The adoption of generative artificial intelligence (AI) has attracted growing attention across industries due to its potential to transform organizational processes and value creation. Despite its high applicability, however, the diffusion of generative AI in the telecommunications industry remains limited. Existing studies have largely focused on identifying individual barriers to AI adoption, providing insufficient understanding of how these barriers interact and form a complex hierarchy of constraints. Addressing this gap, this study investigates the structural interrelationships among barriers to generative AI adoption in the telecommunications industry. Based on a comprehensive literature review and expert validation, fifteen key barriers were identified. Using a Delphi-based Interpretive Structural Modeling (ISM) approach, this study examined the hierarchical influence structure among the barriers. Subsequently, the Matrix Impact Cross-reference Multiplication Applied to Classification (MICMAC) technique was employed to classify the barriers according to their driving power and dependence. The results reveal a four-level hierarchical structure in which environmental barriers play a foundational role. In particular, the absence of alignment in institutional frameworks and technical standards emerges as a root-level barrier exerting strong influence on higher-level constraints. Regulatory uncertainty and concerns about job displacement function as independent drivers linking foundational environmental conditions to execution- level constraints. Most technical, organizational, and economic barriers are concentrated at the intermediate level, forming a highly interdependent execution layer. At the top level, delays and uncertainties in decision-making regarding generative AI adoption appear as outcome-oriented barriers resulting from the cumulative effects of lower-level constraints. By highlighting that barriers to generative AI adoption in the telecommunications industry operate as a structurally connected system rather than isolated factors, this study extends existing adoption research through a structural perspective. The findings provide practical insights for telecommunications firms in prioritizing adoption strategies and offer implications for addressing institutional and regulatory conditions that shape the diffusion of generative AI.

본 연구는 공공기관 구성원을 대상으로 진성리더십, 조직지원인식, 직원몰입, 직무성과 간의 구조적 관 계를 분석하는 것을 목적으로 하였다. 이를 위해 1년 이상 재직한 공공기관 구성원을 대상으로 자료를 수집 및 분석하여 다음과 같은 연구결과를 도출하였다. 첫째, 진성리더십과 조직지원인식은 직무성과에 통계적으로 유의한 영향을 미치지 않았다. 둘째, 진성리더십과 조직지원인식은 모두 직원몰입에 정(+)적 영향을 미치는 것으로 확인되었다. 셋째, 직원몰입은 직무성과에 유의한 정(+)적 영향을 미치는 것으로 나타났다. 넷째, 직원몰입은 진성리더십과 조직지원인식, 직무성과 간 관계에서 매개효과를 보였다. 이러 한 연구결과는 공공기관의 성과 창출 메커니즘에서 리더십과 조직지원이 직접적인 성과 동인이 되기보 다, 구성원의 심리적 몰입을 점화시키는 촉진제로 기능함을 보여준다. 즉, 외적 보상이 제한된 환경에서 실질적인 직무성과는 구성원의 내재적 동기화 과정인 ‘몰입’을 통해서만 발현됨을 입증하였다.이러한 연 구결과를 바탕으로 학문적·실무적 시사점과 후속 연구에 대한 제언을 제시하였다.

This study investigates the internal structure of the Habitat and Riparian Health Index (HRI) by identifying conditional dependencies among its components and the mechanisms that form grade boundaries, rather than treating HRI as a simple arithmetic sum. Using the 2024 national river assessment dataset, the analysis combined bootstrap-supported Bayesian Networks for stable dependency inference with classification decision trees for explicit grading rules and threshold identification. A multi-criterion priority scheme integrating network centrality, contribution to total-score variability, and classification contribution was also applied to derive management priorities within and across basins. Across all basins and analytical perspectives, Flow Velocity Diversity consistently emerged as the most influential component. It occupied the central position in the dependency structure and accounted for the largest share of variability in the composite score, indicating that it operates as a system-level outcome in which channel morphology, bed condition, and anthropogenic constraints converge. The grading mechanism was strongly asymmetric. Deficiencies in riverbank protection functioned as a dominant trigger for rapid grade deterioration, whereas attainment of the highest grade required a conjunctive and non-linear pathway in which sufficient flow heterogeneity was accompanied by the sequential resolution of structural constraints, particularly those associated with transverse structures and embankments. Basin-level comparisons further showed that network structures were not interchangeable, with the Nakdong River basin exhibiting the most distinct configuration and basinspecific priority patterns. These results imply that management should separate strategies aimed at preventing degradation through bottleneck control from strategies aimed at achieving top-tier conditions through coordinated, multi-component interventions.

