Ga-Eun Jung, JiKook Baek, Jianyong Liu, V. Q. Dao, M. Dinh, Chang-Soon Kim, Myung-Kwan Lee, JungHyo Bae
{"title":"The Precision SOC Estimation Method of LiB for EV Applications Using ANN","authors":"Ga-Eun Jung, JiKook Baek, Jianyong Liu, V. Q. Dao, M. Dinh, Chang-Soon Kim, Myung-Kwan Lee, JungHyo Bae","doi":"10.1109/ICTC52510.2021.9620997","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9620997","url":null,"abstract":"Lithium-ion battery(LiB) is being used in various fields due to their advantages such as high energy density, high power density, and longer cycle life. In order to optimize the performance of the LiB and improve the lifetime of the Electric Vehicle (EV), monitoring the State of Charge (SOC) is very important. Therefore, it is essential to estimate of the SOC of the battery. This paper proposed the SOC estimation model for lithium-ion batteries based on the Artificial Neural Network (ANN) model. In the proposed model, SOC estimation of lithium-ion batteries was performed through five steps include variable selection, data collection, data preprocessing, neural network paradigm, and neural network learning. The actual SOC and the predicted SOC of the EV battery model were compared to prove the validity of the ANN model. As a result, the ANN showed the maximum and average errors of 18% and 2.65%, respectively, and the accuracy was 97.35%.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125273608","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}
P. T. Daely, Yohana Jayanti Aruan, Jae-Min Lee, Dong-Seong Kim
{"title":"Dynamic VRP Optimization Using Discrete PSO in Edge Computing Environment","authors":"P. T. Daely, Yohana Jayanti Aruan, Jae-Min Lee, Dong-Seong Kim","doi":"10.1109/ICTC52510.2021.9620744","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9620744","url":null,"abstract":"This paper proposes using Discrete Particle Swarm Optimization (PSO) to generate an immediate solution for the dynamic vehicle routing problem (VRP). There are many applications of dynamic VRP in the real world, where not every target location to be visited is known at the very beginning, and each target location is informed at any arbitrary time. Therefore, a routing system is required to route any available vehicle to visit all target locations. Furthermore, an algorithm is needed to provide route updates when a new location is acquired. Each location must be visited within a specific time, and all vehicles must go back to the depot before the depot closing time. This variant of VRP can be categorized as dynamic capacitated VRP with time windows (DCVRPTW). An edge computing environment is designed to distribute the management of vehicles to multiple edge nodes so that the cloud server does not need to handle the vehicle, thus cutting the computation time. A discrete PSO based algorithm is designed and deployed at each edge node to solve this problem. Computer simulations show that the proposed system can route available vehicles to all target locations within their time windows with minimal routing time by edge nodes.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126646743","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}
{"title":"Performance analysis of Access Point Switch ON/OFF schemes for Cell-free mmWave massive MIMO UDN systems","authors":"Soojung Jung, Seung‐Eun Hong","doi":"10.1109/ICTC52510.2021.9620943","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9620943","url":null,"abstract":"Considering required features for beyond-5G wireless communication, such as higher spectral efficiency and energy efficiency, cell-free massive MIMO(mMIMO) is one of the promising technologies. In this paper, we propose an Access Point(AP) Switch ON/OFF (ASO) scheme in cell-free mmWave mMIMO systems for higher energy efficiency, which switch on/off APs based on the order determined by the importance of APs within the systems. Numerical results show that the proposed scheme improves the energy efficiency performance of cell-free mmWave mMIMO systems compared to the conventional schemes.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114887333","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}
Jongtae Song, JiWook Youn, Dae-Ub Kim, Kyeong‐Eun Han, Joonki Lee
{"title":"Performance Evaluation on Optically Disaggregated Memory Architecture","authors":"Jongtae Song, JiWook Youn, Dae-Ub Kim, Kyeong‐Eun Han, Joonki Lee","doi":"10.1109/ICTC52510.2021.9621006","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9621006","url":null,"abstract":"We investigate the performance of cloud network with optically disaggregated memory under different CPU-memory interconnection architectures. We found that long burst of cache memory traffic minimizes the performance degradation and CPU intensive application can achieve ~94 % performance of ideal condition even in inter-rack distance with 1Gbps CPU-memory bandwidth.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122550126","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}
{"title":"A Service Management Method for Distributed Deep Learning","authors":"Seungwoo Kum, Seungtaek Oh, Jaewon Moon","doi":"10.1109/ICTC52510.2021.9621013","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9621013","url":null,"abstract":"With the advance of deep learning technologies, many applications and/or services that rely on them can be easily found these days. Applications relying on deep learning varies from video, audio, text and time-series data, and they provide high-accuracy services that are built with the software platforms such as TensorFlow or PyTorch. Usually, a deep learning service requires rich resources such as GPU and large memory. For instance, GPT-3 requires memories up to a few hundred gigabytes, and for the video processing it needs accelerators such as GPU. The cost will be increased if all the resources are on the cloud, and there are many works on offloading these workloads of deep learning onto distributed infrastructure. One of the focuses of these works are distribution of deep learning workloads onto various resource and providing an end-to-end service by the combination of them. Edge computing or Fog computing is one of the architectures providing workload distribution method from cloud to edge resources. This paper proposes a method that enables autonomous configuration between distributed services. In the proposed method, the composition of distributed services is described in systematic way so to configure the connections between them more intuitively. Further, the proposed method includes binding of a resource to a service which enables management of multiple service distributions, and how it can work with existing standards.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122730771","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}
