Pub Date : 2023-07-01DOI: 10.1109/MSMC.2022.3231415
M. W. Akhtar, N. Saeed
The next generation of wireless communication systems will integrate terrestrial and nonterrestrial networks, targeting the coverage of the undercovered regions, especially those connected to marine activities. Unmanned aerial vehicle (UAV)-based connectivity solutions offer significant advances to support conventional terrestrial networks. However, the use of UAVs for maritime communication is still an unexplored area of research. Therefore, this article highlights different aspects of UAV-based maritime communication, including the basic architecture, various channel characteristics, and use cases. The article afterward discusses several open research problems, such as mobility management, trajectory optimization, interference management, and beam forming.
{"title":"UAVs-Enabled Maritime Communications: UAVs-Enabled Maritime Communications: Opportunities and Challenges","authors":"M. W. Akhtar, N. Saeed","doi":"10.1109/MSMC.2022.3231415","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3231415","url":null,"abstract":"The next generation of wireless communication systems will integrate terrestrial and nonterrestrial networks, targeting the coverage of the undercovered regions, especially those connected to marine activities. Unmanned aerial vehicle (UAV)-based connectivity solutions offer significant advances to support conventional terrestrial networks. However, the use of UAVs for maritime communication is still an unexplored area of research. Therefore, this article highlights different aspects of UAV-based maritime communication, including the basic architecture, various channel characteristics, and use cases. The article afterward discusses several open research problems, such as mobility management, trajectory optimization, interference management, and beam forming.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"37 1","pages":"2-8"},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73162374","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}
Pub Date : 2023-07-01DOI: 10.1109/MSMC.2022.3220315
Xiaoming Li, Jie Gao, C. Wang, Xiao Huang, Yimin Nie
Vehicle proactive guidance strategies are used by ride-hailing platforms to mitigate supply–demand imbalance across regions by directing idle vehicles to high-demand regions before the demands are realized. This article presents a data-driven stochastic optimization framework for computing idle vehicle guidance strategies. The objective is to minimize drivers’ idle travel distance, riders’ wait time, and the oversupply costs (OSCs) and undersupply costs (USCs) of the platform. Specifically, we design a novel neural network that integrates gated recurrent units (GRUs) with mixture density networks (MDNs) to capture the spatial-temporal features of the rider demand distribution.
{"title":"MDN-Enabled SO for Vehicle Proactive Guidance in Ride-Hailing Systems: Minimizing Travel Distance and Wait Time","authors":"Xiaoming Li, Jie Gao, C. Wang, Xiao Huang, Yimin Nie","doi":"10.1109/MSMC.2022.3220315","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3220315","url":null,"abstract":"Vehicle proactive guidance strategies are used by ride-hailing platforms to mitigate supply–demand imbalance across regions by directing idle vehicles to high-demand regions before the demands are realized. This article presents a data-driven stochastic optimization framework for computing idle vehicle guidance strategies. The objective is to minimize drivers’ idle travel distance, riders’ wait time, and the oversupply costs (OSCs) and undersupply costs (USCs) of the platform. Specifically, we design a novel neural network that integrates gated recurrent units (GRUs) with mixture density networks (MDNs) to capture the spatial-temporal features of the rider demand distribution.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"41 1","pages":"28-36"},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88012408","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}
Building the right learning teams is a key to the success of collaborative learning in online and offline learning environments. However, existing research on learning team formation (LTF) ignores the uncertainty of learners’ abilities and lacks a common problem modeling and optimization approach. Aiming at the characteristics of two typical types of leader-centered (LC) LTF problems, a universal optimization framework of LC-LTF is proposed by introducing role-based collaboration (RBC) theory. This framework evaluates the comprehensive ability of learners via a fuzzy description mechanism; applies the environments–classes, agents, roles, groups, and objects (E-CARGO) model to formulate the LC-LTF problem; and employs an optimization platform to obtain an optimal solution. A case study demonstrates the effectiveness and feasibility of the proposed framework.