AI-driven automation for structural design has been actively studied in structural engineering. In particular, reinforcement learning (RL) has attracted attention as a framework in which an agent interacts with an environment to autonomously search for optimal design solutions in complex design spaces. This study proposes an automated design model for rectangular reinforced-concrete (RC) columns based on a multi-agent Double Deep Q-Network (Double DQN). Extending prior RL-based automation developed for RC beam design to column members, the proposed environment explicitly incorporates key column-specific behaviors, including axial force–bending moment (P–M) interaction and moment magnification due to column buckling. Four agents independently determine the section width (b), section depth (h), number of longitudinal bars (n), and bar size. The reward function combines (i) penalty terms for violations of ACI 318-19 design constraints and (ii) an economic reward defined relative to an approximate optimal cost predicted by a quadratic regression model. After training for approximately 10,000 episodes, the proposed multi-agent Double DQN consistently generated ACI-compliant column designs across all test load cases and produced solutions with improved cost efficiency compared with the approximate optimal baseline. These results demonstrate the feasibility and practical potential of multi-agent RL for automated RC column section design.

The Gopura in Preah Pithu T temple, which is partially damaged and collapsed, is densely wooded and has a high percentage of humidity due to moats and ponds, the stone materials are not in good condition and significantly damaged due to intrinsic structural defects and other damage factors. The examination of major endangered and vulnerable parts through status analysis is also necessary in order to restore the Gopura in T temple in a more structurally stable state. This study proposes the effective structural safety inspection measures by applying rational structural modeling and structural analysis method reflecting the damage type by construction type and carrying out structural safety evaluation by damage type and member based on the results of analysis.

In this study, a non-welded beam-to-column connection applicable to the extension and renovation of pipe-rack structures was proposed. The structural performance of the proposed connection was verified at the component level through preliminary finite element analyses. In order to verify structural performance of beam-to-column connection implementing panel zone reinforcing elements, full-scale quasi static test was conducted. As a result, the specimen incorporating box-type panel zone reinfocing element exhivited maximum strength approaximatly 1.3 times higher than that of the specimen with existing connection detail of which structural behavior was governed by weak panel zone deformation. However, the specimen with suggested detail shows stable ductile behavior due to reduction of stress concentrated on the beam-to-column connection since the applied forces were distributed through the yielding of the beam end plate and the reinforcing element inserted into the panel zone.

국내 고속도로 콘크리트 포장은 주로 줄눈 콘크리트 포장(JCP) 형식으로 시공되어 줄눈부 파손에 따른 유지관리 부담이 지속되고 있으며 이를 보완하기 위해 연속철근 콘크리트 포장(CRCP)이 확대 적용되고 있다. 하지만 기존의 노후화된 JCP를 CRCP로 전환하는 기술에는 한계가 있는 실정이다. 이에 본 연구에서는 공용성과 시공성을 동시에 확보하기 위해 CRCP 형 식과 프리캐스트 콘크리트 포장 공법을 접목한 프리캐스트 CRCP 슬래브를 설계하였다. 슬래브 내부의 철근비를 0.68%로 설계하여 배근하였으며 타이바 포켓은 슬래브 측면 중앙부에 배치하도록 설계하였다. 유한요소해석과 모멘트 분포 분석을 수행하여 슬래브 상부에 최적 인양 위치를 선정하였으며 매립형 인양 장치를 배치하였다. 또한 그라우트 주입구는 차선 기 준으로 슬래브 외곽부 중앙에 위치하도록 설계하였다. 슬래브의 연결부는 덮개 형식으로 구성하였으며 상부 덮개에는 앵커 를 설치하여 그라우트의 탈락을 방지하였다. 연결부에는 연속철근을 노출시켜 인접되는 슬래브와의 거동이 일체화되어 CRCP의 특성을 발휘하도록 설계하였다.

