• 수산해양기술연구
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• 제58권3호
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• pp.272-280
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• 2022

The first step is to determine the principal dimensions of the design ship, such as length between perpendiculars, beam, draft and depth when accomplishing the design of a new vessel. To make this process easier, a database with a large amount of existing ship data and a regression analysis technique are needed. Recently, deep learning, a branch of artificial intelligence (AI) has been used in regression analysis. In this paper, deep learning neural networks are used for regression analysis to find the regression function between the input and output data. To find the neural network structure with the highest accuracy, the errors of neural network structures with varying the number of the layers and the nodes are compared. In this paper, Python TensorFlow Keras API and MATLAB Deep Learning Toolbox are used to build deep learning neural networks. Constructed DNN (deep neural networks) makes helpful in determining the principal dimension of the ship and saves much time in the ship design process.

• Smart Structures and Systems
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• 제31권6호
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• pp.545-559
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• 2023

Nanoparticle strips (NPS) are widely used as external reinforcers for two-way reinforced concrete slabs. However, the Structural Health Monitoring (SHM) of these slabs is a very important issue and was evaluated in this study. This study has been done analytically and numerically to optimize the placement of sensors. The properties of slabs and carbon nanotubes as composite sheets were considered isotopic and orthotropic, respectively. The nonlinear Finite Element Method (FEM) approach and suitable optimal placement of sensor approach were developed as a new MATLAB toolbox called DECOMAC by the authors of this paper. The Suitable multi-objective function was considered in optimized processes based on distributed ECOMAC method. Some common concrete slabs in construction with different aspect ratios were considered as case studies. The dimension and distance of nano strips in retrofitting process were selected according to building codes. The results of Optimal Sensor Placement (OSP) by DECOMAC algorithm on un-retrofitted and retrofitted slabs were compared. The statistical analysis according to the Mann-Whitney criteria shows that there is a significant difference between them (mean P-value = 0.61).

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.169-177
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• 2024

Interacting Spherical tank has maximum storage capacity is broadly utilized in industries because of its high storage capacity. This two tank level system has the nonlinear characteristics due to its varying surface area of cross section of tank. The challenging tasks in industries is to manage the flow rate of liquid. This proposed work plays a major role in controlling the liquid level in avoidance of time delay and error. Several researchers studied and investigated about reducing the nonlinearity problem and their approaches do not provide better result. Different types of controllers with various techniques are implemented by the proposed system. Intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) based Sliding Mode Controller (SMC) with Fractional order PID controller is a novel technique which is developed for a liquid level control in a interacting spherical tank system to avoid the external disturbances perform better result in terms of rise time, settling time and overshoot reduction. The performance of the proposed system is obtained by analyzing the simulation result obtained from the controller. The simulation results are obtained with the help of FOMCON toolbox with MATLAB 2018. Finally, the performance of the conventional controller (FOPID, PID-SMC) and proposed ANFIS based SMC-FOPID controllers are compared and analyzed the performance indices.

• BMB Reports
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• 제57권1호
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• pp.30-39
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• 2024

Directed evolution (DE) of desired locus by targeted random mutagenesis (TRM) tools is a powerful approach for generating genetic variations with novel or improved functions, particularly in complex genomes. TRM-based DE involves developing a mutant library of targeted DNA sequences and screening the variants for the desired properties. However, DE methods have for a long time been confined to bacteria and yeasts. Lately, CRISPR/Cas and DNA deaminase-based tools that circumvent enduring barriers such as longer life cycle, small library sizes, and low mutation rates have been developed to facilitate DE in native genetic environments of multicellular organisms. Notably, deaminase-based base editing-TRM (BE-TRM) tools have greatly expanded the scope and efficiency of DE schemes by enabling base substitutions and randomization of targeted DNA sequences. BE-TRM tools provide a robust platform for the continuous molecular evolution of desired proteins, metabolic pathway engineering, creation of a mutant library of desired locus to evolve novel functions, and other applications, such as predicting mutants conferring antibiotic resistance. This review provides timely updates on the recent advances in BE-TRM tools for DE, their applications in biology, and future directions for further improvements.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.119-129
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• 2024

We look at Web 3.0 business model canvas (BMC) of metaverse gaming platform, The Sandbox (TS). As results, the decentralized, blockchain-based platform, TS benefits its creators and players by providing true ownership, tradability of decentralized assets, and interoperability. First, in terms of the governance and ownership, The SAND functions a governance token allowing holders to participate in decision and SAND owners can vote themselves or delegate voting rights to other players of their choice. Second, in terms of decentralized assets and activities, TS offers three products as assets like Vox Edit as a 3D tool for voxel ASSETS, Marketplace as NFT market, and Game Maker as a visual scripting toolbox. The ASSETS made in Vox Edit, sold on the Marketplace, can be also utilized with Game Maker. Third, in terms of the network technology, in-game items are no longer be confined to a narrow ecosystem. The ASSETS on the InterPlanetary File System (IPFS) are not changed without the owner's permission. LAND and SAND are supported on Polygon, so that users interact with their tokens in a single place. Last, in terms of the token economics, users can acquire in-game assets, upload these assets to the marketplace, use for paying transaction fees, and use these as governance token for supporting the foundation.

