• The Journal of Industrial Distribution & Business
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• v.15 no.8
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• pp.21-27
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• 2024

Purpose: There is a significant opportunity for ESG management to act as a useful guideline for social welfare organizational structures when dealing with sustainability and ethical leadership. The ESG guidelines should allow these companies to improve their business efficacy. This paper aims to explore the specific impacts of ESG management on social welfare. Research design, data and methodology: The systematic review approach ensures that quality work is undertaken in tackling the existing gaps in the literature on ESG management in social welfare organizations. The outcomes of this review will give a useful 'real-life' picture of the consequences of ESG practices and suggestions that can increase the efficiency and sustainability of social welfare organizations. Results: The principal favorable consequences are discussed in this chapter regarding the social welfare organization due to the implementation of ESG management. Subsequently, each effect is posted under different sub-titles and evidence from previously conducted research studies. Conclusions: ESG management is vital for social welfare organizations since it increases their efficiency in operations, public image, and opportunities to receive funds, and it helps improve relations with stakeholders. More so, these organizations can embrace the ESG practices and as a result bring more efficiency to the general welfare of the society.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.140-147
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• 2024

Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.639-643
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• 1996

The manufacturing system has been changed from labored manual process system, which is managed and operated by managers and operators, to CIMS(Computer Integrated Manufacturing System) for integration of manufacturing, research, development and consumption in the age of diverse customer's needs[6]. However, because it involves the hierarchical system composed of many sub-systems interface and its installation & setup cost is very expensive, CIMS has many difficulties in constructing the durable optimal system that is able to adapt to rapid in-outer circumstance change. So, HMS(Holonic Manufacturing System), the new conceptual manufacturing system having the self-problem-solving and self-organization[11], is instructed to solve these difficulties that it has in these days. The system flexibility in the HMS is able to be ensured, with the integration of human's strong points into mechatronics manufacturing system to reduce interference among sub-systems. In this paper, the manufacturing process rationalization and integration of the assembly line in an automobile industry, has lots of problems in efficiency and productivity, has been studied in an early stage of converting the present state of process system to HMS, which is human-oriented processing system, to improve the line efficiency, system productivity and reliability by using human capability effectively. This paper is derived into the human-oriented & object-oriented holons settlement of the shop floor system composed of processing, assembly and material handling system for the future holonic manufacturing system, which is going to be computer supported control system.

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.66-79
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• 2024

The model developed in this study holds significant importance in predicting carbon emissions in maritime transport. By utilizing ship data and EEDI (Energy Efficiency Design Index) guidelines, the model presents a highly accurate prediction tool, providing a solid foundation for maximizing operational efficiency and effectively managing carbon emissions in ship operations. The model's accuracy was demonstrated by an R² score of 0.95 and a Mean Absolute Percentage Error (MAPE) of 1.4%. Through SHAP (SHapley Additive exPlanations) and Partial Dependence Plots (PDP), it was identified that Speed Over Ground and relative wind speed are the most significant variables, both showing a positive correlation with increased CO2 emissions. Additionally, environmental factors such as exceeding an average draft of 22(m), a Leeway over 5°, and a current angle exceeding 200° were found to increase emissions significantly. Specific ranges of wind and swell wave angles also notably affected emissions. Conversely, lower pitch, roll, and rudder angle were associated with reduced emissions, indicating that stable ship operation enhances efficiency.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1049-1055
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• 2023

The utilization of agricultural drones for pest control operations has been increasing due to its economic efficiency. However, variations in the effectiveness of these operations occur depending on the operator's proficiency. In this study, we applied a smart operating mode to overcome the limitations of manual flight mode and proposed a numerical model. Through comparative validation with prior research, we conducted experimental verification. As a result, we determined the spray time and calculation of spray area for each drone model. We selected a drone for pest control with a high similarity to the numerical model and verified it experimentally. Through this, we confirmed that the application of the smart operating mode is more effective in terms of calculation of spray area and operational efficiency compared to manual flight mode.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.603-605
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• 2015

Recent IoT (Internet Of Things) development of the technology is growing rapidly. When multiple devices to perform operations on the IoT environment, it is possible to improve the efficiency of operations by different devices to join the collaborative relationship (Relation) between. Research on existing methods and has been used and the user to issue commands to each device P2M (Person to Machine) method, is now being replaced by effective M2M (Machine to Machine) manner than by way bring forth the relationship between the device P2M. In this paper, we define the relationship between the device and bring forth proposals for collaborative data transfer algorithms. To block the operation duplicated between different work through the proposed algorithm and is believed to improve the efficiency of work to do.

• KIEAE Journal
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• v.13 no.4
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• pp.11-19
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• 2013

The purpose of this study is to establish the assessment baseline of $CO_2$ emissions from building operations in the view of GHG reduction policy in Korea. The assessment baseline of $CO_2$ emissions shall be used in GHG policy and Carbon Credits in building sectors, but the assessment baseline has not been studied enough or established yet. Also, $CO_2$ emissions from building operations will be variable according to the building occupancy. Therefore the baseline will be different and this study aimed at the establishment of the assessment baseline for residential apartments and office buildings firstly. After reviews of BEER and international standards for building $CO_2$ emissions such as ISO and UNEP-SBCI documents, the analysis of BEER certification data has been pursued for 292 residential apartment complexes and 65 office buildings in South Korea during 2004~2012. As analysis results, the assessment baseline was set to 23.03 $kg{\cdot}CO_2/m^2{\cdot}yr$ or 1.95 $t{\cdot}CO_2/unit{\cdot}yr$ for residential apartment complexes, and 95.91 $kg{\cdot}CO_2/m^2{\cdot}yr$ for office buildings according to the BEER certification basis. Additional assessment baselines were calculated according to year basis, region basis, public and private basis, and GHG policy basis. Finally, the established baseline for residential apartment complexes has been applied for the pilot project in M district, Seoul, and showed 24.97% reduction rate according to the BEER certification basis.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2148-2153
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• 2007

The electricity conversion-efficiency of solar cell for commercial application is about 6-15%. More than 85% of the incoming solar energy is either reflected or absorbed as heat energy. Consequently, the working temperature of the photovoltaic cells increases considerably after prolonged operations and the cell's efficiency drops significantly. PV/T refers to the integration of a PV module and a solar thermal collector in a single piece of equipment. By cooling the PV module with a fluid steam like air or water, the electricity yield can be improved. At the same time, the heat pick-up by the fluid can be to support space heating or service hot-water systems. In this study, a pulsating heat pipe solar heat collector was combined with single-crystal silicon photovoltaic cell in hybrid energy-generating unit that simultaneously produced low temperature heat and heat and electricity. This experiment was investigating thermal and electrical efficiency for evaluation of a PV/T system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1034-1037
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• 2003

Microcrystalline silicon(c-Si:H) thin-film solar cells are prepared with intrinsic Si-layer by hot wire CVD. The operating parameters of solar cells are strongly affected by the filament temperature ($T_f$) during intrinsic layer. Jsc and efficiency abruptly decreases with elevated $T_f$ to $1400^{\circ}C$. This deterioration of solar cell parameters are resulted from increase of crystalline volume fraction and corresponding defect density at high $T_f$. The heater temperature ($T_h$) are also critical parameter that controls device operations. Solar cells prepared at low $T_h$ ($<200^{\circ}C$) shows a similar operating properties with devices prepared at high $T_f$, i.e. low Jsc, Voc and efficiency. The origins for this result, however, are different with that of inferior device performances at high $T_f$. In addition the phase transition of the silicon films occurs at different silane concentration (SC) by varying filament temperature, by which highest efficiency with SC varies with $T_f$.