현대 군사 환경에서 병력 보충 방식은 부대의 전투력 유지와 직접적인 연관이 있으며, 한국군의 경우 기존의 개인보충 방식이 부대 응집력 저하 및 전투력 약화의 원인으로 작용하고 있다. 특히, 2021년 12월 병 복무기간이 18개월로 단축된 이후, 개인보충 방식이 과거와 동일하게 유지되면서 연간 병력 교체율이 66%를 상회하게 되었으며, 이로 인해 부대의 전투 효율성 유지가 더욱 어려워지고 있다. 또한, 현재 동원 부대의 편성 방식 역시 개별 동원지정을 기반으로 하고 있어 부대 고정율이 낮고, 짧은 동원훈련 기간으로 인해 유사시 신속한 전투력 발휘에 한계가 존재한다. 이에 따라, 기존 개인보충 방식의 한계를 극복할 수 있는 새로운 병력 보충 방식의 도입이 필요하다. 본 연구는 한국군의 현역 및 동원전력 보충 방안으로 ‘중대단위 부대보충’ 개념을 제안하고, 이를 통해 전투력 유지 및 응집력 강화를 도모하는 방안을 모색하였다. 이를 위해 독일, 이스라엘, 미국 등의 부대보 충 사례를 분석하고, 이를 한국군에 적용할 수 있는 정책적 시사점을 도출하였다. 또한, 부대보충 방식이 부대의 전투력과 조직 응집력에 미치는 영향을 실증적으로 분석하기 위해 전투력 평가 실험을 설계하고, 경제적 타당성 분석을 수행하였다. 분석 결과, 중대단위 부대보충 방식은 병력 운영의 안정성을 높이고, 장기적으로 전투력 유지 및 국가 방위력 강화에 기여할 수 있는 것으로 평가되었다. 본 연구는 한국군의 병력 보충 방식에 대한 새로운 접근법을 제시하고, 부대보충 방식이 기존 개인보충 방식에 비해 효과적인 대안이 될 수 있음을 실증적으로 검토하였다. 이를 통해, 향후 군사정책 수립 및 동원체제 개편에 있어 중요한 자료로 활용될 수 있을 것으로 기대된다.

In this study, among the indoor lighting sources of a training ship, the fluorescent lamps for lighting in the passageways, emergency fire pump room, refrigerant plant room, steering gear room, and bow hydraulic pump room, which have very high lighting rates, were replaced by 40W fluorescent lamps with 17W and 20W fluorescent lamps with 11W LEDs. The analysis results of replacing the lighting sources with LEDs showed that the power consumption and carbon dioxide emissions were reduced by 62.1% when using shore power.

This study develops a machine learning-based tool life prediction model using spindle power data collected from real manufacturing environments. The primary objective is to monitor tool wear and predict optimal replacement times, thereby enhancing manufacturing efficiency and product quality in smart factory settings. Accurate tool life prediction is critical for reducing downtime, minimizing costs, and maintaining consistent product standards. Six machine learning models, including Random Forest, Decision Tree, Support Vector Regressor, Linear Regression, XGBoost, and LightGBM, were evaluated for their predictive performance. Among these, the Random Forest Regressor demonstrated the highest accuracy with R2 value of 0.92, making it the most suitable for tool wear prediction. Linear Regression also provided detailed insights into the relationship between tool usage and spindle power, offering a practical alternative for precise predictions in scenarios with consistent data patterns. The results highlight the potential for real-time monitoring and predictive maintenance, significantly reducing downtime, optimizing tool usage, and improving operational efficiency. Challenges such as data variability, real-world noise, and model generalizability across diverse processes remain areas for future exploration. This work contributes to advancing smart manufacturing by integrating data-driven approaches into operational workflows and enabling sustainable, cost-effective production environments.

In this article, to solve the problems about obsolescence of parts and unable to driving turret when internal components are failure, the DC-DC boost converter in the gun/turret drive system of mobile weapon was improved. The power converting circuit in converter is changed by applying the latest components, and the control circuit is changed from analog to digital. Also, the power converting circuits were modularized in three parallel so that it could be driven even when some components failed. The improved DC-DC boost converter secured stability such as converting to voltage in a linear manner in the entire section from the start of boosting to the end. Also, through the modular configuration, turret driving system can operates when some components failed.

