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最佳論文
- 會議名稱：
The 8th International Conference on Innovative Computing(IC2025)
- 論文摘要：
This study explores the integration of Internet of Things (IoT), Virtual Reality (VR), and Big Data technologies in personalized athletic assessment and training systems. Our experimental results reveal that the integration of IoT, VR, and Big Data offers significant benefits for athletic training by providing tailored feedback that enhances users' awareness of their performance, helping to improve training outcomes.
- 會議名稱：
2024 Antenna Measurement Techniques Association (AMTA)
- 論文摘要：
Non-terrestrial networks (NTNs), including satellites, high-altitude platforms (HAPS), and unmanned aerial vehicles (UAVs), operate above the Earth’s surface. Along with ground base stations, they often require the implementation of beamforming and beam tracking techniques to achieve high-speed, low-latency transmission, thereby ensuring seamless coverage. Consequently, diagnosing the functionality of the radio units (RUs) in those network devices and verifying their beamforming patterns are critical for the effective applications of this technology. This paper presents the 3D far-field pattern measurements and calibrations of the RF carrier EIRP levels for millimeter-wave beamforming testing suites that emulate RU operations. This is achieved using a combination of the planar near-field (PNF) and compact antenna test range (CATR) measurement systems at Taiwan Tech. A side-deployed PNF scanner is used in over-the-air (OTA) scan mode for 3D antenna pattern measurement and aperture diagnosis of the RU devices in transmit mode, utilizing controlled scan beams of single-tone and modulated RF carriers. Additionally, a compact range (CR) mode is employed to calibrate the RF EIRP in the peak direction of each RU-scanned beam. Beamforming patterns obtained from the near-field measurements in the OTA scan mode demonstrate good agreements with conventional near-field tests and show reliable EIRP values at 28 GHz for 5G FR2 radio units.
- 會議名稱：
IEEE ICKII 2024
- 論文摘要：
This study introduces IVA-PBC, an innovative intelligent virtual assistant designed specifically for cloud data centers. Developed on the CHT-PBC framework, IVA-PBC utilizes a cloud-native architecture. It offers lightweight and highly packaged business functionalities, integrating cohesive and loosely coupled functional modules to achieve agile development goals. Additionally, the modular nature of CHT-PBC allows for seamless integration among PBC instances, thus enabling enhanced capabilities. By integrating IVA-PBC with existing cloud IDC management PBC, it facilitates the development of value-added applications, thereby establishing a cutting-edge 3D intelligent assistant service that provides domain expertise and business support within a cloud IDC management PBC. This study also provides an overview of the CHT-PBC framework. With the successful implementation of the CHT-PBC framework by Chunghwa Telecom, this architecture holds significant potential for adoption across various industries, particularly as businesses actively embrace digital transformation.
- 會議名稱：
2024 2nd International Conference on Artificial Intelligence and Power Engineering
- 論文摘要：
4K video frame interpolation is challenging due to the large motion and unexpected occlusion between two consecutive frames. To address this challenge, we propose the Flow Upscaling Network for 4K Video Frame Interpolation, denoted as FUN-VFI. Specifically, it consists of two main modules, global flow flied estimation and adjustable upscaler. In global flow field estimation, the flow estimator predicts bilateral flow fields between two downscaled consecutive frames. Subsequently, we iteratively enhance these bilateral flow fields using the adjustable upscaler. the core of upscaler is ConvNext block, a pure CNN model that can rival vision transformers while preserving the simple structure and efficient runtime of convolution neural networks. Last, we warp two consecutive input frames using refined flow fields and blend them to generate the reconstructed intermediate frame. Experimental results demonstrate that proposed method achieves outstanding performance across diverse benchmark datasets. Furthermore, compared with existing methods like M2M-PWC and BI-Former, FUN-VFI accelerates inference times by approximately 2-6 times at 4K resolution, while consistently delivering superior outcomes.
