• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.9
• /
• pp.2399-2418
• /
• 2023

The paper focuses on investigating secure transmission in wireless powered communication networks (WPCN) that involve multiple energy-constrained relays and one energy-constrained source. The energy is harvested from a power beacon (PB) while operating in the presence of a passive eavesdropper. The study primarily aims to achieve energy-efficient secure communications by examining the impact of channel estimation on the secrecy performance of WPCN under both perfect and imperfect CSI scenarios. To obtain practical insights on improving security and energy efficiency, we propose closed-form expressions for secrecy outage probability (SOP) under the linear energy harvesting (LEH) model of WPCN. Furthermore, we suggest a search method to optimize the secure energy efficiency (SEE) with limited power from PB. The research emphasizes the significance of channel estimation in maintaining the desired performance levels in WPCN in real-world applications. The theoretical results are validated through simulations to ensure their accuracy and reliability.

• Journal of Electrochemical Science and Technology
• /
• v.12 no.3
• /
• pp.297-301
• /
• 2021

Microbial fuel cells (MFCs) convert chemical energy to electrical energy via electrochemically active microorganisms. The interactions between microbes and the surface of a carbon electrode play a vital role in capturing the respiratory electrons from bacteria. Therefore, improvements in the electrochemical and physicochemical properties of carbon materials are essential for increasing performance. In this study, a microwave and sulfuric acid treatment was used to modify the surface structure of graphite granules. The prepared expandable graphite granules (EGG) exhibited a 1.5 times higher power density than the unmodified graphite granules (1400 vs. 900 mW/m³). Scanning electron microscopy and Fourier transform infrared spectroscopy revealed improved physical and chemical characteristics of the EGG surface. These results suggest that physical and chemical surface modification using sulfuric acid and microwave heating improves the performance of electrode-based bioprocesses, such as MFCs.

• Journal of Sensor Science and Technology
• /
• v.31 no.4
• /
• pp.218-227
• /
• 2022

Triboelectric nanogenerators (TENGs), a new green energy, that have various potential applications, such as energy harvesters and self-powered sensors. The output performance of TENGs has been improving rapidly, and their output power significantly increased since they were first reported owing to improved triboelectrification materials and interfacial material engineering. Because the operation of a TENG is based on contact electrification in which electric charges are exchanged at the interface between two materials, its output can be increased by increasing the contact area and charge density. Material surface modification with microstructures or nanostructures has increased the output performance of TENGs significantly because not only does the sharp micro/nano morphology increases the contact area during friction, but it also increases the charge density. Chemical treatment in which ions or functional groups are added has also been used to improve the performance of TENGS by modifying the work functions, charge densities, and dielectric constants of the triboelectric materials. In addition, ultrahigh output power from TENGs without using new materials or treatments has been obtained in many studies in which special structures were designed to control the current release or to collect the charge current directly. In this review, we discuss physical and chemical treatments, bulk modifications, and interfacial engineering for enhancing TENG performance by improving contact electrification and electrostatic induction.

• ETRI Journal
• /
• v.44 no.1
• /
• pp.155-167
• /
• 2022

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2018.11a
• /
• pp.92-93
• /
• 2018

This study analyzed the physical properties of insulation materials upon completion of building completion years and found the suitability of the current energy performance analysis methodology to apply the insulation specified in the design drawings to the same thermal conductivity values as the new materials.

• Journal of Life Science
• /
• v.19 no.11
• /
• pp.1623-1628
• /
• 2009

The purpose of this study was to investigate the effects of complex ergogenic aid supplementation on endurance performance, energy substrate utilization (glucose, FFA) and blood fatigue factors (ammonia, lactate, phosphorous, pH, 5-HT) in endurance exercise. Subjects (male=10) took in complex ergogenic aid (180 ml/day) for 4 weeks and were tested after pre-test. Endurance performance times increased after supplementation compared to before supplementation. However, there was no additional accumulation of the fatigue materials. Thus the complex ergogenic aid supplementation caused the delay of the fatigue material accumulation during endurance exercise.

