• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.1
• /
• pp.280-294
• /
• 2023

Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.6
• /
• pp.1728-1742
• /
• 2023

In this paper, we extended a hierarchical clustering technique, which is the most researched in the sensor network field, and studied a dynamic differential clustering technique to minimize energy consumption and ensure equal lifespan of all sensor nodes while considering the mobility of sinks. In a sensor network environment with mobile sinks, clusters close to the sinks tend to consume more forwarding energy. Therefore, clustering that considers forwarding energy consumption is desired. Since all clusters form a hierarchical tree, the number of levels of the tree must be considered based on the size of the cluster so that the cluster size is not growing abnormally, and the energy consumption is not concentrated within specific clusters. To verify that the proposed DDC protocol satisfies these requirements, a simulation using Matlab was performed. The FND (First Node Dead), LND (Last Node Dead), and residual energy characteristics of the proposed DDC protocol were compared with the popular clustering protocols such as LEACH and EEUC. As a result, it was shown that FND appears the latest and the point at which the dead node count increases is delayed in the DDC protocol. The proposed DDC protocol presents 66.3% improvement in FND and 13.8% improvement in LND compared to LEACH protocol. Furthermore, FND improved 79.9%, but LND declined 33.2% when compared to the EEUC. This verifies that the proposed DDC protocol can last for longer time with more number of surviving nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.9
• /
• pp.2590-2608
• /
• 2023

The high-altitude and mobility characteristics of unmanned aerial vehicles (UAVs) have made them a key element of new radio systems, particularly because they can exceed the limits of terrestrial networks. However, at high altitudes, UAVs can be significantly affected by intercell interference at a high line-of-sight probability. To mitigate this drawback, we propose an algorithm that selects the optimal beam to reduce interference and maximize transmission efficiency. The proposed algorithm comprises two steps: constructing a user-location-based fingerprint database according to the user types presented herein and cooperative beam selection. Simulations were conducted using cellular cooperative downlink systems for analyzing the performance of the proposed method, and the signal-to-interference-plus-noise cumulative distribution function and spectral efficiency cumulative distribution function were used as performance analysis indicators. Simulation results showed that the proposed algorithm could reduce the effect of interference and increase the performance of the desired signal. Moreover, the algorithm could efficiently reduce overheads and system cost by reducing the amount of resources required for information exchange.

• ETRI Journal
• /
• v.45 no.5
• /
• pp.887-898
• /
• 2023

Aerial base stations (ABSs) seem promising to enhance the coverage and capacity of fifth-generation and upcoming networks. With the flexible mobility of ABSs, they can be positioned in air to maximize the number of users served with a guaranteed quality of service (QoS). However, ABSs may be overloaded or underutilized given inefficient placement, and user association has not been well addressed. Hence, we propose a three-dimensional ABS placement scheme with a delay-QoS-driven user association to balance loading among ABSs. First, a load balancing utility function is designed based on proportional fairness. Then, an optimization problem for joint ABS placement and user association is formulated to maximize the utility function subject to statistical delay QoS requirements and ABS collision avoidance constraints. To solve this problem, we introduce an efficient modified gray wolf optimizer for ABS placement with a greedy user association strategy. Simulation results demonstrate that the proposed scheme outperforms baselines in terms of load balancing and delay QoS provisioning.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.881-902
• /
• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.6
• /
• pp.1462-1477
• /
• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.26 no.2
• /
• pp.15-32
• /
• 2024

Modern fashion manifests in forms that mirror the diverse lifestyles and personalities of consumers. It transcends mere aesthetic designs and embodyies practicality. There is a preference for comfortable, highly functional attire, leaning towards easy wear. Casual wear, in particular, embraces a sense of freedom not found in standard business attire. It seeks a comfortable, natural silhouette through tactile fabrics rather than sportswear. Loose, drop shoulder sleeves enhance comfort and mobility and often become key elements in casual wear designs. Given that clothing must balance aesthetics with functionality, especially across various activities, it is natural to prioritize functional design. Research on patterns suited for dynamic conditions is imperative. The rise of drop shoulder styles necessitates the development of corresponding sleeve patterns. It is crucial to differentiate pattern drafting methods due to the resulting silhouette variations. This study aims to categorize drop shoulder pattern drafting techniques based on shoulder extension and angle dimensions. Each method will be examined, and drop shoulder sleeve patterns and wear forms will be studied using a 3D virtual system. This research holds significance in providing valuable insights and foundational data for designing diverse drop shoulder sleeve patterns, contributing to their practical development and advancement.

• Journal of the Society of Naval Architects of Korea
• /
• v.61 no.4
• /
• pp.226-235
• /
• 2024

A method for quantifying the adaptability of ship maneuver scenarios for data-driven modeling of ship dynamics is developed based on the principal component analysis. A random maneuver scenario is suggested as a reference for ship dynamics, which can obtain the converged principal components of ship dynamics features by the Monte Carlo simulation. Principal components of conventional maneuver scenarios defined by the International Maritime Organization (IMO) are compared to that of the random maneuver. A conventional ship dynamics model for a container carrier vessel for four degrees of freedom dynamics is introduced to simulate the random and IMO maneuver scenarios. It is confirmed that the IMO tests follow the tendency of random maneuver scenario in terms of execution time and adaptability.

• Journal of the Society of Naval Architects of Korea
• /
• v.61 no.4
• /
• pp.247-257
• /
• 2024

The present study suggests a data-driven multivariate identification method based on principal component analysis and shows an application to ship dynamics modeling in maneuver. A reduced order model of ship dynamics is built by linear combination of three principal components acquired from large angle zigzag maneuver test. For a given kinematic state with three variables, a proper span is found by least square method, therefore accompanying hydrodynamic force and moment is determined. Suggested dynamics model correctly estimates hydrodynamic force and moment, thus it showed good agreement in maneuver simulation with that of conventional ship dynamics model obtained by system identification of captive model tests.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.27 no.5
• /
• pp.611-618
• /
• 2024

5G New Radio(NR) technology, with its focus on high speed, low latency, and connectivity, introduces crucial advancements like MIMO for enhanced reliability and transmission rates, edge computing for reduced latency, and IAB for extended coverage. However, military communication networks face challenges such as limited capacity, unpredictable mobility and communication dead zones. This paper delves into the trends of the above 5G NR technologies outlined by the 3GPP standard, exploring their potential applications within military infrastructure networks. Our aim is to underscore the benefits of harnessing these technologies in military settings. Additionally, through simulation, we forecast the advantages associated with integrating these core 5G NR technologies, thereby paving the way for enhanced military communication capabilities.