- 會議名稱：
IEEE International Conference on Electronic Communications, Internet of Things and Big Data Conference 2024 (IEEE ICEIB 2024)
- 論文摘要：
Traditional virtualized services are gradually transitioning to containerized services with telecom shifts towards cloud-native. Additionally, governments have been actively striving to improve energy consumption efficiency to reduce environmental impact in recent years. Therefore, managing the power consumption of containerized network services and achieving energy-saving benefits has attracted attention in telecom, such as containerized network functions. This paper proposes an architecture and method for monitoring the power consumption of containerized network services in the telco cloud, aiming to measure the utilization of telecom containerized network services and quantify power consumption to support telecom service auto-scaling and equipment power dynamic control.
- 會議名稱：
IEEE ICEIB 2023 - International Conference on Electronic Communications, Internet of Things and Big Data
- 論文摘要：
Handover (HO) is the key function to maintaining users’ connections while moving within the coverage of cellular communication networks. During the HO process, it is possible to decrease the data throughput and cause interruptions of time-critical services. In addition, the HO signal processes between the mobile phone and the mobile network increase energy consumption for both of them. These problems are even more complex in the 5G era because of the co-existence of macro- and micro-cell (ultra-dense small cells), and different deployment architectures, such as non-standalone (NSA) and standalone (SA). To investigate HO behaviors in real 5G networks, we collected a rich mobile signal dataset consisting of 2 sets of repeated driving trips under a 5G commercial NSA network in Taoyuan, Taiwan. Based on the dataset, we analyze and compare the HO sequential frequent patterns and the probability of the occurrence of ping-pong HO for the 2 driving routes. The results show the HO frequent patterns with high support can be found, and several ping-pong events occur repeatedly at the same position. Several observations are described to discuss the value of utilizing the dataset and design AI-assisted HO algorithms for decreasing ping-pong effects and unnecessary HO events.
SCI期刊(2024-2025)
- 期刊名稱：
IEEE ACCESS
- 論文摘要：
The state-of-the-art study, "L-ECQV: Lightweight ECQV Implicit Certificates for Authentication in the Internet of Things," eliminates the need for a signature within the certificate using Elliptic Curve Qu-Vanstone (ECQV) and introduces a lightweight ECQV implicit certificate structure to significantly reduce the certificate length within packets. This is a noteworthy research achievement. Building on this foundation, the current study integrates the Certificate Digest Method, allowing each packet to carry only the certificate digest rather than the full certificate, further reducing packet size. Additionally, by utilizing pre-stored public keys, this study avoids the need to reconstruct the actual public key using reconstruction data and the certificate authority's public key during each signature verification. In the experimental setup, this study was implemented on a Raspberry Pi 4 Model B and evaluated the computational efficiency across different National Institute of Standards and Technology (NIST) and Brainpool elliptic curves.
- 期刊名稱：
IEEE ACCESS
- 論文摘要：
The state-of-the-art study, "Exploring Secure V2X Communication Networks for Human-Centric Security and Privacy in Smart Cities," proposed a blockchain-based vehicular network framework designed to enhance communication security and protect vehicle privacy in vehicle-to-everything (V2X) communications. The proposed framework validates vehicle legitimacy using individual certificates and subsequently transmits data collected and integrated by intermediate entities to the blockchain, thereby avoiding direct exposure of vehicle privacy. However, the framework does not prevent intermediate entities from accessing vehicle privacy, leaving vehicles vulnerable to tracking and monitoring by these entities. In response to this limitation, this study proposes a key expansion method based on elliptic curve cryptography (ECC). This approach employs a two-stage key expansion process, referred to as "butterfly key expansion," to ensure that vehicle privacy is not exposed to any device within the V2X communications. Experimental results demonstrate that the key expansion time does not significantly differ from the key generation time. Furthermore, the signature generation and verification times using the expanded keys are comparable to those of the original keys. These findings indicate that the proposed method achieves enhanced privacy protection without imposing additional computational overhead.
