficient resource utilization. The proposed IHAR system consists of closed-circuit television (CCTV) camera based image acquisitioning, various filtering based image enhancement, principle component analysis(PCA) based features extraction, and various machine learning algorithms for recognition accuracy performance comparison. We collected dataset of 10 different activities such as walking, sitting down and standing up consists of 35,530 images. The dataset is divided into(90%,10%),(80%,20%), and(70%,30%)training and testing respectively and evaluated three classifier K-nearest neighbors (KNN), Random Forest (RF), and Decision Tree(DT). The experimental results show the accuracy of 95%, 97%, and 90% by KNN, RF, and DT respectively.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115818617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Performance Improvement of Video Classification using Generated Labeled Data 基于生成标记数据的视频分类性能改进

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289479

Alex Lee, Jeong-Woo Son, Sun-Joong Kim

引用次数: 0

Impact of Data Center Cooling Technology to Effectiveness of Turbo-Mode 数据中心冷却技术对涡轮模式效率的影响

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289200

Jaehyong Shin, Euiseong Seo

引用次数: 2

Limit Action Space to Enhance Drone Control with Deep Reinforcement Learning 限制行动空间，用深度强化学习增强无人机控制

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289571

Sooyoung Jang, Noh-Sam Park

引用次数: 0

Generative Adversarial Network for Robust Regression using Continuous Dataset 基于连续数据集的鲁棒回归生成对抗网络

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289188

Yu-Lim Min, Seung-Jin Hong, Hye-jin Kim, Seung-Ik Lee

{"title":"Generative Adversarial Network for Robust Regression using Continuous Dataset","authors":"Yu-Lim Min, Seung-Jin Hong, Hye-jin Kim, Seung-Ik Lee","doi":"10.1109/ICTC49870.2020.9289188","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289188","url":null,"abstract":"Recently, advanced neural network, which is implementing technical method, has focus on dealing with image classification problems. Unlike classification problems, regression provides a value of output in complex and sophisticated continuous datasets. Though nonlinear models can perform regression better than linear model as Linear Regression(LR), the difficulty to make robust model still remain. In this paper, our purpose is to design training architecture for robust regression. We approach Neural Network known as nonlinear regression to solve limitation of Linear Regression. Additionally, Our architecture uses a new artificial Neural Network(NN) based on adversarial architecture by using the Generator(G) and Discriminator(D). The Discriminator shows the better performance while competing with the Generator and learning regression problem as same time. In evaluation experiments, we compare our proposed model with baseline models including Linear Regression and Neural Network using continuous real world data. We split four datasets into train and test sets as 90:10 and evaluate them by using Mean Squared Error(MSE) function. In summary, our model trained with Generative Adversarial Network(GAN) shows better performance than the baseline models.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129976656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Study on Blockchain-based Music Distribution Framework: Focusing on Copyright Protection 基于区块链的音乐发行框架研究:以版权保护为核心

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289184

Ahyoung Kim, Mucheol Kim

{"title":"A Study on Blockchain-based Music Distribution Framework: Focusing on Copyright Protection","authors":"Ahyoung Kim, Mucheol Kim","doi":"10.1109/ICTC49870.2020.9289184","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289184","url":null,"abstract":"Blockchain, which started as a cryptocurrency bitcoin, has recently been applied to various fields such as finance, distribution, and public services beyond the category of cryptocurrency. In this paper, we propose a music distribution model to protect music copyrights and rights holders' rights based on blockchain and smart contract technology. By designing and implementing a blockchain-based music distribution model, it organizes music assets into blocks and distributes them among blockchain participating nodes, providing integrity, confidentiality and non-repudiation of assets, and a single point of blockchain advantage. Single Point of Failure (SPOF) problem can be minimized. Blockchain allows musicians to easily approve and manage their music copyright with distributed ledger technology. Rights holders can automatically and immediately receive royalties from the music industry, even if no broker is involved in the distribution process. By distributing and managing music using the proposed model, we can provide all transaction information and related tasks in the music market safely and transparently.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130120251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

A Novel Frequency Domain Preamble Detection for OFDM based WLAN Systems 一种基于OFDM的WLAN系统频域前导检测方法

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289165

E. Jin, Hyuncheol Park

引用次数: 4

Intra-protocol Convergence Problem in BBRv2’s Bandwidth Probing BBRv2带宽探测中的协议内收敛问题

2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289384

Yeong-Jun Song, Won-Ju Eom, Jeong-Keun Kim, Chang-hoon Park, Geon-Hwan Kim, You-Ze Cho

{"title":"Intra-protocol Convergence Problem in BBRv2’s Bandwidth Probing","authors":"Yeong-Jun Song, Won-Ju Eom, Jeong-Keun Kim, Chang-hoon Park, Geon-Hwan Kim, You-Ze Cho","doi":"10.1109/ICTC49870.2020.9289384","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289384","url":null,"abstract":"Google introduced Bottleneck Bandwidth Round-trip propagation time (BBR), which is a new concept of congestion control algorithm. BBR measures the available bottleneck bandwidth and minimum round-trip time. It then creates network path models to maximize the delivery rate and minimize latency. However, BBR creates unfairness problem with other TCP flows and excessive packet loss in a small buffer. Google, therefore, updated BBR, creating a new version, called BBRv2, to improve coexistence with other flows and reduce aggressiveness. BBRv2 significantly improved the fairness with loss-based congestion control algorithms and reduced the number of packet retransmissions in a small buffer compared to the existing BBR. However, in this study, we confirmed that multiple BBRv2 flows that enter the same link at different times do not take up bandwidth fairly. Therefore, we evaluate the fairness between identical BBRv2 flows through the Mininet emulation and analyze the reason for this problem. The test results show that when the bottleneck buffer size is smaller than 0.2 BDP, two BBRv2 flows have similar throughput and the number of packet retransmissions greatly reduces compared to BBRv1. However, with a large buffer, the flow starting first occupies more bandwidth.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134258773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2