Al–Mg co-doped ZnO thin films were fabricated by a sol–gel spin-coating process to investigate the effect of dopant ratio on their structural, electrical, and optical properties. The total dopant concentration was fixed at 3 mol%, while the Al-to-Mg ratio was systematically varied in AlxMg0.03-xZn0.97O (0 ≤ x ≤ 0.03). X-ray diffraction analysis showed that the films maintained a hexagonal wurtzite structure with a preferred (002) orientation up to an Al concentration of 1.5 mol%, whereas higher Al contents resulted in a degradation of crystallinity due to exceeding the solid solubility limit of Al in the ZnO lattice. Hall effect measurements revealed a decrease in carrier mobility with increasing Al content, attributed to enhanced ionized impurity scattering, while the carrier concentration and electrical conductivity reached optimal values at an Al–Mg co-doping ratio of 1.5 mol%–1.5 mol%. All films exhibited high optical transmittance in the visible region, with the highest average transmittance of approximately 83% observed at the same composition. These results demonstrate that controlling the Al/Mg dopant ratio is crucial for optimizing the performance of ZnO-based transparent conducting oxide thin films.

In the fabrication of curved steel plates for shipbuilding, post line-heating is widely used to induce plastic deformation by applying local heat and controlling residual stress. However, the process is still dependent on skilled labor and empirical methods, making it difficult to ensure consistent quality and precision. To improve the automation and standardization of the post line-heating process, this study aims to investigate the relationship between heating conditions and the resulting deformation behavior of marine structural steel plates. Experiments were conducted on AH36 steel specimens under 24 different heating conditions, including three plate thicknesses (12mm, 16mm, 20mm), two heating speeds, two gas flow ratios, and two torch tip types. Maximum deformation was measured across 15 locations per case. The results showed that thinner plates exhibited greater deformation, and higher heat input—such as slower heating speed and higher gas flow—led to increased deformation. The 800-type torch tip, with a narrower flame focus, also induced larger deformation than the 1000-type. These findings provide fundamental data for optimizing post line-heating parameters and establishing automated correction processes in shipbuilding applications.

This study investigates the deformation behavior of AH32 steel plates under various line heating conditions in the post line-heating process. A total of 24 experimental cases were conducted by varying material thickness (12mm, 16mm, 20mm), heating speed, oxygen and acetylene flow rates, and torch tip size. Deformation was measured at 35 points per specimen, with emphasis on the maximum deformation at the 300mm X-axis location. The deformation results were classified into three groups: high (≥4.0mm), medium (2.0–3.9mm), and low (≤1.0mm). The results confirmed that material thickness had the greatest effect on deformation, followed by heat input parameters such as heating speed and gas flow rate. High deformation occurred under low heating speed and high flow rate conditions, while low deformation was observed in thick plates with fast heating and low flow rates. These findings highlight the importance of controlling heat input and geometric factors for deformation correction. The data acquired from this study can be utilized as a reference for optimizing automated post line-heating processes in shipbuilding.

In this study, a thermal-fluid-structure coupled analysis was performed to improve the thermal performance of a burner for a coal gasification power plant. After combustion analysis, an average temperature of 1,400°C was obtained, closely matching the actual coal gasification system environment. The highest burner tip surface temperature, 887°C, was achieved at the analysis variable, a coal fines inflow velocity of 8m/s. This temperature was mapped to a thermal-structural analysis model, and by increasing the radius of the cooling channel inside the burner to 5 mm, the analysis confirmed a reduction in thermal stress of approximately 20%. In particular, changing the material to HP50-Nb resulted in significantly superior cooling efficiency compared to Inconel 718 without any cooling channel design. The results of this study will be useful for the optimal design of coal gasification facilities as well as for improving the durability of the facilities.

