• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.104-112
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• 2017

The CRE (Cell Range Expansion) that selects the small cell with more efficient uplink resources has been developed by 3GPP to relieve the problem of the traffic imbalance due to the power differences between macro and small cells in HetNet. In addition, ABS (Almost Blank Subframes) has been proposed to resolve the signal interference problem due to the operation CREs. This paper proposes an effective method to calculate the ABS ratio by considering the proportion of the number of UEs in CRE and macro cell ranges, as well as the number of small cells in a macro cell. The proposed method has been implemented on the LTESim simulator, and compared with previously proposed methods. The experimental results show that the proposed method can improve the throughput and packet loss ratio performances. In particular, it is also shown that CRE bias values affect those performances, and there exist effective CRE bias values to derive the best performances.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.883-888
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• 2023

Since data centers are places that provide IT services 24 hours a day, 365 days a year, data center power consumption is expected to increase to approximately 10% by 2030, and the introduction of high-density IT equipment will gradually increase. In order to ensure the stable operation of IT equipment, various types of research are required to conserve energy in cooling and improve energy management. This study proposes the following process for energy saving in data centers. We conducted CFD modeling of the data center, proposed an artificial intelligence-based thermal environment prediction model, compared actual measured data, the predicted model, and the CFD results, and finally evaluated the data center's thermal management performance. It can be seen that the predicted values of RCI, RTI, and PUE are also similar according to the normalization used in the normalization method. Therefore, it is judged that the algorithm proposed in this study can be applied and provided as a thermal environment prediction model applied to data centers.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.2
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• pp.182-191
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• 2024

Purpose: The purpose of this study was to explore the characteristics of social networks among registered nurses in acute nursing care units. Methods: This study used a survey design. Four nursing units from two acute hospitals were selected using a convenience method, and 83 nurses from those nursing units participated in the study in July 2022. The positive influences among nurses included friendship, collaboration, advice, and referent networks, and the negative influences included avoidance and bullying networks. Using the NetMiner program, the k-means clustering technique was applied to create groups of nodes with similar characteristics. The general characteristics of the participants were analyzed by mean, standard deviation, frequency, and ANOVA or chi-squared test. Results: As a result of dividing the 83 nurse participants into four clusters, positive influencers, silent peers, unwelcome peers, and active bullies were identified. Positive influence group nurses were frequently mentioned in the friendship, collaboration, advice, and referent networks. On the other hand, nurses in the unwelcome group and the active bullying group were frequently mentioned in the avoidance and bullying networks. Conclusion: Social networks that have a positive or negative impact on nursing performance are created through different relationships between nurses. Nurse managers can use the findings to create a more supportive and collaborative environment. Further research is needed to develop intervention programs to improve interactions and relationships between fellow nurses.

• IMMUNE NETWORK
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• v.24 no.1
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• pp.9.1-9.21
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• 2024

The cytokine IL-7 plays critical and nonredundant roles in T cell immunity so that the abundance and availability of IL-7 act as key regulatory mechanisms in T cell immunity. Importantly, IL-7 is not produced by T cells themselves but primarily by non-lymphoid lineage stromal cells and epithelial cells that are limited in their numbers. Thus, T cells depend on cell extrinsic IL-7, and the amount of in vivo IL-7 is considered a major factor in maximizing and maintaining the number of T cells in peripheral tissues. Moreover, IL-7 provides metabolic cues and promotes the survival of both naïve and memory T cells. Thus, IL-7 is also essential for the functional fitness of T cells. In this regard, there has been an extensive effort trying to increase the protein abundance of IL-7 in vivo, with the aim to augment T cell immunity and harness T cell functions in anti-tumor responses. Such approaches started under experimental animal models, but they recently culminated into clinical studies, with striking effects in re-establishing T cell immunity in immunocompromised patients, as well as boosting anti-tumor effects. Depending on the design, glycosylation, and the structure of recombinantly engineered IL-7 proteins and their mimetics, recombinant IL-7 molecules have shown dramatic differences in their stability, efficacy, cellular effects, and overall immune functions. The current review is aimed to summarize the past and present efforts in the field that led to clinical trials, and to highlight the therapeutical significance of IL-7 biology as a master regulator of T cell immunity.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.993-1001
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• 2024