• Korean Journal of Exercise Nutrition
• /
• v.24 no.4
• /
• pp.15-23
• /
• 2020

[Purpose] Lactate is a principal energy substrate for the brain during exercise. A single bout of high-intensity interval exercise (HIIE) can increase the blood lactate level, brain lactate uptake, and executive function (EF). However, repeated HIIE can attenuate exercise-induced increases in lactate level and EF. The lactate levels in the brain and blood are reported to be correlated with exercise-enhanced EF. However, research is yet to explain the cause-and-effect relationship between lactate and EF. This study examined whether lactate consumption improves the attenuated exercise-enhanced EF caused by repeated HIIE. [Methods] Eleven healthy men performed two sets of HIIE, and after each set, 30 min were given for rest and examination. In the 2^nd set, the subjects consumed experimental beverages containing (n = 6) and not containing (n = 5) lactate. Blood, cardiovascular, and psychological variables were measured, and EF was evaluated by the computerized color-word Stroop test. [Results] The lactate group had a higher EF (P < 0.05) and tended to have a higher blood lactate level (P = 0.082) than the control group in the 2^nd set of HIIE. Moreover, blood lactate concentration was correlated with the interference score (i.e., reverse score of EF) (r = -0.394; P < 0.05). [Conclusion] Our results suggest that the attenuated exercise-enhanced EF after repeated HIIE can be improved through lactate consumption. However, the role of lactate needs to be elucidated in future studies, as it can be used for improving athletes' performance and also in cognitive decline-related clinical studies.

• Current Photovoltaic Research
• /
• v.11 no.1
• /
• pp.27-33
• /
• 2023

In this paper, a machine learning model by using a regression algorithm is proposed to estimate the power generation performance of the BIPV system. The physical model formula for estimating the generation performance and the proposed model were compared and analyzed. For the physical model formula, simple efficiency model, temperature correction model, and regressive physics model for changing an irradiance were used. As a result, when comparing the regressive physics model for changing an irradiance and the proposed model with the actual generation measured data, the respective RMSE values are 0.1497 kW, 0.0451 kW and the accuracy values are 86.44%, and 96.56%. Therefore, the proposed model implemented in this experiment can be useful in estimating power generation.

• 한국신재생에너지학회:학술대회논문집
• /
• 2007.06a
• /
• pp.698-701
• /
• 2007

DAHAN, the first 1 MWe Solar Power Tower system locates north to Beijing where nearby The Great Wall is now under construction with cooperation between China and Korea. Results in predicting the preliminary performance of this central receiver system are presented in this paper. Operating cycles under some typical weather condition days are simulated and commented. These results can be used to assess the impact of alternative plant designs or operating strategies on annual energy production, with the final objective being to optimize the design of central receiver power plants. Two subsystems are considered in the system simulation: the solar field and the power block. Mathematic models are used to represent physical phenomena and relationships so that the characteristics of physical processes involving these phenomena can be predicted. Decisions regarding the best position for locating heliostats relative to the receiver and how high to place the receiver above the field constitute a multifaceted problem. Four different kinds of field layout are designed and analyzed by the use of ray tracing and mathematical simulation techniques to determine the overall optical performance ${\eta}_{field}$ and the spillage ${\eta}_{spill}$.The power block including a Rankine cycle is analyzed by conventional energy balance methods.

• Journal of information and communication convergence engineering
• /
• v.19 no.3
• /
• pp.136-141
• /
• 2021

Research on wireless sensor networks has focused on the monitoring and characterization of large-scale physical environments and the tracking of various environmental or physical conditions, such as temperature, pressure, and wind speed. We propose a stochastic mobility model that can be applied to a MANET (Mobile Ad-hoc NETwork). environment, and apply this mobility model to a newly proposed clustering-based routing protocol. To verify its stability and durability, we compared the proposed stochastic mobility model with a random model in terms of energy efficiency. The FND (First Node Dead) was measured and compared to verify the performance of the newly designed protocol. In this paper, we describe the proposed mobility model, quantify the changes to the mobile environment, and detail the selection of cluster heads and clusters formed using a fuzzy inference system. After the clusters are configured, the collected data are sent to a base station. Studies on clustering-based routing protocols and stochastic mobility models for MANET applications have shown that these strategies improve the energy efficiency of a network.