본 연구는 남북군사회담에서 한반도 평화체제와 관련하여 주요 쟁점으 로 논의된 정전협정의 평화협정 전환, 군사적 신뢰구축, 비핵화 및 안전 보장 문제를 『6·15 남북공동선언』 전후로 비교·분석하여 평화체제 구축 의 구조적 특성을 규명하였다. 연구 결과, 평화체제 발전은 의제별로 상 이하였다. 평화협정 전환은 6·15 이전 선언 단계에서 제도화 단계로 발 전했으나 원칙적 합의 단계는이행되지 못했다. 6·15 이후 원칙적 합의 단계와 제도화 단계가 구체화되었으나 정세 악화로 후퇴하였다. 군사적 신뢰구축은 선언 단계와 원칙적 합의 단계를 거쳐 제도화 단계로 발전했 으나 중단되었고, 2018년 9·19 군사합의에서 이행 단계가 시작되었으나 북·미 협상 결렬로 중지되었다. 비핵화는 원칙적 합의 단계와 제도화 단 계를 시도했으나 검증 갈등과 북미 협상 결렬로 이행되지 못하였다. 결 론적으로 세 의제 모두 선언 단계, 원칙적 합의 단계, 제도화 단계까지 진전되었으나 이행으로 발전하지 못했다. 남북의 자유주의적 제도화 노 력에도 불구하고 국제정치적 제약과 북한 도발이라는 현실주의적 요인이 이행을 차단한 구조적 딜레마의 결과이다. 따라서 협력과 억제의 균형, 상시적 소통체계의 제도화, 합의 이행을 담보할 법적 기반 강화, 국제적 협력을 포함한 다층적 보장 구조가 병행되어야 한다.

In conventional construction methods, the slab-balcony junction often experiences thermal bridging. This phenomenon arises from the discontinuity of insulation materials, leading to energy loss and condensation that can compromise the structure's usability and durability. To address this issue, thermal break insulation systems were installed between the slab and balcony to effectively prevent thermal bridging and energy loss, thereby improving the overall energy efficiency of buildings. This study aims to enhance both the structural performance and thermal efficiency of slab-balcony connections in residential buildings. To assess the impact of the thermal break insulation system, two experimental specimens were prepared: one incorporating the system and the other without it. Experimental results confirmed that the inclusion of reinforcing bars significantly improved the connection's structural load-bearing capacity. Furthermore, thermal analysis revealed that the thermal break insulation system outperformed conventional insulation methods by reducing the thermal damage ratio and maintaining higher surface temperatures at the connection. In addition, a structural analysis using an FEM (finite element analysis) program was conducted to evaluate the load distribution across the specimens, demonstrating that the experimental data accurately predicted the structural behavior of the connections.

본 연구는 공공서비스 AI가 인권을 침해하는 구조적 메커니즘을 분석하고, 인권기반 거버넌스 모델을 제시하는 것을 목적으로 한다. 공공서비스 AI의 권리 침해는 단순한 기술 결함이 아닌 제도 설계와 운영 과정에서 구조적으로 발생한다. 이에 본 연구는 인권기반접근(HRBA)을 이론적 토대로 삼아, 네덜란드 SyRI와 호주 Robodebt 사례를 비교 분석하였다. 분석 결과, 공공서비스 AI의 인권 침해는 3단계 메커니즘 을 통해 형성되고 누적된다. 첫째, 설계 단계에서 행정 효율성 중심의 목표가 우선되면서 권리 보호 장치가 충분히 내장되지 못한다. 둘째, 운영 단계에서 자동화된 판단이 알 권리와 이의제기권을 실질적으로 약화 시킨다. 셋째, 결과 단계에서 사회경제적 취약 집단에 감시와 제재가 불균형하게 집중된다. 이러한 발견에 기초하여 본 연구는 공공서비스 AI를 국가 권력 행사의 새로운 인프라로 재정의하고, 인권영향평가(HRIA) 를 핵심으로 하는 거버넌스 체계를 제안한다. 이는 기존의 위험기반 규제가 간과한 절차적 권리 보장과 구조적 차별 통제를 통해 공공서비스 AI 거버넌스의 인권적 공백을 보완하는 데 기여한다.