- 期刊名稱：
International Journal of Web and Grid Services
- 論文摘要：
This paper presented an adaptive proportional derivative adjuster (APDA) notch filter for ECG signal processing. Electrocardiography (ECG) signal detection technologies have been a research topic in health care fields. The ECG signal have different interference, especially that of 60Hz environment electromagnetic fields in user static state measurement. Traditional adaptive filter algorithms adjusted filter parameters base on ECG mathematical model. However, the different user has different ECG model and hardware measurement structure have different seriousness of 60Hz environment electromagnetic fields. This paper proposed a real time adaptive filter base on proportional derivative adjuster to reduce ECG signal serious 60Hz interference signal coupled issue, in which APDA Notch Filter detected ECG status and simplified ECG system model obtained adaptive law parameters upgrading filter which not need train ECG mathematical model. We implemented a real time adaptive filter base on proportional derivative adjuster in wearable device and real time feedback output response to PC analysis. In the experimental results, the APDA real time adjusted parameters to improve ECG environment noise issue.
- 期刊名稱：
MDPI Sensors Journal
- 論文摘要：
As the Metaverse continues to evolve, Virtual Reality (VR) is emerging as a cornerstone for building immersive and socially interactive digital environments. However, current VR systems face several limitations, including high hardware demands, platform incompatibilities, and challenges in enabling seamless multiplayer experiences. VR streaming presents a promising solution by offloading computational workloads to remote servers, thereby delivering high-quality VR experiences to a wider audience, including users with lower-end devices.
In this paper, we introduce "Loka", a cross-platform VR streaming framework designed to address these challenges and empower Metaverse applications with scalable, accessible, and interactive capabilities. Built on the Unity Engine and WebRTC, Loka eliminates the need for device-specific SDKs, enabling consistent cross-platform deployment. It supports real-time integration of custom sensory data—such as motion capture and physiological signals from IoT devices—enhancing user immersion, personalization, and research applications within virtual environments.
Loka also features built-in multiplayer and multicasting support, fostering synchronous collaboration and social interaction—core elements of the Metaverse vision. By leveraging cloud-based rendering and low-latency streaming, Loka ensures smooth, high-fidelity VR experiences on a broad spectrum of devices. Its modular architecture facilitates extensibility, allowing developers and researchers to incorporate new data types, functionalities, and experimental setups with ease.
Overall, Loka offers a flexible and powerful foundation for immersive, socially connected VR experiences in the emerging Metaverse landscape.
- 期刊名稱：
IEEE ACCESS
- 論文摘要：
With the rapid advancement of computer vision technology, various deepfake tools for generating deceptive images have emerged. Generative Adversarial Networks (GANs) can create various deceptive media streams, including images, audio, and video, leading to numerous societal challenges. Palmprint recognition technology has recently been applied in financial identity verification, particularly in confirming transactions across various banking platforms. Manipulating critical financial transactions or generating malicious images to deceive authentication processes can result in significant disruptions. Convolutional Neural Networks (CNNs) are considered practical tools. We propose the implementation of a Dual Cascade Convolutional Neural Network (DC-CNN) algorithm that utilizes a dual-channel technique. This approach involves two networks that train one subnetwork and then apply the same configuration to the other. The feature vectors are combined, the fake inputs can be identified. This dual-channel technique is particularly effective for detecting forged images. Our approach involves comparing various CNN architectures, such as MesoNet, MesoInceptionNet, and Dense CNN (D-CNN), within the framework of GAN methods, such as Wasserstein GAN (WGAN) and Cycle GAN. In our experiments, DC-CNN demonstrates favorable results in detecting fake palmprints based on WGAN and cycle GAN. Specifically, for WGAN-based fake palmprints, the model achieved the precision of 98.20%, recall of 87.73%, F1 scores of 92.67% and accuracy of 90.20%. In the case of Cycle GAN-based fake palmprints, the model exhibited the precision of 91.71%, recall of 88.89%, F1 scores of 90.28% and accuracy of 87.91%. Therefore, DC-CNN emerges as a promising approach in the fields of deepfake palmprint detection and identity verification.