본 논문의 주요 목적은 총체전력 정책(TFP, Total Forces Policy) 차원에 서 국방동원 환경 변화에 부합하는 우리 군의 예비전력의 역할 변화와 방안 방향에 대해 제시하는 봄에 있다. 이를 위해서 주요 분석 요소는 미래 국방 동원 환경 변화에 따른 예비전력의 운용과 역할 변화, 국방동원에 대한 인식 전환, 4차 산업기술을 활용한 과학화 예비군훈련장의 구축 현황과 활용 방안이다. 장기화되고 있는 러-우 전쟁에서 볼 수 있듯이, 미래전의 양상과 인구급감에 따른 첨단 과학기술 중심의 군 구조 개편 등을 고려해 볼 때, 상 비군 중심의 전투에 예비군이 보완하는 형태의 전쟁 수행은 어려울 것이다. 국가 총체전력 차원에서 유사시 전장에서 상비전력과의 동반전력으로 전쟁 을 억제하고 전쟁의 지속능력을 보장할 수 있는 예비전력에 대한 인식 전환 을 통해 예산 확보와 주요 핵심 필요한 역할 등을 점진적으로 확대해야 한 다. 따라서 다양한 분쟁 상황에 대비하여 예비군을 필요한 시기와 장소에 적시적으로 보충하기 위해서 과학화 예비군훈련장을 중심으로 장비와 물 자를 편성해서 실전적 훈련이 꾸준히 전개돼야 한다.

본 논문은 모바일 폰 사진을 활용하여 도시 공간에서 전력선과 건물 사이의 거리를 편리하게 모델링하고 측정하는 방법에 중점을 두고 있으며, 이에 대한 정확성을 평가하였다. 모바일 장 치용 2뷰 지오메트리를 사용한 전력선과 건물의 3D 재구성 방법을 설계하여 어디에서나 즉시 측정할 수 있도록 하였다. 특징점을 사용하여 전력선과 건물 사이의 거리를 계산하고 건물 정 보를 활용하여 게임 가상 공간에 전력선과 전주를 배치할 수 있다. 본 논문에서는 대전시 내 10개의 위치에서 실험을 실시하고, 상업용 시스템과 LiDAR가 있는 경우와 없는 경우를 포함 한 이전 방법과의 성능을 평가하였다. 우리의 방법을 스마트폰에 구현했기 때문에 장점은 휴 대성과 저렴함이다.

19세기 근대로 가는 길목에서 조선은 외세의 침입이라는 새로운 시대 상황을 맞게 되었다. 이러한 외압(外壓)에 대응하는 데 가장 근본이 되었 던 것이 당시는 수군(水軍)이라 불렸던 조선 해군(海軍)의 군사력이었고 할 수 있다. 이러한 인식을 바탕으로 본 연구는 19세기 조선 해군 전력 의 일단(一端)을 살펴볼 수 있는 실증적 사례 연구를 진행하였다. 구체적 으로 전라좌수영(全羅左水營)에 속해 있던 광양현(光陽縣)과 경상우수영 (慶尙右水營)에 속해 있던 하동부(河東府)의 수군 전력의 실태를 파악하 고자 하였다. 이들 두 군현은 19세기 ‘중기(重記)’ 자료가 남아 있다. 중 기 자료는 작성 당시 지방 군현의 군비 실태를 파악할 수 있는 가장 좋 은 자료이다. 따라서 이 중기 자료를 중심으로 19세기 조선 해군 전력의 일단을 살펴보았다. 이와 더불어 각종 관찬 자료와 읍지(邑誌), 사례(事 例) 등을 비교 검토하였다. 이 연구를 통해 19세기 조선 해군 전력의 일 단을 확인하였다. 당시 조선 정부는 해양 방위[海防]에 상당한 관심을 가 지고 있었지만 이에 대응한 해군 전력의 향상은 적절히 이루어지지 못한 것으로 보인다. 이는 본 연구를 통해 일부 확인되는 것처럼 특히 지방 군현의 수군 전력은 형식적 전력을 유지하는 데 그쳤고, 그 실제는 전력 이 약화되고 있었던 것으로 여겨진다.

