• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.5904-5927
• /
• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• Journal of Korean Society for Quality Management
• /
• v.46 no.4
• /
• pp.959-972
• /
• 2018

Purpose: This study developed a simulation model that incorporates the uncertainty of demand and yield to obtain optimized results for supply chain coordination within environmental constraints. The objective of this study is to examine whether yield management for perishable products can achieve the goal of supply chain coordination between a single buyer and a single supplier under a variety of environmental conditions. Methods: We investigated the efficiency of a revenue-sharing contract and a wholesale price contract by considering demand and yield uncertainty, profit maximizing ratio, and success ratio. The implications for environmental variation were derived through a comparative analysis between the wholesale price contract and the revenue-sharing contract. We performed Monte Carlo simulations to give us the results of an optimized supply chain within the environments defined by the experimental factors and parameters. Results: We found that a revised revenue-sharing contracting model was more efficient than the wholesale price contract model and allowed all members of the supply chain to achieve higher profits. First, as the demand variation (${\sigma}$) increased, the profit of the total supply chain increased. Second, as the revenue-sharing ratio (${\Phi}$) increased, the profits of the manufacturer gradually decreased, while the profits of the retailer gradually increased, and this change was linear. Third, as the quality of yield increased, the profits of suppliers appear to increased. At last, success rate was expressed as the profit increased in the revenue-sharing contract compared to the profit increase in the wholesale price contract. Conclusion: The managerial implications of the simulation findings are: (1) a strategic approach to demand and yield uncertainty helps in efficient resource utilization and improved supply chain performance, (2) a revenue-sharing contract amplifies the effect of yield uncertainty, and (3) revised revenue-sharing contracts fetch more profits for both buyers and suppliers in the supply chain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.189-192
• /
• 2014

Recently, U.S. and Europe, which are advanced to Air Traffic Control Management, are interest in replacing Radar System with Communications, Navigation and Surveillance(CNS) and Air Traffic Management(ATM). They pursue to research the efficient Air Traffic Control Management. This paper covers ADS-B 1090ES system which is one of CNS/ATM surveillance systems. This research satisfied all performance required by RTCA DO-268B and EUROCAE ED-129. It optimized algorism to mainly enhance performance such as quality of receiver signal, dynamic range, and so on. The optimized mechanism provided stable performance of demodulation, tuned the level of signal, and had reduced the false reception ratio by the signal level difference. The analyzed algorism helped great performance and will be considered to apply broad system applications.

• Journal of the Korea Safety Management & Science
• /
• v.15 no.4
• /
• pp.17-24
• /
• 2013

On this study, we extracted pending problem and controversial point from management of disaster such as terror for domestic massive performance and then, investigated countermeasure plan against disaster for massive performance through comparison and analysis between anti-disaster strategy of Korea and U.S. U.S are conducting security system actively for passenger of major facilities such as public institution. Nonetheless, In U.S that has the world's best security system, serious affair such as 911 terror and Boston marathon terror are continued to happen. When considering domestic situation that North Korea and South Korea are antagonistic to each other, it is judged when it is high time to prepare for threat of terrorism. Accordingly, On this study, through analyzing of latest terror attacks in U.S and disaster risk in the nation, we analyzed in detail countermeasure plan classified as legislation, operation of security system, instilling a sense. As the result of this analyzing, using by flow-chart, we suggested domestic optimized disaster management system for massive performance. Consequently, we propose to establish systematized disaster management system such as preliminary survey of disaster influence for massive performance.

• Journal of IKEEE
• /
• v.16 no.4
• /
• pp.310-315
• /
• 2012

This thesis is intended to design multi thread mobile GPGPU optimized in mobile environment, and to verify an effective thread management method of the multi thread mobile processor. In thread management, there is no management hardware and implement with software instructions. For the verification of the multi thread management method, Lane detection algorithm was implemented to compare nVidia's CUDA Architecture and the designed GPGPU in terms of thread management efficiency. The number of thread is normalized to 48 threads. An implemented Land Detection Algorithm is composed of Gaussian filter algorithm and Sobel Edge Detection algorithm. As a result, the designed GPGPU's thread efficiency is up to 2 times higher than CUDA's thread efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.11
• /
• pp.2677-2682
• /
• 2015

Smart factory has the function of integrated management of production process management, logistics management as a intelligent factory, it is also emerging as the core of new industry which converges ICT and manufacturing business. We suggested Smart factory logistics management system which embedded position tracking technology and the system converges ICT and IoT. This suggested system can manage all the processes from production to release by tracking route and position based on signal strength of bluetooth 4.0 beacon tag. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• Smart Structures and Systems
• /
• v.30 no.6
• /
• pp.571-582
• /
• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.11-25
• /
• 2024

The proliferation of IoT devices has presented an unprecedented challenge in managing device identities securely and efficiently. In this paper, we introduce an innovative Hybrid Blockchain-Based Approach for IoT Identity Management that prioritizes both security and efficiency. Our hybrid solution, strategically combines the advantages of direct and indirect connections, yielding exceptional performance. This approach delivers reduced latency, optimized network utilization, and energy efficiency by leveraging local cluster interactions for routine tasks while resorting to indirect blockchain connections for critical processes. This paper presents a comprehensive solution to the complex challenges associated with IoT identity management. Our Hybrid Blockchain-Based Approach sets a new benchmark for secure and efficient identity management within IoT ecosystems, arising from the synergy between direct and indirect connections. This serves as a foundational framework for future endeavors, including optimization strategies, scalability enhancements, and the integration of advanced encryption methodologies. In conclusion, this paper underscores the importance of tailored strategies in shaping the future of IoT identity management through innovative blockchain integration.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.680-695
• /
• 1998

The objective of this study is to optimize the responses of the creep feed ceramic grinding process simultaneously by an off-1ine multicriteria optimization methodology. The responses considered as objectives are material removal rate, flexural strength, normal grinding force, workpiece surface roughness and grinder power. Alumina material was ground by the creep feed grinding mode using superabrasive grinding wheels. The process variables optimized for the above objectives include grinding wheel specification, such as bond type, mesh size, and grit concentration, and grinding process parameters, such as depth of cut and feed rate. A weighting method transforms the multi-objective problem into a single-objective programming format and then, by parametric variation of weights, the set of non-dominated optimum solutions are obtained. Finally, the multi-objective optimization methodology was tested by a sensitivity analysis to check the stability of the model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.652-655
• /
• 2012

With the development of IT and digital camera technology, diverse applications of image processing services are becoming available. In this paper, in order to ultimately automate parking management system, we designed and implemented a system for recognizing vehicle license plates that show vehicles' unique numbers by using EmguCV which shows optimized performance on Intel-based environment. We also implemented UI for administrators to easily manage the entire system by utilizing.