The TANDEM project is a European initiative funded under the EURATOM program. The project started on September 2022 and has a duration of 36 months. TANDEM stands for Small Modular ReacTor for a European sAfe aNd Decarbonized Energy Mix. Small Modular Reactors (SMRs) can be hybridized with other energy sources, storage systems and energy conversion applications to provide electricity, heat and hydrogen. Hybrid energy systems have the potential to strongly contribute to the energy decarbonization targeting carbon-neutrality in Europe by 2050. However, the integration of nuclear reactors, particularly SMRs, in hybrid energy systems, is a new R&D topic to be investigated. In this context, the TANDEM project aims to develop assessments and tools to facilitate the safe and efficient integration of SMRs into low-carbon hybrid energy systems. An open-source "TANDEM" model library of hybrid system components will be developed in Modelica language which, by coupling, will extend the capabilities of existing tools implemented in the project. The project proposes to specifically address the safety issues of SMRs related to their integration into hybrid energy systems, involving specific interactions between SMRs and the rest of the hybrid systems; new initiating events may have to be considered in the safety approach. TANDEM will study two hybrid systems covering the main trends of the European energy policy and market evolution at 2035's horizon: a district heating network and power supply in a large urban area, and an energy hub serving energy conversion systems, including hydrogen production; the energy hub is inspired from a harbor-like infrastructure. TANDEM will provide assessments on SMR safety, hybrid system operationality and techno-economics. Societal considerations will also be encased by analyzing European citizen engagement in SMR technology safety.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.160-166
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• 2024

The inversion of radiation field distribution is of great significance in the decommissioning sites of nuclear facilities. However, the radiation fields often contain multiple mixtures of radionuclides, making the inversion extremely difficult and posing a huge challenge. Many radiation field reconstruction methods, such as Kriging algorithm and neural network, can not solve this problem perfectly. To address this issue, this paper proposes an optimized inverse distance weighted (IDW) interpolation algorithm for reconstructing the gamma radiation field. The algorithm corrects the difference between the experimental and simulated scenarios, and the data is preprocessed with normalization to improve accuracy. The experiment involves setting up gamma radiation fields of three Co-60 radioactive sources and verifying them by using the optimized IDW algorithm. The results show that the mean absolute percentage error (MAPE) of the reconstruction result obtained by using the optimized IDW algorithm is 16.0%, which is significantly better than the results obtained by using the Kriging method. Importantly, the optimized IDW algorithm is suitable for radiation scenarios with multiple radioactive sources, providing an effective method for obtaining radiation field distribution in nuclear facility decommissioning engineering.

• Animal Bioscience
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• v.37 no.2
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• pp.184-192
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• 2024

Objective: This study aims to investigate the genetic structure and characteristics of the Angus cattle population in Hungary. The survey was performed with the assistance of the Hungarian Hereford, Angus, Galloway Association (HHAGA). Methods: Genetic parameters of 1,369 animals from 16 Angus herds were analyzed using the genotyping results of 12 microsatellite markers with the aid of PowerMarker, Genalex, GDA-NT2021, and STRUCTURE software. Genotyping of DNA was performed using an automated genetic analyzer. Based on pairwise identity by state values of animals, the Python networkx 2.3 library was used for network analysis of the breed and to identify the central animals. Results: The observed numbers of alleles on the 12 loci under investigation ranged from 11 to 18. The average effective number of alleles was 3.201. The overall expected heterozygosity was 0.659 and the observed heterozygosity was 0.710. Four groups were detected among the 16 Angus herds. The breeders' information validated the grouping results and facilitated the comparison of birth weight, age at first calving, number of calves born and productive lifespan data between the four groups, revealing significant differences. We identified the central animals/herd of the Angus population in Hungary. The match of our group descriptions with the phenotypic data provided by the breeders further underscores the value of cooperation between breeders and researchers. Conclusion: The observation that significant differences in the measured traits occurred among the identified groups paves the way to further enhancement of breeding efficiency. Our findings have the potential to aid the development of new breeding strategies and help breeders keep the Angus populations in Hungary under genetic supervision. Based on our results the efficient use of an upcoming genomic selection can, in some cases, significantly improve birth weight, age at first calving, number of calves born and the productive lifespan of animals.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.117-127
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• 2024

Purpose: The purpose is to conduct basic research to save energy and improve the safety of manufacturing plant infrastructure by comprehensively monitoring energy management, temperature, humidity, dust and gas, air quality, and machine operation status in small and medium-sized manufacturing plants. Method: To this end, energy-related data and environmental information were collected in real time through digital power meters and IoT sensors, and research was conducted to disseminate and respond to situations for energy saving through monitoring and analysis based on the collected information. Result: We presented an application plan that takes into account energy management, cost reduction, and safety improvement, which are key indicators of ESG management activities. Conclusion: This study utilized various sensor devices and related devices in a smart factory as a practical case study in a company. Based on the information collected through research, a basic system for energy saving and safety improvement was presented.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.