Since the National Emergency Management Agency’s seismic fragility function, developed in 2009, classified domestic buildings by structural type, numerous studies have used this classification. In 2021, the updated seismic fragility function adopted a slightly more complex classification logic, limited to concrete structures. Data for structural-type classification were derived from information in the building register, including primary use, floor area, permit date, and number of stories. To verify and improve the accuracy of the classification logic, a sample of approximately 1,800 from about 13,000 concrete buildings in a specific region was selected. Structural types classified by the logic were compared with those identified through road views provided by the Architecture HUB. The results confirmed that the existing classification logic requires revision to incorporate additional variables, including the sub-use of the building and the area-by-use on the first floor. The revised logic significantly improved classification accuracy by including those variables.

Sodium-ion batteries (SIBs) have emerged as a promising alternative to lithium-ion batteries due to the natural abundance and low cost of sodium resources. However, the relatively large ionic radius of sodium ions hinders their intercalation into conventional graphite anodes, necessitating the development of advanced anode materials. In this study, high-performance hard carbon materials were synthesized from ZIF-8 precursors through controlled carbonization at various temperatures. Among the samples, ZIF-800, which is carbonized at 800 °C, exhibited the highest reversible capacity (156.63 mAh/g after 100 cycles at 100 mA/g) and excellent cycling stability. This superior performance is attributed to the optimized combination of high specific surface area (700.35 m2/ g), well-developed pore structure, and enhanced defect concentration, as indicated by a low IG/ ID ratio. The capacitive-dominant charge storage behavior further contributes to the improved electrochemical characteristics. These findings highlight the critical role of tuning carbonization temperature to achieve a balanced microstructure, offering valuable insights for the rational design of high-performance hard carbon anodes for SIBs.

The rapid expansion of the fast fashion industry has led to a dramatic increase in textile waste, posing significant environmental and systemic challenges. Although approximately 95% of discarded clothing is technically recyclable, current recycling system remains inefficient due to fragmented collection, manual sorting, limited recycling capabilities, and a lack of integrated data management. This study investigates the structural limitations of Korea’s waste clothing recycling system and proposes optimization strategies grounded in circular economy principles. These strategies, if implemented, have the potential to significantly improve the efficiency and effectiveness of Korea’s textile waste recycling system. Through a comparative analysis of international models― including government-led Extended Producer Responsibility (EPR) systems, digital platform-based collection services, and brand-driven recycling initiatives―the study identifies key bottlenecks in Korea’s current system. The findings highlight the need for a unified and monitored collection infrastructure, the deployment of AI-based automated sorting technologies, and the development of fiber-to-fiber (F2F) recycling processes supported by standardized classification codes and centralized databases. Furthermore, the study emphasizes the importance of real-time data integration across all stages of the recycling chain to enable transparent tracking and performance evaluation. Drawing on successful PET bottle recycling cases, the research outlines a roadmap for transitioning Korea’s textile waste management to a scalable, sustainable circular economy. The study concludes by calling for robust institutional support, legal clarity, and most importantly, cross-sector collaboration. This collaboration is crucial to ensure effective implementation of EPR and long-term resource circulation, and it will require the collective efforts of environmental policymakers, waste management professionals, industry stakeholders, and researchers.