This study deals with the application of an artificial neural network (ANN) model to predict power consumption for utilizing seawater source heat pumps of recirculating aquaculture system. An integrated dynamic simulation model was constructed using the TRNSYS program to obtain input and output data for the ANN model to predict the power consumption of the recirculating aquaculture system with a heat pump system. Data obtained from the TRNSYS program were analyzed using linear regression, and converted into optimal data necessary for the ANN model through normalization. To optimize the ANN-based power consumption prediction model, the hyper parameters of ANN were determined using the Bayesian optimization. ANN simulation results showed that ANN models with optimized hyper parameters exhibited acceptably high predictive accuracy conforming to ASHRAE standards.

In this paper, a tidal power conversion system (PCS) using seawater level differences was presented.. To verify the presented PCS, an actual lab-scale tidal power generation system was constructed. The operation of the lab-scale PCS was first modeled mathematically and was analyzed through dynamic simulation and experimental tests.

The Korean military has sought to build an all-round military force against the national and international security environment and future asymmetric threats as well as the military threats it faces. However, while raising the need for timely electrification, there are few cases of quantitatively evaluating the loss when electrification is delayed, making it difficult for our military to provide a logical basis to support the importance of the electrification period. Therefore, through this study, we tried to analyze the index of loss cost that can support the need for timely electrification with logical and quantitative data and present it as a logical basis. To this end, the loss cost was calculated in terms of combat efficiency, equipment utilization rate, and maintenance requirements, which can be quantitatively calculated based on “combat readiness,” a general impact on the military in case of delayed timely electrification.

The 4th Industrial Revolution and the continuous development of Science and Technology have also required a speedy business promotion method in the defense industry. Advanced countries including the United States are already boldly innovating the existing high-cost and long-term acquisition system with the highest priority in weapons development to cope with the military rise of Russia and China. The Ministry of National Defense and the Defense Acquisition Program Administration have also recently introduced a quick acquisition system and are applying it to business promotion. In addition, some small-scale projects and weapons systems are being reorganized so that they can be managed by the units demanding them. After an organizational diagnosis of the Project Acquisition Group by the Ministry of National Defense in 2020, it has been reassigned as a subordinate unit of the Army Logistics Command from a direct unit managed by the Army HQ. As a result, problems such as work conflict or redundancy have been identified. In addition, a system has been implemented to shorten the acquisition period by applying a rapid acquisition program in the field of weapons systems by benchmarking the rapid acquisition program of advanced countries. The force support system project process will also need to introduce such a quick acquisition system. In addition, the Ministry of National Defense is considering ways to delegate some weapon systems to each military, which will then carry out tasks ranging from requirements determination to project management. Accordingly, it is now time to expand the organization for the management of the Army's weapons system acquisition project. Therefore, in this paper, the Army Project Acquisition Group was analyzed on its organization, acquisition procedures, and cooperation systems, with presentations of development plans for each field.

Smart factory companies are installing various sensors in production facilities and collecting field data. However, there are relatively few companies that actively utilize collected data, academic research using field data is actively underway. This study seeks to develop a model that detects anomalies in the process by analyzing spindle power data from a company that processes shafts used in automobile throttle valves. Since the data collected during machining processing is time series data, the model was developed through unsupervised learning by applying the Holt Winters technique and various deep learning algorithms such as RNN, LSTM, GRU, BiRNN, BiLSTM, and BiGRU. To evaluate each model, the difference between predicted and actual values was compared using MSE and RMSE. The BiLSTM model showed the optimal results based on RMSE. In order to diagnose abnormalities in the developed model, the critical point was set using statistical techniques in consultation with experts in the field and verified. By collecting and preprocessing real-world data and developing a model, this study serves as a case study of utilizing time-series data in small and medium-sized enterprises.

Recent, there has been a need for a terminal device with artificial intelligence to detect emergency situations in various means of transportation to prevent overdischarge of the battery even when parking the vehicle for a long time so that the driver can properly prepare. The transmission system, which guides the situation and location information of the vehicle, uses AHD video technology and RTOS technology to reduce the load of wireless networks by increasing the video playback rate through UDP implementation by WiFi, and stabilizes through wireless networks and low-power sensors using LoRa services.

Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%.