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Optimizing 3D Flight Paths for Multiple UAVs with Connectivity Management in Urban Delivery Systems 19

Optimizing 3D Flight Paths for Multiple UAVs with Connectivi...

引用

19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Lee, Yeongmin Syahran, Raihan Muhammad Spangenberger, Mael Yang, Huigyu Oh, Jiyong Choo, Hyunseung Dept. of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of Convergence Research Institute Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of Informatics Télécom SudParis Évry France

ISBN: (纸本)9798331507817

The dynamic deployment of aerial vehicles in urban delivery scenarios demands precise route planning, reliable data links, and efficient use of network infrastructure. Although prior efforts have explored various aspects of unmanned navigation or communication optimization, existing approaches often overlook the combined impact of three-dimensional path selection and robust connectivity maintenance. To address this gap, this paper proposes a deep reinforcement learning framework employing Independent Proximal Policy Optimization (IPPO) to steer the flight paths of unmanned vehicles while curtailing needless interactions with base stations (BSs). By incorporating communication-specific metrics, Reference Signal Received Power (RSRP), the proposed system adapts to urban conditions and upholds resilient network links. Comprehensive performance evaluations reveal the potential of the framework to reduce excessive BS connections by up to 82.24%, preserve RSRP levels above -80 dBm, and balance handover frequencies across flight trajectories. These findings affirm the scalability and effectiveness of the method for achieving efficient aerial navigation and consistent communication in urban delivery services. © 2025 IEEE.

关键词： Deep reinforcement learning

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Topic Relation Graph Construction to Identify Challenges in Introducing Programming in Indonesian K-12 Education 1

Topic Relation Graph Construction to Identify Challenges in ...

引用

1st IEEE International Conference on Smart Technology, ICE-SMARTec 2023

作者： Ayub, Mewati Karnalim, Oscar Toba, Hapnes Wijanto, Maresha Caroline Dulimarta, Hans Saputra, Williyandie Kotambunan, Tabitha Emanuella Master Program of Computer Science Maranatha Christian University Bandung Indonesia Ewha Womans University Dept. of Computer Science and Engineering Seoul Korea Republic of School of Computing Grand Valley State University MI United States Informatics Engineering Maranatha Christian University Bandung Indonesia

ISBN: (纸本)9798350306156

Programming can help K-12 students to develop their 21st-century core skills. Despite the benefits, programming is not common to be delivered in Indonesian K-12 education. There is a need to understand potential challenges in introducing programming to K-12 students. We developed a questionnaire survey covering four identified dimensions of challenges: administrative, facilities, teachers, and students. We also asked about common programming assessments and their preferred software features for teaching programming. Forty K-12 teachers were invited to complete the survey. The responses were analyzed with thematic analysis using a bigram-based Latent Dirichlet Allocation topic modeling and descriptive statistics. Our study shows that the challenges include limited learning modules, an insufficient number of computers, limited programming skills, and limited computational thinking skills. Scratch was the most common programming language used and many programming assessments were about debugging a program or writing a small program. Visualization and animation can be helpful in teaching programming. © 2023 IEEE.

关键词： Students

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Channel Attention HalfU-Net for Skin Lesion Segmentation 1

Channel Attention HalfU-Net for Skin Lesion Segmentation

引用

1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Prasetyo, Heri Mahdy, Abid Ammar Nadhif, Abrar Dwi Fairuz Guo, Jing-Ming Hsia, Chih-Hsien Department of Informatics Surakarta Indonesia National Taiwan Univ. Sci. Technolgy Department of Electrical Engineering Taipei Taiwan National Ilan University Dept. Computer Sci. Infor. Engineering Yilan Taiwan

ISBN: (纸本)9798350306484

U-shaped architecture have gain popularity in the image segmentation task, especially for biomedical image. Regardless of its good performance, U-shaped architecture generally has huge number of parameters. Considering the resource constraint in actual medical environment, the needs lightweight model is essential. In order to overcome this problem, we propose Channel Attention HalfU-Net. The proposed method implement the existing medical image segmentation model named HalfU-Net. HalfU-Net can reduce the computational cost by simplify the decoder part of the UNet. Channel attention is assigned between ghost model for every stage in encoder part to capture more relevant feature. This leads to performance improvement in skin lesion segmentation problem. Despite that our model achieve state-ofthe-arts performance by surpassing U-Net in aspects of DSC and IoU metrics by 0.86% and 3.48% respectively, the number of parameter of our proposed method is more than 200 times less then U-Net. © 2023 IEEE.

