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This study aims to solve the problem that both the speed and the required driving power of electric vehicles (EVs) will change during the dynamic wireless charging (DWC) process, making it difficult to charge EVs with a constant power considering the overall efficiency of DWC system, the numbers of EVs and the power supply capacity. Therefore, this paper proposes the power control and efficiency optimization strategies for multiple EVs.

The wireless power charging system for multiple loads with a structure of double-sided LCC compensation topology is established. The expressions of optimal transmission efficiency and optimal equivalent impedance are derived. Taking the Tesla Model 3 as an example, a method to determine the number of EVs allowed by one transmitter coil and the overall charging power is proposed considering EV speed, power supply capacity, safe braking distance and overall efficiency. Then, the power control strategy, which can adapt to the changes of EV speed and the efficiency optimization strategy under different numbers of EVs are proposed.

In this paper, a method to determine the numbers of EVs allowed by one transmitter coil and the overall charging power is proposed considering EVs speed, power supply capacity, safe braking distance and overall efficiency. The accuracy of the charging power is good enough and the overall efficiency reaches a maximum of 91.79% when the load resistance changes from 5Ω to 20Ω.

In this paper, the power control and efficiency optimization strategy of DWC system for multiple EVs are proposed. Specifically, a method of designing the number of EVs and charging power allowed by one transmitter coil considering the factors of EV speed, power supply capacity, safe braking distance and overall efficiency is designed. The overall efficiency of the experiment reaches a maximum of 91.79% after adopting the optimization strategy.

The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA.

The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance.

The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations.

The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

The purpose of this paper is to develop a load detection method for domestic induction cooktops. The solution aims to minimize its impact in the converter power transmission while enabling the estimation of the equivalent electrical parameters of the load. This method is suitable for a multi-output resonant inverter topology with shared power devices.

The considered multi-output converter presents power devices that are shared between several loads. Thus, applying load detection methods in the literature requires a halt in the power transfer to ensuring safe operation. The proposed method uses a complementary short-voltage pulse to excite the induction heating (IH) coil without stopping the power transfer to the remaining IH loads. With the current through the coil and the analytical equations, the equivalent inductance and resistance of the load is estimated. The precision of the method has been evaluated by simulation, and experimental results are provided.

The measurement of the current through the induction coil as a response to a short-time single-pulse voltage variation provides enough information to estimate the load equivalent parameters, allowing to differentiate between no-load, non-suitable IH load and suitable IH load situations.

The proposed method provides a solution for load detection without requiring additional circuitry. It aims for low power transmission to the load and ensures zero-voltage switching and reduced peak current even in no-load cases. Moreover, the proposed solution is extensible to less complex converters, as the half bridge.

Sustainable textiles have become imperative in mitigating the adverse environmental and social impacts of the textile industry. This paper aims to synthesize recent advancements and key considerations in sustainable textile development, emphasizing their role in promoting environmental stewardship, social responsibility and economic viability.

The literature search has been conducted by identifying and articulating the previous studies related to integrating the latest cutting-edge techniques with functional textiles.

Future-generation textiles (FGTs), which incorporate state-of-the-art developments in materials, technologies and functionalities, herald a paradigm-shifting period in the textile industry. FGTs mark a new era in this dynamic world by igniting conversations about their mechanisms, problems, progress to date and potential future applications. This investigation covers a wide range of topics, including wearable electronics, nanotechnology, 3D printing, recycling, machine learning and energy harvesting. Key components include sustainability, functionality, intelligent integration, advanced manufacturing processes and multifunctionality. The paper highlights the potential benefits of smart textiles, wearable technology, improved performance and sustainability through advances in customization and security.

It is an original review work. This paper will be helpful for manufacturers and researchers in the smart wearable textile sector in developing innovative techniques for multifunctional garments by integrating cutting-edge technology.

Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.

To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.

The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.

A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.

Passive chipless RFID (radio frequency identification) sensors, devoid of batteries or wires for data transmission to a signal reader, demonstrate stability in severe conditions. Consequently, employing these sensors for metal crack detection ensures ease of deployment, longevity and reusability. This study aims to introduce a chipless RFID sensor design tailored for detecting metal cracks, emphasizing tag reusability and prolonged service life.

The passive RFID sensor is affixed to the surface of the aluminum plate under examination, positioned over the metal cracks. These cracks alter the electrical length of the sensor, thereby influencing its amplitude-frequency characteristics. Hence, the amplitude-frequency profile generated by various metal cracks can effectively ascertain the occurrence and orientation of the cracks.

Simulation and experimental results show that the proposed crack sensing tag produces different frequency amplitude changes for four directions of cracks and can recognize the crack direction. The sensor has a small size and simple structure, which makes it easy to deploy.

This research aims to deploy crack detection on metallic surfaces using passive chipless RFID sensors, analyze the amplitude-frequency characteristics of crack formation and distinguish cracks of varying widths and orientations. The designed sensor boasts a straightforward structural design, facilitating ease of deployment, and offers a degree of reusability.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

The purpose of this study is to determine research areas that are most favorable in supporting the development and manufacturing of electric vehicle (EV) components locally in Indonesia for 2025–2035. Therefore, will provide direction for the formulation of the related government policies and programs. Consequently, an EV technology research priority must be identified.

A technology foresight (TF) procedure which consists of a STEEPV analysis, followed by scenarios development and expert elicitation techniques, was conducted to determine an EV technology research priority that may direct future specific local component innovations, and therefore businesses.

The results of this study indicate that research in a range of EV battery technologies, technologies relating to a variety of key components (to increase local content) and autonomous systems were important to support the local development and manufacturing of EV components in Indonesia.

In this study, the scenarios development process was conducted based on selected available experts, mostly internally from BRIN. Some biased opinions may be present.

There have not been any TF studies regarding the development of EV technology research priority in Indonesia.

Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.

The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.

The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.

This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.

A wireless body area network (WBAN) is a collection of sensing devices attached to a person’s body that is typically used during health care to track their physical state. This paper aims to study the security challenges and various attacks that occurred while transferring a person’s sensitive medical diagnosis information in WBAN.

This technology has significantly gained prominence in the medical field. These wearable sensors are transferring information to doctors, and there are numerous possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. As a result, mutual authentication and session key negotiations are critical security challenges for wearable sensing devices in WBAN. This work proposes an improved mutual authentication and key agreement protocol for wearable sensing devices in WBAN. The existing related schemes require more computational and storage requirements, but the proposed method provides a flexible solution with less complexity.

As sensor devices are resource-constrained, proposed approach only makes use of cryptographic hash-functions and bit-wise XOR operations, hence it is lightweight and flexible. The protocol’s security is validated using the AVISPA tool, and it will withstand various security attacks. The proposed protocol’s simulation and performance analysis are compared to current relevant schemes and show that it produces efficient outcomes.

This technology has significantly gained prominence in the medical sector. These sensing devises transmit information to doctors, and there are possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. Hence, this paper proposes a lightweight and flexible protocol for mutual authentication and key agreement for wearable sensing devices in WBAN only makes use of cryptographic hash-functions and bit-wise XOR operations. The proposed protocol is simulated using AVISPA tool and its performance is better compared to the existing methods. This paper proposes a novel improved mutual authentication and key-agreement protocol for wearable sensing devices in WBAN.