Earticle

With the growing demand for hybrid UAVs, efficient energy management systems (EMS) are becoming increasingly essential. This study proposes a Deep Q-network-based EMS for hybrid UAVs powered by an internal combustion engine and a battery. The EMS optimizes engine efficiency by maintaining operation within its most effective range while the battery supplies additional power as needed. Simulations under dynamically changing conditions demonstrate that the EMS efficiently distributes energy between sources, ensuring reliable power delivery and significantly improving overall efficiency. The proposed system presents a promising approach to enhancing the performance of hybrid UAVs.

With the emergence and popularization of multi-homing intelligent terminals, multi-receiver D2D communication has become a hot research issue. Based on the characteristic that D2D communication can work in licensed and unlicensed spectrum, a new grouping D2D (GD2D) model contains two transmitters (one works in the licensed spectrum and the other works in the unlicensed spectrum) and one receiver is constructed in this paper. To improve the user’s quality-of-service (QoS) at the edge of the cell, we develop a novel relay selection scheme based on a social tie that considers both physical and social constraints. Furthermore, we formulate a resource allocation problem that aims to maximize the system’s energy efficiency (EE). We derive the optimal closed solutions of the expressions by the fractional programming method and the Lagrangian dual approach. Numerical results show that the proposed grouping D2D scheme can yield significant EE performance gain over the traditional cell-edge user scheme.

Objective To compare the energy efficiency of gait with knee-ankle-foot orthosis (KAFO) and robot-assisted gait and to develop a usability questionnaire to evaluate the satisfaction of walking devices in paraplegic patients with spinal cord injuries. Methods Thirteen patients with complete paraplegia participated and 10 completed the evaluation. They were trained to walk with KAFO (KAFO-gait) or a ReWalk robot (ReWalk-gait) for 4 weeks (20 sessions). After a 2-week wash-out period, they switched walking devices and underwent 4 additional weeks of training. Two evaluations were performed (after 2 and 4 weeks) following the training periods for each walking device, using the 6-minute walking test (6MWT) and 30-minute walking test (30MWT). The spatiotemporal variables (walking distance, velocity, and cadence) and energy expenditure (heart rate, maximal heart rate, the physiologic cost index, oxygen consumption, metabolic equivalents, and energy efficiency) were evaluated duringthe 6MWT and 30MWT. A usability evaluation questionnaire for walking devices was developed based on the International Organization for Standardization/International Electrotechnical Commission guidelines through expert consultation. Results The ReWalk-gait presented significant advantages in energy efficiency compared to KAFO-gait in the 6MWT and 30MWT; however, there were no differences in walking distance or speed in the 30MWT between ReWalk-gait and KAFOgait. The usability test demonstrated that ReWalk-gait was not superior to KAFO-gait in terms of safety, efficacy, efficiency, or patient satisfaction. Conclusion The robot (ReWalk) enabled patients with paraplegia to walk with lower energy consumption compared to KAFO, but the ReWalk-gait was not superior to KAFO-gaitin terms of patient satisfaction.

In this paper, we study secure energy efficiency (SEE) for simultaneous wireless information and power transfer (SWIPT) in a distributed antenna system (DAS) based IoT network. We consider a system in which both the legitimate user (Bob) and the eavesdropper (Eve) rely on the energy harvested from the received radio signal. Firstly, with perfect channel state information (CSI), we formulate the maximization of SEE as a constrained optimization problem. In this problem, we aim to highlight the advantage of SWIPT in exploiting the Eve’s energy harvesting requirement. This is achieved by defining a charge constraint in the SEE optimization problem which ensures that the Eve is deprived of its only energy source. Next, considering the fact that perfect CSI is hard to achieve in practice, we characterize the system performance in terms of the outage probability (OP) of SEE. For the given SWIPT-in-DAS setup, we derive the closed form expression for the OP of SEE and with the help of numerical results, we study the effect of transmit power levels, number of distributed antenna (DA) ports and the PS ratio of devices. To the best of our knowledge, this is the first attempt to define the OP of SEE for SWIPT-in-DAS.

