• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.31-44
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• 2024

People have been using more energy in the last years. Several research studies were conducted to develop sustainable energy sources that can produce clean energy to fulfill our energy requirements. Using renewable energy sources helps to decrease the harm to the environment caused by conventional power plants. Choosing the right location and capacity for DG-RESs can greatly impact the performance of Radial Distribution Systems. It is beneficial to have a good and stable electrical power supply with low energy waste and high effectiveness because it improves the performance and reliability of the system. This research investigates the ideal location and size for solar and wind power systems, which are popular methods for producing clean electricity. A new artificial intelligent algorithm called Nutcracker Optimization Algorithm (NOA) is used to find the best solution in two common electrical systems named IEEE 33 and 69 bus systems to examine the improvement in the efficiency & reliability of power system network by reducing power losses, making voltage deviation smaller, and improving voltage stability. Finally, the NOA method is compared with another method called PSO and developed Hybrid Algorithm (NOA+PSO) to validate the proposed algorithm effectiveness and enhancement of both efficiency and reliability aspects.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.1-6
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• 2019

Recently, big data and artificial intelligence (AI) based on communication systems have become one of the hottest issues in the technology sector, and methods of analyzing big data using AI approaches are now considered essential. This paper presents diverse paradigms to subjects which deal with diverse research areas, such as image segmentation, fingerprint matching, human tracking techniques, malware distribution networks, methods of intrusion detection, digital image watermarking, wireless sensor networks, probabilistic neural networks, query processing of encrypted data, the semantic web, decision-making, software engineering, and so on.

• 한국융합학회논문지
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• 제5권2호
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• pp.7-11
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• 2014

본 연구에서는 텅스텐합금강의 상부구조와 폴리에틸렌소재로 구성된 하부구조의 무릎 인공관절이 하중을 받았을 때에 인공관절의 하중분포와 인공관절의 설치를 위한 지지구멍에 가해지는 응력분포에를 유한요소해석에 의하여 연구하였으며, 이러한 결과들을 이용하여 실물에 대한 실험을 위한 기초자료를 얻을 수 있었다. 상부구조의 모서리 끝부분부터 하중이 집중되어 크랙이 발생되며 이는 의학계에 보고된 인공관절파손에 의한 조직괴사사례와 그 거동이 일치하였다.

• 한국세라믹학회지
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• 제45권11호
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• pp.750-754
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• 2008

The artificial aggregates with dense surface layer (shell) was fabricated and the dependence of water emission rate upon the shell structures was studied. The EAF dust containing many flux components and waste white clay with ignition loss of above 48% were used as for liquid phase and gas forming agents during a sintering process respectively. In addition, the shell structure was modified with various processes and the modification effect on water emission rate was analyzed. The pores under $10{\mu}m$ were found in the sintered artificial light aggregates and disappeared by incorporating to a bigger pore during re-sintering. The water emission rate in an initial step depended on a void content of aggregates filled in a bottle rather than a shell structure. But, after 7 days where the water emission of the aggregate with a shell is above 40%, the shell of aggregates suppressed the water emission. The core of aggregates was exposed and most shell was lost when crushed to smaller size so, the ability for suppressing water emission of the crushed aggregates decreased. The activation energy for the water emission was $3.46{\pm}0.25{\times}10^{-1}$J/mol for the most specimens showing that the activation energy is irrelevant to the pore size distribution and shell structure.

• Steel and Composite Structures
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• 제19권2호
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• pp.349-368
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• 2015

This paper presents a new algorithm to find the optimal distribution of steel diagonal braces (SDB) using artificial bee colony optimization technique. The four different objective functions are employed based on the transfer function amplitude of; the top displacement, the top absolute acceleration, the base shear and the base moment. The stiffness parameter of SDB at each floor level is taken into account as design variables and the sum of the stiffness parameter of the SDB is accepted as an active constraint. An optimization algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed to minimize the objective functions. The proposed ABC algorithm is applied to determine the optimal SDB distribution for planar buildings in order to rehabilitate existing planar steel buildings or to design new steel buildings. Three planar building models are chosen as numerical examples to demonstrate the validity of the proposed method. The optimal SDB designs are compared with a uniform SDB design that uniformly distributes the total stiffness across the structure. The results of the analysis clearly show that each optimal SDB placement, which is determined based on different performance objectives, performs well for its own design aim.

• Journal of information and communication convergence engineering
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• 제15권4호
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• pp.205-211
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• 2017

Combining dispersion-managed optical links with midway optical phase conjugation (OPC) is a possible method of compensating for optical signal distortion due to group velocity dispersion and nonlinear Kerr effects. Although an improvement in the performance of these optical links has been reported, the fixed residual dispersion per span (RDPS) that is typically used restricts the flexibility of link configurations. Thus, in this paper, a flexible dispersion-managed link configuration, comprising artificial distributions of linearly/nonlinearly incremented RDPS, is proposed. Simulations show that a descending distribution of RDPS before the midway OPC, and an ascending distribution of RDPS after the midway OPC, gives the best artificial distribution pattern as the number of fiber spans is increased, regardless of the RDPS incrementation method.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2006년도 총회 및 춘계학술발표회
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• pp.391-393
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• 2006

In this study, the performance of artificial neural network (ANN) models for estimating spatial distribution of water quality was evaluated using electric conductivity (EC) values in landfill site. For the ANN model development, feedforward neural networks and backpropagation algorithm with gradient descent method were used. In Test 1, the interpolation ability of the ANN model was evaluated. Results of the ANN model were more precise than those of the Kriging model. In Test 2, spatial distributions of EC values were predicted using precipitation data. Results seemed to be reasonable, however, they showed a limitation of ANN models in extrapolations.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.143-148
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• 2022

In this paper, we employ deep neural network (DNN) to discern Android user interaction data distribution from artificial data distribution. We utilize real Android user interaction trace dataset collected from [1] to evaluate our DNN design. In particular, we use sequential model with 4 dense hidden layers and 1 dense output layer in TensorFlow and Keras. We also deploy sigmoid activation function for a dense output layer with 1 neuron and ReLU activation function for each dense hidden layer with 32 neurons. Our evaluation shows that our DNN design fulfills high test accuracy of at least 0.9955 and low test loss of at most 0.0116 in all cases of artificial data distributions.

• 수산해양기술연구
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• 제37권3호
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• pp.214-222
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• 2001

연안어장의 해저지형을 조사하기 위한 정밀음향측심시스템은 Public-DGPS 수신기. 싱글빔 음향측심기 및 측량용 소프트웨어로 구성하였으며, 그 유용성을 확인하기 위하여 정치망어장의 해저지형 특성 및 투입된 인공어초의 분포를 조사하였고 그 결과는 다음과 같다. 1. 본 연구에서 사용한 public-DGPS 수신기의 위치측정오차는 DGPS 모드일 때와 GPS 모드일 때 각각 5.47 m, 7.03 m이었다. 2. 실험정치망어장의 수심은 9~10 m이었고 해저는 대체로 평탄하였으며 이 어장으로부터 남쪽으로 120 m 떨어진 곳에 깊이 1~2 m, 폭 10 m내외의 골이 존재하였다. 3. 자란만 부근의 인공어초 수역에는 20개의 사각형 어초 (L3$\times$W3$\times$H3 m)가 수심 15~25 m에 낱개로 투입되어 있었고, 이 인공어초군의 가까이에 높이 5~8 m의 자연초가 있음을 확인할 수 있었다. 4. 본 연구에서 구현한 정밀음향측심시스템은 인공어초사업의 적지선정을 위한 사전조사에 활용할 수 있음을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.465-470
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• 2012

This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.