{"title":"Universal Optimization Framework: Leader-Centered Learning Team Formation Based on Fuzzy Evaluations of Learners and E-CARGO","authors":"Hua Ma, Jingze Li, Yuqi Tang, Haibin Zhu, Zhuoxuan Huang, Wen-sheng Tang","doi":"10.1109/MSMC.2022.3231698","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3231698","url":null,"abstract":"Building the right learning teams is a key to the success of collaborative learning in online and offline learning environments. However, existing research on learning team formation (LTF) ignores the uncertainty of learners’ abilities and lacks a common problem modeling and optimization approach. Aiming at the characteristics of two typical types of leader-centered (LC) LTF problems, a universal optimization framework of LC-LTF is proposed by introducing role-based collaboration (RBC) theory. This framework evaluates the comprehensive ability of learners via a fuzzy description mechanism; applies the environments–classes, agents, roles, groups, and objects (E-CARGO) model to formulate the LC-LTF problem; and employs an optimization platform to obtain an optimal solution. A case study demonstrates the effectiveness and feasibility of the proposed framework.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"4 1","pages":"6-17"},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80677827","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}
Deep vein thrombosis (DVT) is a venous reflux disorder disease caused by abnormal blood coagulation in the deep veins. It frequently occurs in the lower limbs of orthopedic patients, pregnant women, and the elderly. DVT can easily cause a pulmonary embolism (PE), a disease with a high mortality rate. Therefore, the detection and processing of DVT are crucial. Based on traditional diagnostic management, doctors use D-dimer and ultrasound (US) for screening and diagnosis. However, it does not work well for early diagnosis, and the cost to the health-care system is enormous. Early detection and continuous monitoring are the urgent capabilities that current diagnostic equipment needs. Point-of-care testing (POCT) equipment is a type of detection equipment that can diagnose independently and also has the advantages of stability, reliability, easy care, and long-term monitoring. It has a wide application scenario and can be used away from the service and inspection centers, for example, in telemedicine, outdoor first aid, and community health care. POCT equipment also benefits new development in the early diagnosis of DVT. This article presents the history of diagnostic procedures and a clinical diagnostic approach to DVT. We investigate the early diagnosis of DVT based on the characteristics of POCT equipment. We present the current state, benefits, and drawbacks of POCT diagnostic equipment, including POC D-dimer, POC US (POCUS), and photoplethysmography (PPG). In addition, we analyze performance measures from research methods, such as sensitivity and specificity. Finally, we outline the developing trends of DVT detection methods and propose several issues that need to be addressed.
深静脉血栓形成(DVT)是由深静脉内血液凝固异常引起的静脉反流性疾病。常见于骨科病人、孕妇和老年人的下肢。深静脉血栓形成很容易导致肺栓塞(PE)，这是一种死亡率很高的疾病。因此，深静脉血栓的检测和处理至关重要。在传统诊断管理的基础上，医生使用d -二聚体和超声(US)进行筛查和诊断。然而，它在早期诊断方面效果不佳，而且医疗保健系统的成本巨大。早期发现和持续监测是当前诊断设备迫切需要的能力。POCT (Point-of-care testing)设备是一种能够独立诊断的检测设备，具有稳定、可靠、护理方便、长期监测等优点。它具有广泛的应用场景，可以在远离服务和检测中心的地方使用，例如远程医疗、户外急救和社区卫生保健。POCT设备在DVT的早期诊断方面也有了新的发展。本文介绍了深静脉血栓的诊断程序和临床诊断方法的历史。我们根据POCT设备的特点探讨深静脉血栓的早期诊断。我们介绍了POCT诊断设备的现状、优点和缺点，包括POC d -二聚体、POCUS (POCUS)和光容积脉搏波描记仪(PPG)。此外，我们从研究方法，如敏感性和特异性分析性能指标。最后，我们概述了DVT检测方法的发展趋势，并提出了需要解决的几个问题。
{"title":"Point-of-Care Testing in the Diagnosis of Deep Vein Thrombosis: A Review","authors":"Zejun Zhang, Junding Wu, Wanjun Cheng, Xia Zhang, Lisheng Xu, Yudong Yao","doi":"10.1109/MSMC.2022.3224595","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3224595","url":null,"abstract":"Deep vein thrombosis (DVT) is a venous reflux disorder disease caused by abnormal blood coagulation in the deep veins. It frequently occurs in the lower limbs of orthopedic patients, pregnant women, and the elderly. DVT can easily cause a pulmonary embolism (PE), a disease with a high mortality rate. Therefore, the detection and processing of DVT are crucial. Based on traditional diagnostic management, doctors use D-dimer and ultrasound (US) for screening and diagnosis. However, it does not work well for early diagnosis, and the cost to the health-care system is enormous. Early detection and continuous monitoring are the urgent capabilities that current diagnostic equipment needs. Point-of-care testing (POCT) equipment is a type of detection equipment that can diagnose independently and also has the advantages of stability, reliability, easy care, and long-term monitoring. It has a wide application scenario and can be used away from the service and inspection centers, for example, in telemedicine, outdoor first aid, and community health care. POCT equipment also benefits new development in the early diagnosis of DVT. This article presents the history of diagnostic procedures and a clinical diagnostic approach to DVT. We investigate the early diagnosis of DVT based on the characteristics of POCT equipment. We present the current state, benefits, and drawbacks of POCT diagnostic equipment, including POC D-dimer, POC US (POCUS), and photoplethysmography (PPG). In addition, we analyze performance measures from research methods, such as sensitivity and specificity. Finally, we outline the developing trends of DVT detection methods and propose several issues that need to be addressed.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"8 1","pages":"49-56"},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87007098","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}