To effectively manage the escalating traffic, attention is drawn to the coexistence mechanism of cellular and Wi-Fi networks which offload the cellular traffic from the licensed band to the unlicensed band. For the coexistence of 5G new radio-unlicensed and Wi-Fi, we tackle the energy efficiency maximization problem by sequentially determining the duty cycle and transmit power through the use of distributed deep Q-network (DQN) techniques. When utilizing the existing unlicensed band, the proposed method minimizes the impact on Wi-Fi networks while achieving optimal energy efficiency. Simulations validate the superior energy efficiency of the proposed coexistence mechanism over various benchmark methods.

In B5G heterogeneous cellular networks, a rapid increase in the number of small cell base stations (SBSs) to support a massive number of devices tends to waste a considerable amount of energy. Therefore, intelligent management of SBSs’ power consumption is one of the most important research issues. We herein propose quasi-distributed Q-learning-based cell breathing (QD-QCB) considering full and partial SBS collaborations for maximizing network energy efficiency. Also, the concept of an aggregated active SBS set based on regional user distributions is proposed for computing- and energy-efficient operation. Through intensive simulations, we show that the proposed QD-QCB algorithm can achieve optimal energy efficiency, and improve the network energy efficiency significantly compared with conventional algorithms such as no transmit power control, random cell breathing, and greedy cell breathing algorithms.

A total of 96 non-lean-type(Yorkshire×Landrace)×Duroc gilts and barrows weighing approximately 80kg were randomly allocated to 24 pens under a 2(sex)×3[diet; 3.4, 3.2, and 3.0McalDE/kg{‘high’-, ‘medium’-, and ‘low’-energy diets(HE, ME, and LE), respectively}] factorial arrangement of treatments. All animals were slaughtered approximately at 115kg, after which carcass quality traits and grades and physicochemical and sensory characteristics of the loin related to meat quality were analyzed. The ADG and gain:feed were not affected by the sex or dietary treatment, whereas ADFI was greater in the ME vs HE group. Backfat thickness was greater in barrows vs gilts and also in ME and HE vs LE only in barrows. Enumerated carcass marbling and quality grade, which were highly correlated(r=0.56; P<0.01), were greater in barrows vs gilts. Physicochemical characteristics including the color, pH, drip loss and contents of moisture, protein, and fat of fresh loin, as well as sensory characteristics of fresh and cooked loin, were not affected by the sex or dietary treatment, except for shear force for cooked loin which was greater(P<0.05) in LE and ME vs HE. In conclusion, it is thought that ME is comparable to HE in terms of the effect on growth and carcass quality of finishing pigs, but that the relative effect of LE vs ME needs to be further studied.

This study was executed to estimate the impacts of increasing dietary standardized ileal digestible (SID) lysine and net energy levels on growth, nutrient absorption, and meat carcass traits in growing-finishing pigs. In total, 90 pigs [(Yorkshire × Landrace) × Duroc] were erratically dispensed to 3 treatments (6 replicate/treatment) with 5 pigs (3 barrows and 2 gilts) per pen, and their average primary body weight was 20.51± 0.02 kg. The trial period was 16 weeks (growing stage, initial to week 8; finishing stage, week 8 to week 16). The dietary treatments used included control (CON) as the basal diet, TRT1 (basal diet + 0.05% SID lysine), and TRT2 (basal diet + 0.05% SID lysine + 0.084 MJ/kg net energy) for both the growing and finishing stages. Both the TRT1 and TRT2 group diets improved (p = 0.033) average daily gain (ADG) at week 12 and tended to enhance (p = 0.088) body weight at week 12 and ADG at the overall period compared to the CON group. Moreover, pigs in the TRT2 group had higher backfat thickness (p = 0.034) at week 12 in comparison to the TRT1 and CON diets. Nevertheless, no treatment effect was found (p > 0.05) in nutrient absorption or carcass grade among the dietary treatments. Hence, incorporating the increasing level of 0.05% SID lysine and 0.084 MJ/kg net energy into the pig diet during the growing and finishing stages can be considered a suitable approach for enhancing both growth efficiency and carcass backfat thickness in pigs.

