• 센서학회지
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• 제31권1호
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• pp.64-68
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• 2022

Herein, we propose a LoRaWAN-based small draft system that can measure the ocean current flow (speed, direction, and distance) in real time at the request of the Coast Guard to develop a device that can promptly find survivors at sea. This system has been implemented and verified in the early stages of rescue after maritime vessel accidents, which are frequent. GPS signals often transmit considerable errors, so correction algorithms using the improved triangulation method algorithm are required to accurately indicate the direction of currents in real time. This paper is structured in the following manner. The introduction section elucidates rescue activities in the case of a maritime accident. Chapter 2 explains the characteristics and main parameters of the GPS surveying technique and LoRaWAN communication, which are related studies. It explains and expands on the critical distance error correction algorithm for GPS signals and its improvement. Chapter 3 discusses the design and analysis of small draft buoys. Chapter 4 presents the testing and validation of the implemented system in both onshore and offshore environments. Finally, Section 5 concludes the study with the expected impact and effects in the future.

• Asian Journal of Business Environment
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• 제12권1호
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• pp.1-9
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• 2022

Purpose: This study measures the effect of Information Technology (IT) on both cost and profit efficiency of State-owned Commercial Banks (SOCBs) in Bangladesh. Research design, data and methodology: Yearly Non-IT and IT data are collected from the annual report of SOCBs of Bangladesh from 2008 to 2017. Variable Return to Scale (VRS) cost Data Envelopment Analysis (DEA) and Profit DEA are employed to measure the efficiency of SOCBs and Ordinary Least Square (OLS) is used to investigate the impacts of ICT components on operating cost and profit efficiency for SOCBs. Results: The average cost efficiency (74.4%) was noticed higher than the average profit efficiency (20.6%) for SOCBs. SOCBs were more affordable and less profitable for both cost and profit efficiency. Rupali bank was the most cost efficient while Sonali bank was the most profit efficient. IT Investment and IT personnel expenses were positively significant for cost efficiency. IT income, IT personnel, IT personnel expenses, ATM expenses, and Credit card expenses were negatively significant for profit efficiency. Conclusion: The further studies can combine DEA with machine learning algorithms to study the impact of IT on banks' performances. The results could aid government to remove the hindrance of progress in Bangladesh.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.407-410
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• 1998

Configuration is a set of building block processes, a series of selection and combining parts or components which composes a whole thing. A whole thing could be such a configurable object as manufacturing product, network system, financial portfolio, system development plan, project team, etc. Configuration problem could happen during any phase of product life cycle: design, production, sales, installation, and maintenance. Configuration has long been one of cost and time consuming work, because only high salaried technical experts on product and components can do configuration. Rework for error adjustments of configurations at later process causes far much cost and time, so accurate configuration is required. Under the on-line electronic commerce environment, configuration problem solving becomes more important, because component-based sales should be done automatically on the merchant web site. Automated product search, order placement, order fulfillment and payment make that manual configuration is no longer feasible. Automated configuration means that all the constraints among components should be checked and confirmed by configuration engine automatically. In addition, technical constraints and customer preferences like price range and a specific function required should be considered. This paper gives an brief overview of configuration problems: characteristics, representation paradigms, and solving algorithms and introduce CRSP(Constraint and Rule Satisfaction Problem) method. CRSP method adopts both constraint and rule for configuration domain knowledge representation. A survey and analysis on web sites adopting configuration functions are provided. Future directions of configuration for EC is discussed in the three aspects: methodology itself, companies adopting configuration function, and electronic commerce industry.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products me classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem far disposal products. In this paper, a heuristic approach fuzzy ART neural network is suggested. The modified fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its ai is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• KIEAE Journal
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• 제16권6호
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• pp.5-12
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• 2016

Purpose: Quasi-steady state simulations have played a pivoting role to expand the user group of simulation to design engineers and architects in Korea. Initially they are introduced in the market as a building energy performance rating tool. In domestic practice, however, quasi-steady state simulations seem to be regarded as a de facto simulation only available for energy retrofit. Selection of ECMs and economic feasibility analysis are being decided through these tools, which implies that running these tools has become a norm step of the Investment-grade Audit. Method: This study aims at identifying issues and problems with the current practice via test cases, analyzing the reasons and opportunities, and then eventually suggesting proper uses of quasi-steady state and dynamic simulations. Result: The functionality of quasi-steady state simulations is more optimized to the rating. If they are to used for energy retrofits, their off-the-shelf functions also need to be expanded for customization and detailed reports. Yet their roles may be limited only to the go/no go decision; because their algorithms are still weak at precisely estimating energy and load savings that are required for making investment decisions compared to detailed simulations.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• 한국강구조학회 논문집
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• 제22권1호
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• pp.33-42
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• 2010

막구조의 설계에서 막재료의 효율적인 사용을 위해서는 측지선에 의한 재단도 해석을 수행해야 한다. 막구조의 측지선 결정방법은 크게 측지요소(geodesic element)를 이용한 비선형 형상해석에 의한 방법과 임의의 곡면 형상에 대한 측지선 탐색에 의한 방법으로 나눌 수 있는데, 현재까지 이 두 가지 해석법은 모두 3절점요소에 대한 적용알고리즘 만이 제시되었고, 4절점 요소에 대한 해석법은 제시되지 않았다. 이는 막구조의 설계에서 4절점 요소의 적용을 어렵게 하는 가장 큰 요인이라고 할 수 있다. 본 연구에서는 3절점, 4절점 평면요소에 동시에 적용 가능한 측지선 결정알고리즘을 제시한다. 이를 위해 저자의 이전 연구를 발전시켜 명시적 비선형 해석법인 동적이완법을 비선형 측지선 형상해석에 적용하였다. 또한 3절점요소 뿐만 아니라 4절점요소에 대해서도 측지요소의 도입에 의한 형상해석이 가능하도록 하였으며, 4절점요소와 측지선요소에 의한 비선형 형상해석 및 재단도 해석예제를 통하여 본 연구에서 제시한 알고리즘의 정확성 및 효율성을 검증하였다. 따라서 본 연구에서 제안한 측지선 형상해석알고리즘은 형상해석, 응력해석, 재단도 해석과 관련된 일련의 해석과정에 대한 4절점요소의 적용성을 높일 수 있을 것으로 사료된다.

• 전자통신동향분석
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• 제37권2호
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• pp.30-41
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• 2022

As the society is superaging, the number of patients with movement disabilities due to musculoskeletal or nervous system illness is rapidly increasing. To improve public health and reduce medical expenses, it is essential to develop rehabilitation systems that allow patients to resume their daily-life activities. However, the existing musculoskeletal illness diagnosis and rehabilitation method is limited in terms of precision and efficiency because it is based on an empirical diagnosis and prescription without regard for individual characteristics. To overcome these limits, it is critical to design a novel concept of routine rehabilitation therapy device that is capable of inducing musculoskeletal balance by the precise analysis of musculoskeletal usage patterns via the motion and the muscle activity tracking of linked muscles. This study introduces the trend of on-skin sensor device technology for routine musculoskeletal monitoring and therapy. For on-skin rehabilitation systems, skin-adhesive and stretchable motion/posture, electromyography, pressure sensors, small-size and low-power wireless sensor interfaces, and user-friendly rehabilitation contents based on new algorithms are combined.