Pub Date : 2023-04-01DOI: 10.1109/MSMC.2022.3229838
K. Karunanithi, S. Ramesh, S. Raja, Swaminathan Saravanan
In this article, optimum sizing and modeling of a stand-alone dc microgrid (DCMG) system for domestic applications with hybrid storage system is been proposed. The hybrid storage system consists of a lithium-ion battery (LIB) and supercapacitor (SC). The DCMG is designed to meet the load requirements of a house located in Aruppukottai, in the southern region of Tamil Nadu, India. The daily energy demand is estimated as 7.77 kWh with a peak load of 1.19 kW. This DCMG is designed and simulated by using Homer Pro software. The optimum sizing of solar photovoltaics (PVs), wind turbine (WT), LIB, and SC is evaluated based on cost of energy (CoE) and net present cost (NPC), and all feasible configurations are discussed. The feasible configurations include PV+LIB, PV+WT+LIB, WT+LB, PV+WT+SC, PV+SC, and WT+SC and are compared in terms of CoE and NPC. The results show that the PV+LIB architecture is the optimum configuration, with a CoE of ${$}$0.2/kWh and an NPC of $7,334.
{"title":"Optimum Sizing and Modeling of Stand-Alone DC Microgrid With Hybrid Energy Storage System for Domestic Applications: Cost of Energy, Net Present Cost, and Feasible Configurations","authors":"K. Karunanithi, S. Ramesh, S. Raja, Swaminathan Saravanan","doi":"10.1109/MSMC.2022.3229838","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3229838","url":null,"abstract":"In this article, optimum sizing and modeling of a stand-alone dc microgrid (DCMG) system for domestic applications with hybrid storage system is been proposed. The hybrid storage system consists of a lithium-ion battery (LIB) and supercapacitor (SC). The DCMG is designed to meet the load requirements of a house located in Aruppukottai, in the southern region of Tamil Nadu, India. The daily energy demand is estimated as 7.77 kWh with a peak load of 1.19 kW. This DCMG is designed and simulated by using Homer Pro software. The optimum sizing of solar photovoltaics (PVs), wind turbine (WT), LIB, and SC is evaluated based on cost of energy (CoE) and net present cost (NPC), and all feasible configurations are discussed. The feasible configurations include PV+LIB, PV+WT+LIB, WT+LB, PV+WT+SC, PV+SC, and WT+SC and are compared in terms of CoE and NPC. The results show that the PV+LIB architecture is the optimum configuration, with a CoE of ${$}$0.2/kWh and an NPC of $7,334.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"115 1","pages":"18-24"},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83470651","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}
Pub Date : 2023-04-01DOI: 10.1109/msmc.2023.3259475
{"title":"IEEE App","authors":"","doi":"10.1109/msmc.2023.3259475","DOIUrl":"https://doi.org/10.1109/msmc.2023.3259475","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134987384","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}
Pub Date : 2023-04-01DOI: 10.1109/msmc.2023.3250064
Tingwen Huang
{"title":"Optimization Theory and Application for Intelligent Systems [Editorial]","authors":"Tingwen Huang","doi":"10.1109/msmc.2023.3250064","DOIUrl":"https://doi.org/10.1109/msmc.2023.3250064","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"44 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72939313","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}
Pub Date : 2023-04-01DOI: 10.1109/MSMC.2022.3224843
Fiseha B. Tesema, J. Gu, Wei Song, Hong-Chuan Wu, Shiqiang Zhu, Zheyuan Lin, Min Huang, Wen Wang, R. Kumar
Addressee detection (AD) enables robots to interact smoothly with a human by distinguishing whether it is being addressed. However, this has not been widely explored. The few studies that have explored this area focused on a human-to-human or human-to-robot conversation confined inside a meeting room using gaze and utterance. These works used statistical and rule-based approaches, which tend to depend on specific settings. Further, they did not fully leverage the available audio and visual information or the short-term and long-term segments, and they have not explored combining important conversation cues—the facial and audio features. In addition, no audiovisual spatiotemporal annotated dataset captured in mixed human-to-human and human-to-robot settings is available to support exploring the area using new approaches.