본 연구는 선박용 내연 기관에 적용되는 연료 분사 노즐을 대상으로, 수소 연료 운전 조건에서의 구조적 거동을 규명하기 위해 정적 열-구조 연성(static thermo-structural coupled) 유한요소 해석(FEA)을 수행하였다. 해석은 상용 프로그램 ANSYS Mechanical 2025 R1을 사 용하였으며, 주요 경계 조건으로 연료 공급 온도 -60°C~120°C, 연료 공급 압력 60 bar 및 연료 분사 압력 60 bar를 적용하였다. 또한 노즐 니들의 개폐(open/close) 상태를 각각 모델링하여 니들의 개폐에 따른 구조적 응답 변화를 비교하였다. 해석 결과, 노즐의 최대 등가 응력 (maximum equivalent stress)은 니들 폐쇄 상태에서 니들 개방 상태에 비해 약 1.6배 높게 나타났으며, 최대 등가 응력은 모든 조건에서 유로 벽면에 집중되었다. 이러한 결과는 수소 연료 적용 시 노즐의 잠재적 취약 부를 사전에 예측할 수 있음을 시사하며, 내수소성 확보를 위 한 재료 선정 및 구조 보강 설계의 기초 자료로 활용될 수 있다. 제안된 해석 접근법은 향후 수소 내연기관용 노즐의 내구성 향상, 형상 최적화 및 신뢰성 평가를 위한 기반 연구로서 의의가 있다.

지진에 대한 플랜트 시스템의 확률론적 안전성 평가(Probabilistic Safety Assessment, PSA)를 수행하기 위해 고장수목(Fault Tree) 기반의 베이지안 네트워크(Bayesian Network, BN) 방법론이 제안된 바 있다. 해당 PSA를 수행하기 위해서는 구조물 및 설비들의 지 진 취약도 곡선 정보는 필수적이며, 해당 정보는 Federal Emergency Management Agency(FEMA)에서 일부 제공하고 있다. 그러나 다 양한 종류의 설비에 비해 제공되는 정보는 매우 제한적이며, 특히 플랜트 운영지속성을 위해 여분의 설비가 배치된 경우에도 개별 설 비의 구조적 상태가 반영되지 못하고 같은 정보가 사용되어, 결과적으로 일률적인 리스크 평가와 제한적인 의사결정만이 이루어질 수 있음을 확인하였다. 따라서 본 연구에서는 플랜트의 여러 주요 설비 중 석유화학 플랜트의 증류탑을 선정하고, 증류탑의 손상 메커 니즘을 모사 가능한 조이스틱 모델을 구축하였다. 이와 더불어 지진 취약도 해석 기법 세가지(다중띠해석, 증분독적해석, 산점도분석 법)에 대해 간략히 설명하고 주어진 예제에 대해 각 기법을 이용하여 취약도 곡선을 도출하였다. 도출된 결과에서 세기법의 차이가 크지 않음을 확인하였고, 앵커 파단과 같은 구조적 손상 시나리오를 가정하여 취약도를 도출하였는데, 이 결과를 토대로 개별 설비의 구조적 상태에 따라 상이한 취약도 곡선이 필요함을 확인할 수 있었다.

This study examined the structural, physicochemical, and functional characteristics of five black soybean (Glycine max (L.) Merr.) cultivars—Cheongja5, Danheuk, Socheongja, Seum, and Soriheuk—bred and cultivated in Korea. We conducted comprehensive analyses on morphology, microstructure, thermal and hydration properties, pasting behavior, and antioxidant activity to identify cultivar-specific differences in processing suitability and functional properties. The results indicated significant varietal variations in seed coat ratio, cotyledon density, and color, which affected thermal stability, hydration, and viscosity development during heating. Cultivars with compact cotyledon matrices, such as Cheongja5 and Danheuk, displayed high enthalpy (ΔH), low solubility, and limited viscosity development, suggesting high structural stability and low thermal reactivity-traits favorable for thermally stable or beverage-type applications. In contrast, cultivars with looser structures and greater surface exposure, like Seum and Socheongja, exhibited higher swelling power, dispersion stability, and RVA viscosities, indicating their suitability for viscous or semi-solid systems. Notably, Soriheuk showed the highest antioxidant activity and levels of phenolic and flavonoid compounds, correlating with its high seed coat ratio and dark pigmentation, positioning it as a promising functional ingredient. These findings underscore that the physicochemical and structural diversity among black soybean cultivars significantly influences their processing performance and functional potential, providing a scientific foundation for selecting and developing functional cultivars.