关键词： Image segmentation

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Causal Structure Learning from Imperfect Longitudinal Data in Healthcare 11

Causal Structure Learning from Imperfect Longitudinal Data i...

引用

11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Yang, Haoyu Tourani, Roshan Li, Jia Caraballo, Pedro Steinbach, Michael Kumar, Vipin Simon, Gyorgy University of Minnesota Dept. of Computer Science and Engineering Minneapolis United States University of Minnesota Institute for Health Informatics Minneapolis United States Mayo Clinic Dept. of Internal Medicine Rochester United States

ISBN: (纸本)9798350302639

Causal Structure Discovery (CSD) is the task of learning the set of underlying causal relationships from observational data. Due to their computational scalability and flexibility, a recently developed class of CSD methods, NOTEARS, based on a formulation allowing for continuous optimization, is gaining popularity. However, this formulation can lead to incorrect edge orientations when little/no likelihood advantage is conferred upon any edge orientation, e.g., a → b → c versus c → b → a. In longitudinal data, like electronic health records (EHRs), temporal relationships are observable among many pairs of variables. Such temporal relationship is imperfect but still suggest an orientation since causal effects cannot travel backwards in time. Following this idea, we propose methods to incorporate precedence constraints into continuous optimization-based CSD methods. Experiments on both a synthetic and two real-world datasets validate the effectiveness of the proposed precedence constraints. © 2023 IEEE.

关键词： Machine learning

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WebRTC-based Resource Offloading in Smart Home Environments

WebRTC-based Resource Offloading in Smart Home Environments

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Jeong, Hunseop Lee, Taehyung Eom, Young Ik Sungkyunkwan University Dept. of Digital Media and Communications Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9781665441544

Web platforms face new demands for emerging applications, which use machine learning models such as pose recognition or object detection. These models require significant computing powers in processing enormous inputs such as images or audios for machine learning computation. These demands are also being generated in smart home appliances based on web platforms. Unfortunately, smart home appliances do not generally have built-in input devices, such as cameras or microphones, due to privacy issues and have limited performance compared to mobile devices. This paper proposes a WebRTC-based resource offloading system for web applications, which allows smart home appliances to use resources of nearby mobile devices as if the resources are their own. We implemented the proposed system, performed experiments on the resource offloading framework, and evaluated the performance using five computation-intensive web applications, which use a machine learning model. Our system was able to run machine learning models, through resource offloading to mobile devices, on smart home appliances without an attached camera, and achieved up to 1.5x speedup, compared to local execution with a camera. © 2022 IEEE.

关键词： Domestic appliances

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Generating Automated Assistance Mechanism in Android Programming Self-learning System Using Automatic Testing Tools

Generating Automated Assistance Mechanism in Android Program...

引用

2023 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2023

作者： Syaifudin, Yan Watequlis Liliana, Dewi Yanti Kaswar, Andi Baso Fatmawati, Triana Funabiki, Nobuo Siradjuddin, Indrazno State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Jakarta Dept. of Informatics Engineering Jakarta Indonesia State University of Makassar Dept. of Computer Engineering Makassar Indonesia Okayama University Dept. of Elec. and Comm. Engineering Okayama Japan State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia

ISBN: (纸本)9798350307771

Nowadays, computer-assisted learning (CAL) has experienced a significant increase in demand for self-learning purposes with the mechanism of automated assistance to facilitate assessments and provide instant feedback to learners. Using automatic testing, test cases can be executed repeatedly, providing informative feedback to assist students in correcting the written code referring to the assignment specifications. This research experiences an automated testing mechanism in an Android programming self-learning system to serve several important functions for learning experience enhancement. By adopting the TDD method and utilizing automatic software testing tools, the testing process combines unit testing with JUnit and integration testing with Robolectric. It ensures the quality and functionality of the application under test based on learning assignment's specifications. Utilizing the assertion methods realizes the code verification referring to expected behavior and potentially produces informative feedback that can be captured to provide automated assistance. Evaluation through the test code implementation in the Basic Application learning topic shows that automatic testing tools cover the automated assistance feature in the validations of project configuration and UI components. © 2023 IEEE.

关键词： Specifications

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Borneo Smart Forest Information System for Management of Dipterocarp Plants in Kalimantan Rainforest 8

Borneo Smart Forest Information System for Management of Dip...