{"title":"Addressee Detection Using Facial and Audio Features in Mixed Human–Human and Human–Robot Settings: A Deep Learning Framework","authors":"Fiseha B. Tesema, J. Gu, Wei Song, Hong-Chuan Wu, Shiqiang Zhu, Zheyuan Lin, Min Huang, Wen Wang, R. Kumar","doi":"10.1109/MSMC.2022.3224843","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3224843","url":null,"abstract":"Addressee detection (AD) enables robots to interact smoothly with a human by distinguishing whether it is being addressed. However, this has not been widely explored. The few studies that have explored this area focused on a human-to-human or human-to-robot conversation confined inside a meeting room using gaze and utterance. These works used statistical and rule-based approaches, which tend to depend on specific settings. Further, they did not fully leverage the available audio and visual information or the short-term and long-term segments, and they have not explored combining important conversation cues—the facial and audio features. In addition, no audiovisual spatiotemporal annotated dataset captured in mixed human-to-human and human-to-robot settings is available to support exploring the area using new approaches.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"13 1","pages":"25-38"},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78284081","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}
Pub Date : 2023-04-01DOI: 10.1109/msmc.2023.3238124
S. Kwong
{"title":"Looking Back on the Achievements of the IEEE SMC Society in 2022 [President’s Message]","authors":"S. Kwong","doi":"10.1109/msmc.2023.3238124","DOIUrl":"https://doi.org/10.1109/msmc.2023.3238124","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"23 11 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82922528","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}
Pub Date : 2023-04-01DOI: 10.1109/MSMC.2022.3218423
H. M. D. Kabir, Moloud Abdar, A. Khosravi, D. Nahavandi, S. Mondal, Sadia Khanam, Shady M. K. Mohamed, D. Srinivasan, Saeid Nahavandi, P. N. Suganthan
In this article, we propose ten synthetic datasets for point prediction and numeric uncertainty quantification (UQ). These datasets are split into the train, validation, and test sets for model benchmarking. Equations and the description of each dataset are provided in detail. We also present representative shallow neural network (NN) training and random vector functional link (RVFL) training examples both of which are training models for the point prediction. We perform UQ with the consideration of a Gaussian and homoscedastic distribution. Distribution considerations and models are made quite simple for the following reasons: 1) much room exists for further explorations and improvements, 2) users of the dataset have simple training examples including the process of accessing data, and 3) users get an idea of probable result and the format of the result. The dataset and scripts are available at the following link: https://github.com/dipuk0506/UQ-Data.
{"title":"Synthetic Datasets for Numeric Uncertainty Quantification: Proposing Datasets for Future Researchers","authors":"H. M. D. Kabir, Moloud Abdar, A. Khosravi, D. Nahavandi, S. Mondal, Sadia Khanam, Shady M. K. Mohamed, D. Srinivasan, Saeid Nahavandi, P. N. Suganthan","doi":"10.1109/MSMC.2022.3218423","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3218423","url":null,"abstract":"In this article, we propose ten synthetic datasets for point prediction and numeric uncertainty quantification (UQ). These datasets are split into the train, validation, and test sets for model benchmarking. Equations and the description of each dataset are provided in detail. We also present representative shallow neural network (NN) training and random vector functional link (RVFL) training examples both of which are training models for the point prediction. We perform UQ with the consideration of a Gaussian and homoscedastic distribution. Distribution considerations and models are made quite simple for the following reasons: 1) much room exists for further explorations and improvements, 2) users of the dataset have simple training examples including the process of accessing data, and 3) users get an idea of probable result and the format of the result. The dataset and scripts are available at the following link: https://github.com/dipuk0506/UQ-Data.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"39 1","pages":"39-48"},"PeriodicalIF":3.2,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77056407","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}
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