{"title":"Low-complexity Neighborhood-based Weighted Centroid Localization for Secondary Users in Cognitive Radio Network","authors":"N. Nath, Xiaowei Liang, Bin Shen","doi":"10.1109/ICTC52510.2021.9620939","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9620939","url":null,"abstract":"Traditional spectrum sensing is usually viewed as one of the enabling technologies for cognitive radio (CR) systems due to its capability of guaranteeing the minimum interference between the primary users (PU) and secondary users (SU). In order to determine the possibility of accessing the licensed frequency band (LFB), we propose to exploit the mutual location information of the PUs and SUs in the cognitive radio network (CRN). Specifically, a low-complexity neighborhood-based weighted centroid localization (NB-WCL) algorithm is proposed to acquire the SU localizations. Once the positioning results are obtained, the proposed algorithm assists the SUs in setting their LFB-access flags in the CRN. Simulation results show that the proposed algorithm outperforms some existing conventional localization algorithms with better root mean square error (RMSE) performance. The proposed algorithm can serve as a practically effective candidate solution for LFB status identification in the CRN.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122736281","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}
{"title":"mobile YOLACT: Toward Lightweight Instance Segmentation for Mobile Devices","authors":"Juwon Lee, Seungjae Lee, Jong-gook Ko","doi":"10.1109/ICTC52510.2021.9621125","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9621125","url":null,"abstract":"In this paper, we present a lightweight instance segmentation model, mobileYOLACT which is designed for mobile environments where the computational resources are limited. We propose several modifications to YOLACT to improve computational efficiency. First, we use a quantized lightweight backbone for feature extraction. Second, we reduce the computational burden with marginal degradation in accuracy by employing the depthwise separable convolution on the entire model. Third, we simplified the structure of prototype mask generation branch. Last, we used TorchScript and NCNN to further optimize the model and deploy it on mobile device. We validate the effectiveness of the proposed method from the experiments on COCO dataset. The proposed model can run at the speed of 21 FPS on Samsung Galaxy S20 with 23 APmask at 0.5 IoU threshold.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114472563","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}
Seunghyun Jang, Sunwoo Kong, Hui-Dong Lee, Bonghyun Park, Seok-Bong Hyun
{"title":"Temperature Sensor Circuit with Dynamic Element Matching in CMOS 65 nm for a mmWave Beamformer","authors":"Seunghyun Jang, Sunwoo Kong, Hui-Dong Lee, Bonghyun Park, Seok-Bong Hyun","doi":"10.1109/ICTC52510.2021.9621051","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9621051","url":null,"abstract":"Due to circuit element mismatch occurred during semiconductor fabrication, there exists a discrepancy in performance between the implemented chips and the circuit simulation results. Unfortunately, this discrepancy becomes more severe as a system require higher signal quality. In this paper, a temperature sensor circuit for a mmWave beamformer for 5th generation mobile communication systems is designed and simulated using a CMOS 65 nm process. To obtain highly accurate and robust performance against the circuit element mismatches during the chip production, a dynamic element rotation is exploited because the implementation is simple and occupies small silicon area. According to 1000-run Monte Carlo simulation results, the accuracy of a designed temperature sensor circuit is improved by eight times under a 3- σvariation in sensor biasing currents","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122101639","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}
{"title":"Main features of 5G New Radio for Non-Terrestrial Networks","authors":"M. Yun, Jihyung Kim, Dukhyun You, Moonsik Lee","doi":"10.1109/ICTC52510.2021.9620941","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9620941","url":null,"abstract":"As the non-terrestrial networks can provide a wide range of service coverage and the vulnerability of the spaceborne or airborne platform is reduced, interest in providing 5G service using the non-terrestrial networks has been increasing. To benefit from the economies of scale of the 5G ecosystem, interest in integration of the non-terrestrial networks (NTN) into the terrestrial networks has been growing. Integration with the existing terrestrial networks can also provide global connectivity and communications resiliency. Standardization efforts to integrate NTN into the 3rd generation partnership project (3GPP) ecosystem have been ongoing. In this paper, we provide an overview of the state of the art in the non-terrestrial networks working on the 3GPP. Furthermore, we analyze technical challenges, solutions and remaining issues dealing in 3GPP NTN regarding to two main characteristics of the long propagation delay and fast movement of NTN platforms. Finally, our views on 6G standardization towards realization of three-dimensional spatial networks are presented.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116839655","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}
{"title":"Emotion Detection and Analysis from Facial Image using Distance between Coordinates Feature","authors":"Jinhee Bae, Minwoo Kim, J. Lim","doi":"10.1109/ICTC52510.2021.9621199","DOIUrl":"https://doi.org/10.1109/ICTC52510.2021.9621199","url":null,"abstract":"Facial expression recognition has long been established as a subject of continuous research in various fields. In this study, feature extraction was conducted by calculating the distance between facial landmarks in an image. The extracted features of the relationship between each landmark and analysis were used to classify five facial expressions. We increased the data and label reliability based on our labeling work with multiple observers. Additionally, faces were recognized from the original data, and landmark coordinates were extracted and used as features. A genetic algorithm was used to select features that were relatively more helpful for classification. We performed facial recognition classification and analysis using the method proposed in this study, which showed the validity and effectiveness of the proposed method.","PeriodicalId":299175,"journal":{"name":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706973","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}