This article addresses an energy-efficient positioning system using Ultra-Wideband (UWB) technology. Positioning systems play a crucial role in various applications such as disaster rescue, autonomous robots, and industrial automation. However, in such environments, IoT devices rely on batteries, and UWB systems have been limited in energy efficiency compared to other wireless communication technologies. In this study, we propose a high-resolution positioning algorithm for UWB systems with reduced communication frequency to enhance energy efficiency while providing real-time location information. Experimental results demonstrate that reducing the UWB communication frequency leads to increased energy efficiency. We also analyze the relationship between real-time location update speed and the energy constraints of IoT devices. Finally, we compare the performance of UWB systems with the high-resolution algorithm to conventional triangulation methods. This research provides a fundamental basis for improving energy-efficient positioning systems using UWB technology.

Respiratory diseases are one of the major causes of death worldwide. Therefore, research on respiratory disease classification using respiratory data is considered an important task. Previous studies mainly focused on respiratory disease classification using 2D feature extraction methods such as spectrograms and MFCCs. However, these methods have drawbacks such as long classification time and decreased accuracy as the number of respiratory disease types increases. To address this issue, we propose a solution that combines data with different dimensions to improve the performance of respiratory disease classification. We utilize the gammatone based spectrogram feature extraction method along with raw 1D respiratory data. By combining these two approaches, we can achieve both fast classification speed from 1D time-series models and high classification accuracy from 2D feature extraction methods. Our proposed respiratory disease classification study consists of four stages: data preprocessing, combined data generation, construction of a respiratory disease classification model, and decision-making for respiratory disease diagnosis. We validate our approach using a TCN (Temporal Convolutional Network) model and achieve a high respiratory disease classification accuracy of 98.93%. Moreover, our proposed method significantly reduces the training time for classification by more than four times compared to previous methods, thus demonstrating its superiority.

The indigenous livestock have nutritional adaptive traits which affects the survival and reproduction. In mature goat does, nutrition levels are well known to play an important role in ovulation and fertilization. Therefore, the objective of this study was to determine the effects of five different dietary energy levels on reproductive characteristics in Korean Black goat does. Fifty goat does of 1 year age (32.2±5.9 kg) were stratified by body weight, and randomly assigned to 5 dietary treatments (10 goat does per treatment). The dietary treatment consisted of metabolic energy (ME) of the diets as follow; 1.88 Mcal/kg (T1), 2.05 Mcal/kg (T2), 2.14 Mcal/kg (T3), 2.50 Mcal/kg (T4) and 2.71 Mcal/kg (T5). At the kidding time, goats were monitored at an hourly and the time of birth, body weight and birth types (single, twins and triplets) of kids were recorded immediately after kidding. Kidding rate, gestation rate, reproduction protability and litter size in T2 groups were higher than other groups. In goat kids, birth weight was high in T5, but weaning weight and ADG of kids in T1 and T2 groups higher than other groups. The result of this study may suggest that feeding Korean Black goat does 2.05 Mcal/kg of ME in diets more effective role for goat reproduction. Further study will be necessary to assessment the effects of energy intakes on reproduction characteristics and estrus synchronization for artificial insemination in Korean Black goat does.

In this research, the variation of round-trip efficiency in a liquid air energy storage system (LAES) is calculated and an optimal configuration is found. The multiple stages of cold energy storage are simulated with several materials that process latent heat at different temperature ranges. The effectiveness in the charging and discharging processes of LAES is newly defined, and its relationship with the round-trip efficiency is examined. According to defined correlation, the effectiveness of the discharging process significantly affects the overall system performance. The round-trip efficiency is calculated for the combined cold energy storage materials of aqueous dimethyl sulfoxide (DMSO) solution, ethanol, and pentane theoretically. The performance of LAES varies depending on the freezing point of the cold storage materials. In particular, when the LAES uses several cold storage materials, those materials whose freezing points are close to room temperature and liquid air temperature should be included in the cold storage materials. In this paper, it is assumed that only latent heat is used for cold energy storage, but for more realistic analyzes, the additional consideration of the transient thermal situation to utilize sensible heat is required. In the case of such a dynamic system, since there is certainly more increased heat capacity of the entire storage system, the volume of the cold energy storage system will be greatly reduced.