引用

8th IEEE Information Technology International Seminar, ITIS 2022

作者： Wati, Masna Puspitasari, Novianti Hairah, Ummul Widians, Joan Angelina Septiarini, Anindita Tjikoa, Ade Fiqri Universitas Mulawarman Faculty of Engineering Dept. of Informatics Samarinda Indonesia Universitas Gadjah Mada Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350398199

Kalimantan's tropical rainforest is home to indigenous plants of the Dipterocarpaceae family (tribe), which is renowned for having the most endemic species. Dipterocarp is a family of pantropical plants, many of which are used in the wood industry. This study aims to provide information on the potential of Dipterocarp in Kalimantan forests. Education and conservation efforts for Dipterocarp trees, a prominent component of the forest ecosystem, are crucial in light of the significant harm done to Kalimantan's rainforests. The authors develop the Borneo Smart Forest information system. This system digitally organizes data on the diversity of Dipterocarp in the Kalimantan rainforest based on Web and QR-Code technology. Borneo Smart Forest (BSF) system for monitoring plant inventory and plant markers can be read by smartphones using QR codes. It gives visitors a comprehensive overview of the plants. A QR code is a printed, two-dimensional barcode with limited space for data storage. This technology allows the plant to show earlier administrator-made additions to the inventory information system. The QR code will direct the user to the BSF website, which has data about the plants. The development of this system is one of the efforts to support the achievement of Dipterocarp conservation. © 2022 IEEE.

关键词： Information systems

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Applied Virtual Reality in 3D Geometry 7

Applied Virtual Reality in 3D Geometry

引用

7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Sakkas, Konstantinos Tsogka, Alexandra Giannakeas, Nikolaos Tzimourta, Katerina D. Tzallas, Alexandros T. Glavas, Euripidis University of Ioannina Department of Informatics and Telecommunication Arta Greece University of Western Macedonia Dept. of Electrical and Computer Engineering Kozani Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

The development of Virtual Reality technologies has improved people's daily lives in many sections. Nowadays, it is applied in fields such as Health, Work, Telecommuting and in a large number of other sectors. Education from different perspectives is something that constantly concerns researchers and virtual reality developers, which is why we come across a series of virtual reality applications for situation simulation and student education. Mathematics and especially geometry which is interrelated with the concept of the implementation of applications in three-dimensional space, as well as VR applications, from the perspective of learning are often considered complicated as there are three-dimensional objects that are not easily perceived only through a book. In this paper we examine how through virtual reality geometric concepts can be better understood but at the same time to examine geometric shapes from different angles and perspectives. © 2022 IEEE.

关键词： Geometry

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Analysis of Emotions through the Use of Physiological Signals 7

Analysis of Emotions through the Use of Physiological Signal...

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7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Sakkas, Konstantinos Tsogka, Alexandra Gkimitzoudis, Athanasios Giannakeas, Nikolaos Tzimourta, Katerina D. Tsipouras, Markos Glavas, Euripidis Tzallas, Alexandros T. University of Ioannina Department of Informatics and Telecommunication Arta Greece University of Western Macedonia Dept. of Electrical and Computer Engineering Kozani Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Emotion is a psychosomatic process that is caused either by a conscious or non-conscious perception of an object or a situation whereas, the result of that process is depicted either by the expression of the face, or physically, or with a combination of the above. An important mechanism playing a significant role in the recognition of emotions is the encephalogram, which enables us to detect significant signals of the brain. The methodology developed aims to the identification of basic emotions by using an electroencephalogram through an experimental process where participants were asked to evaluate the experiment according to the valence, arousal and dominance of each emotion inflicted on them by videos they were subjected to watching. Through the experimental process, a vector of characteristics is analyzed for each of the electrodes of the electroencephalogram and for a series of videos. The training of a model and classification of algorithms were the key to finding the best methods in terms of sensitivity, accuracy, and specification of our data. © 2022 IEEE.

关键词： Machine learning

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Adaptation of Natural Gradient Boosting Model for Production Environment 4

Adaptation of Natural Gradient Boosting Model for Production...

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4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Tyurin, Alexey Sergeevich Saraev, Pavel Viktorovich Lipetsk State Technical University Dept. of Informatics and Computer Engineering Lipetsk Russia Lipetsk State Technical University Lipetsk Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

Application of mathematical models in a production environment is associated with solving many complex engineering and analytical problems, one of which is to evaluate the quality of such a model and assess the economic and technological effect. The paper shows how the worst model according to classical metrics can show the best results in production. © 2022 IEEE.

关键词： Training Economics Adaptation models Temperature distribution Time series analysis Production Mathematical models

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