• 디지털융복합연구
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• 제10권9호
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• pp.333-338
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• 2012

본 논문은 윤곽 형상에 밀착된 임의 형상 마스터를 이용한 스키니 스머지 블렌딩 방법에 관한 것이다. 스머지 툴(smudge tool)은 Adobe Photoshop CS6에 내장된 대중적인 그래픽 툴로서 물감을 화폭 상에 문질러서 흐려지게 할 시에 이용된다. 그 효과는 지두화법과 매우 유사하다. 스머지 툴은 Adobe Photoshop CS6의 툴박스에서 스머지 아이콘을 선택한 다음에 화폭 위를 클릭한 후, 마우스 버튼을 누른 상태에서 번짐 효과를 주고 싶은 방향으로 끌어당김으로써 그 기능을 이용할 수 있다. 그러나 기존의 스머지 툴은 마스터 반경 내의 모든 화소값을 블렌딩시켜 결과 영상을 생성함에 따라 원하지 않는 부위의 화소마저도 변형시키는 단점이 있다. 이러한 단점을 해결하고자 본 논문에서는 임의 형상 마스터를 이용한 스키니 스머지 블렌딩 방법을 제안하고자 한다. 제안된 블렌딩 방법은 컬러 영상 분할에 통해 윤곽 형상에 밀착된 임의 형상 마스터를 추출함에 따라 배경에 관계없이 변형하고 싶은 부분에만 번짐 효과를 적용시킬 수 있는 장점이 있다.

• 한국산업정보학회논문지
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• 제18권4호
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• pp.25-35
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• 2013

본 논문에서는 개인화된 분위기 분류 모델 대신에 대중의 분위기 분류 모델을 제안한다. 분위기 판별 성능을 개선하기 위해 두 가지 접근 방법을 선택하였는데, 그 첫 번째가 표준편차에 기초한 특징축소이다. 이는 음악의 특징을 추출하기 위해 사용하는 MIRtoolbox에서 추출되는 391개의 특징들을 모두 사용할 경우의 성능 저하 문제를 해결하기 위한 방법이다. 실험결과, 본 논문에서 제안한 특징축소 방법이 기존의 차원 축소 방법인 R-Square와 PCA보다 성능이 좋음을 확인할 수 있었다. 그리고 특징축소 방법만으로는 성능 개선에 한계가 있어 두 번째 개선방법으로 단위 신경망을 사용하여 추가의 성능 개선을 시도하였다. 실험결과 이 역시 유효한 성능 개선이 이루어짐을 확인할 수 있었다.

• 감성과학
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• 제15권4호
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• pp.477-488
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• 2012

2차원적 이미지에 생동감 있는 3-D 깊이감을 구현하기 위한 노력은 입체 지각에 대한 이론적 이해 및 그에 따른 기술적 발전과 더불어 오래 동안 지속되어 왔다. 본 논문에서는 입체경을 사용한 입체시 구현 원리에 기반을 둔 대중적인 입체경들을 간략히 개괄하고, 이들 중 액티브 셔터 방식의 입체경이 사용된 시각기억 실험 사례를 소개하였다. 실험에 참가한 피험자들은 자극들의 지각된 깊이를 기억하였으며, 이에 대한 기억 정확도가 측정되었다. 기억 및 검사를 위한 항목들의 깊이감은 1) 단안, 2) 양안 그리고 3) 단안과 양안 단서가 사용된 조건으로 각기 달리 처치되어 구분되었다. 참가자들의 기억 수행은 양안단서만이 처치된 조건에서 가장 낮았던 반면, 양안단서와 단안단서가 동시에 구현되었을 때 가장 높았다. 이러한 결과는 시각기억이 깊이 정보를 저장할 때, 양안단서를 통해 구현된 정보보다 단안 단서를 통해 구현된 정보를 더 효율적으로 저장하며, 양안단서와 단안단서가 동시에 사용되었을 때 가장 효과적인 기억 수행이 가능함을 시사한다.

• Journal of Electrical Engineering and Technology
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• 제3권3호
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• pp.391-400
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• 2008

Multi-pulse topology of converters using elementary six-pulse GTO - VSC (gate turn off based voltage source converter) operated under fundamental frequency switching (FFS) control is widely adopted in high power rating static synchronous compensators (STATCOM). Practically, a 48-pulse ($6{\times}8$ pulse) configuration is used with the phase angle control algorithm employing proportional and integral (PI) control methodology. These kinds of controllers, for example the ${\pm}80MVAR$ compensator at Inuyama switching station, KEPCO, Japan, employs two stages of magnetics viz. intermediate transformers (as many as VSCs) and a main coupling transformer to minimize harmonics distortion in the line and to achieve a desired operational efficiency. The magnetic circuit needs altogether nine transformers of which eight are phase shifting transformers (PST) used in the intermediate stage, each rating equal to or more than one eighth of the compensator rating, and the other one is the main coupling transformer having a power rating equal to that of the compensator. In this paper, a two-level 48-pulse ${\pm}100MVAR$ STATCOM is proposed where eight, six-pulse GTO-VSC are employed and magnetics is simplified to single-stage using four transformers of which three are PSTs and the other is a normal transformer. Thus, it reduces the magnetics to half of the value needed in the commercially available compensator. By adopting the simple PI-controllers, the model is simulated in a MATLAB environment by SimPowerSystems toolbox for voltage regulation in the transmission system. The simulation results show that the THD levels in line voltage and current are well below the limiting values specified in the IEEE Std 519-1992 for harmonic control in electrical power systems. The controller performance is observed reasonably well during capacitive and inductive modes of operation.

• Safety and Health at Work
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• 제11권3호
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• pp.322-334
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• 2020

Background: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O₂, N₂, and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.