Remote communication via avatars in the metaverse has attracted much attention. However, in a PC environment that doesn’t have the motion tracking of a VR headset, it is difficult to determine whether the user's avatar has been continuously participating in a conversation. In this paper, we propose a communication system that represents whether avatars have been continuously participating in a conversation by reflecting users’ nods in avatars and changing the transparency of avatars according to how often they nod in a PC-based metaverse environment. In this study, a prototype was actually developed and evaluated through an evaluation experiment. As a result, it was shown that by changing the avatar's transparency according to how often it nods, it becomes clearer compared to using only the nodding function whether the avatar is listening or not, and whether it has been continuously participating in the conversation or not. The feedback method, reflected in the avatar's transparency change, is expected to be one future way to support communication in the metaverse using avatars.
In recent years, there are increasing demands in manufacturing industry for flexible production systems capable of handling high-mix, low-volume manufacturing, along with a growing population of elderly workers. As a result, reducing workers’ physical burdens and optimizing workspace layouts are urgent challenges. In particular, in repetitive tasks such as assembly and inspection performed at desks, the layout of equipment, worker posture, and movement trajectories between tasks significantly impact the operational efficiency and physical strain. Conventional methods often address these elements independently, resulting in limited effectiveness in achieving integrated spatial optimization. This paper proposes a mathematical optimization model that simultaneously optimizes worker postures, equipment layouts, and task-to-task trajectories for repetitive desk-based operations in manufacturing environments. The proposed method formulates constraints on equipment placement and worker posture by a Mixed-Integer Linear Programming (MILP) model, and integrates it with an A* pathfinding that accounts for obstacles and spatial constraints, enabling the derivation of practical workspace configurations. Furthermore, the model incorporates a dynamic optimization mechanism that reconstructs postures and paths across the entire task cycle during repetitive work, thereby aiming to balance long-term efficiency and safety. Simulation results confirm the effectiveness of the proposed method, demonstrating improvements in trajectory efficiency, reduction of postural strain, and rationalization of inter-equipment distances when compared with conventional layouts.
In this paper, we explore cutting-edge systems for tracking and monitoring cattle, with special attention to camels. We examine technologies like GPS, RFID tags, and wireless sensor networks to understand how each helps farmers manage animal behavior and movement. Our research shows how combining these tools with data analytics and machine learning makes tracking more effective. We discuss the pros and cons of injectable RFID tags, challenges with radio collars, and how IoT systems could revolutionize health monitoring. We also look at how computational systems spot health issues early by analyzing behavior patterns through satellite imagery and sensor data. These technologies give farmers unprecedented insight and control, boosting efficiency and sustainability in camel farming. In our tests, the wireless sensor network predicted theft with 92
NDN-VANET has been developed to enable robust end-to-end communication in VANETs, which are vulnerable networks due to the mobility of vehicles. The NDN functionality enables fast content delivery through network caching and content-centric communication. However, standard NDN does not incorporate any mechanism for priority control based on the significance of the requested data. This paper proposes a new caching method that utilizes spatial locality, based on context awareness of vehicular itineraries. Performance evaluation results confirm that the proposed method effectively improves the cache hit ratio enabling fast delivery of emergency content.
In recent years, for realizing a sustainable society, the deployment of renewable energy such as photovoltaic (PV) power and vehicles that emit no CO_2 , such as electric vehicles (EVs), is highly expected. On the other hand, due to large fluctuations in power generation throughout the day, further utilization of PV induces the duck curve, which degrades the efficiency of traditional thermal power generation. This paper discusses how to utilize PV while mitigating the duck curve by using battery swapping EVs (BSEVs). The proposed system uses the storage capacity of battery swapping stations (BSSs), which hold spare batteries for BSEVs, as stationary batteries for electricity time-shifting. In addition, the proposed system incorporates the mobility of BSEVs to coordinate capacity among BSSs, thereby improving the utilization of PV. To enable this coordination, the system employs two methods to mitigate traffic congestion caused by BSEV operations. This paper clarifies that these two methods effectively alleviate the duck curve though the performance evaluations.