Background: Measuring the energy spectrum of γ rays to assess the exposure dose and identifying the leaked radioisotopes at the accident site and the surrounding environment is necessary in the case of an accident involving the leakage of radioactive material at a nuclear power plant or a radiation-related facility. High-purity germanium semiconductor detectors are utilized for γ-ray spectrometry due to their high energy resolution, but they exhibit a high initial and operational cost due to the need for a cooling mechanism. Materials and Methods: We improved the unfolding method for scintillators with a refined response function that involves the energy dependence of scintillation efficiency for secondary electrons produced by incident γ-ray interaction. Monte Carlo simulation code EGS5 with a mesh width of 5 keV in the energy range of 0–3 MeV was used to calculate response functions, assuming γ rays irradiated parallel to the detector sides. The unfolding algorithm involves an iterative approximation method, which is independent of initial guesses. Results and Discussion: The measurement accuracy of the γ-ray fluence rate was almost constant at <10% at ≥0.3 MeV caused by repeated measurements using 137Cs, 133Ba, 88Y, and 60Co radiation sources. Additionally, we confirmed linearity concerning the γ-ray intensity by changing the distance from the source to the detector. Conclusion: We verified that the unfolding method separated peaks for each γ-ray energy, although the difference in γ-ray energies was several tens of keV. Moreover, the accuracy of the unfolding method was almost constant and had linearity concerning γ-ray intensity.

Background: As an important detecting device, TLD is a widely used in the radiation monitoring. It is essential for us to study the property of detecting element. The aim of this study is to calculate the thermo-luminescence efficiency of TL elements. Materials and Methods: A batch of thermo-luminescence elements were irradiated by the filtered X-ray beams of average energies in the range 40-200 kVp, 662 keV 137Cs gamma rays and then the amounts of lights were measured by the TL reader. The deposition energies in elements were calculated by theory formula and Monte Carlo simulation. The unit absorbed dose in elements by photons with different energies corresponding to the amounts of lights was calculated, which is called the thermo luminescent efficiency (). Because of the amounts of lights can be calculated by the absorbed dose in elements multiply, the can be calculated by the experimental data (the amounts of lights) divided by absorbed dose. Results and Discussion: The deviation of simulation results compared with theoretical calculation results were less than 5%, so the absorbed dose in elements was calculated by simulation results in here. The change range of value, relative to 662 keV 137Cs gamma rays, is about 30% in the energy range of 33 keV to 662 keV, is in accordance by the comparison with relevant foreign literatures. Conclusion: The values can be used for updating the amounts of lights that are got by the direct ratio assumed relations with deposition energy in TL elements, which can largely reduce the error of calculation results of the amounts of lights. These data can be used for the design of individual dosimeter which used TLD-2000 thermo-luminescence elements, also have a certain reference value for manufacturer to improve the energy-response performance of TL elements by formulation adjustment.

본 연구에서는 자료포락분석(DEA, Data Envelopment Analysis) 모형을 이용하여 한국과 일본의 광역경제권별 에너지효율성을 분석하였다. 한국과 일본의 총 17개 광역경제권별로 1996년부터 2007년까지 12년 동안의 데이터가 구축되었으며 투입요소로 노동과 자본의 생산요소와 6개의 에너지원, 산출요소로 지역별 GDP (Gross Domestic Product)가 규모에 대한 수익가변(VRS)을 고려한 DEA모형에 적용되었다. 자료포락분석 모형을 통해 총기술적에너지효율(OTEE, Overall Technical Energy Efficiency)과 에너지저감량(EST, Energy Saving Target)이 계산되고, 이로부터 Hu and Wang(2006)에 의해 제안된 총요소에너지효율(TFEE, Total Factor Energy Efficiency) 지수를 도출하여 각 에너지원별 에너지효율성을 평가하였다. 한국의 광역경제권은 일본의 광역경제권에 비해 현저히 낮은 수준의 에너지 효율성을 나타내고 있으며 일본의 수도권과 긴키권을 비롯한 몇몇 경제권은 한국의 광역경제권의 에너지효율 향상을 위한 벤치마킹 대상으로 제시되었다.

This paper analyzes the energy efficiency of 7 economic regions in Korea and 10 in Japan using Data Envelopment Analysis (DEA). For such analysis, a dataset is constructed for the seventeen economic regions during the period from 1996 to 2007. In this VRS (Variable returns to Scale) DEA model, labor, capital and 6 energy factors are selected for inputs. The gross regional domestic product (GRDP) is the only output. An energy saving target and total factor energy efficiency index are provided to indicate the efficiency of regional energy use as is suggested by Hu and Wang (2006). Most of the Japanese economic regions show higher efficiency scores compared with those of Korean for the entire sample period. Some of regions such as Japanese Metropolitan and Kinki Area can be regarded as the benchmark of energy saving target for other regions.

본 논문에서는 다중 사용자 기반의 비결합 무선 에너지 하베스팅 네트워크에서 에너지 효 율을 최적화하는 알고리즘을 제안하고 사용자들의 다양한 지리적 분포 시나리오를 가정하여 에너지 효율의 변화의 트랜드를 분석 및 실험하였다. 무선 데이터 전송 및 무선 에너지 충전 이 동시에 이루어지는 무선 에너지 하베스팅 네트워크에서는 에너지 효율 지표는 네트워크 성능을 판단하는 주요한 지표로서 이를 향상시키기 위해서 다양한 요소가 어떻게 영향을 줄 수 있는지 조사할 필요가 있다. 본 논문에서의 모의실험 결과에서 효과적으로 에너지 효율 내지 무선 전력전송 효율을 증대시키기 위해서 두 송신기 hybrid-access point (H-AP)와 power beacon (PB)을 기준으로 사용자들의 분포 형태가 중요한 요소라는 점을 확인할 수 있다.

In this paper, we propose an algorithm to optimize energy efficiency in a multi-user decoupled RF energy harvesting network and experiment on the trend of energy efficiency change assuming users' various geographical distribution scenarios. In the RF energy harvesting network where both wireless data transmission and RF energy harvesting are simultaneously performed, the energy efficiency is a key indicator of network performance, and it is necessary to investigate how various factors can affect the energy efficiency. In order to increase energy efficiency effectively, we can confirm that users' distributions are important factors in the RF energy harvesting network from the simulation results.

전세계적으로 기후변화 대응을 위한 글로벌 탄소중립을 공조하고 있다. 한국의 경우 온실가스 배출량이 빠른 속도로 증가하고 있어 해결이 시급한 상황이다. 이에 본 연구는 스팀트랩이라는 열 에너지 수집 디바이스를 개발하고, 스팀트랩으로 에너지 사용량을 데이터로 수집하여 향후 전력 사용량에 대해서 예측이 가능한 AI 모델을 개발하였다. 해당 AI 모델의 전력 사용량 예측 정확도 평균은 96.7%로 높은 정확도를 보여주었다. 따라서 해당 AI 모델을 통해 어느날 전력 사용량이 높은지와 어떤 설비에서 전력 사용량이 높은지를 예측하고 관리 할 수 있게 되었다. 향후 연구는 스팀트랩의 이상탐지를 통한 효율적인 장비 운용과 에너지 관리 시스템의 표준화를 통해 에너 지 소비 효율을 최적화하여 온실가스 배출을 줄이고자 한다.

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.