• Advances in concrete construction
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• 제11권5호
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• pp.397-407
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• 2021

This paper investigates the optimal sensor placements and capabilities of this procedure for dynamic characteristics identification of arch dams. For this purpose, a prototype arch dam is constructed in laboratory conditions. Berke arch dam located on the Ceyhan River in city of Osmaniye is one of the highest arch dam constructed in Turkey is selected for field verification. The ambient vibration tests are conducted using initial candidate sensor locations at the beginning of the study. Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are used to extract experimental dynamic characteristics. Then, measurements are repeated according to optimal sensor locations of the dams. These locations are specified using the Effective Independence Method. To determine the optimal sensor locations, the target mode shape matrices which are obtained from ambient vibration tests of the selected dam with a large number of accelerometers are used. The dynamic characteristics obtained from each ambient vibrations tests are compared with each other. It is concluded that the dynamic characteristics obtained from initial measurements and those obtained from a limited number of sensors are compatible with each other. This situation indicates that optimal sensor placements determined by the Effective Independence Method are useful for dynamic characteristics identification of arch dams.

• 한국항행학회논문지
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• 제24권6호
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• pp.549-556
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• 2020

이 논문에서는 마코프 프로세스로 모델링되는 전송 오류나 전송 지연이 있는 네트워크 제어 시스템을 위한 제어기 설계 방법들을 제안한다. 마코프 지연을 갖는 제어 시스템을 위한 안정화 조건을 지연 의존적인 리아프노프-크라소프스키 범함수가 증가된 제어 시스템의 리아프노프 함수와 동일한 형태를 갖는다는 점을 이용하여 찾는다. 유도된 안정화 조건으로부터 복잡도를 줄이기 위한 수 개의 제어 설계기 방법을 제안한다. 모의 실험을 통하여 제안된 방법 중 행렬 변수의 탐색 공간을 블록 대각 행렬로 제한하는 제한 부분 공간 방법이 성능과 복잡도 사이에서 가장 좋은 트레이드오프를 제공함을 확인되었다.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.241-247
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• 2022

Ad hoc network is self-organized network powered by battery. The reliability of virtual user identification and channel security are reduced when SNR is low due to limited user energy. In order to solve this problem, a joint virtual user identification and channel security en/decoding method is proposed in this paper. Transmitter-receiver-based virtual user identification code is generated by executing XOR operation between orthogonal address code of transmitter and pseudo random address code of receiver and encrypted by channel security code to acquire orthogonal random security sequence so as to improve channel security. In order to spread spectrum as well as improve transmission efficiency, data packet is divided into 6-bit symbols, each symbol is mapped with an orthogonal random security sequence. Subspace-based method is adopted by receiver to process received signal firstly, and then a judgment model is established to identify virtual users according to the previous processing results. Simulation results indicate that the proposed method obtains 1.6dB E_b/N₀ gains compared with reference methods when miss alarm rate reaches 10^-3.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.212-216
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• 2022

Space based constellation network is a kind of ad hoc network in which users are self-organized without center node. In space based constellation network, users are allowed to enter or leave the network at any given time. Thus, the number of active users is an unknown and time-varying parameter, and the performance of the network depends on how accurately this parameter is estimated. The so-called problem of active user identification, which consists of determining the number and identities of users transmitting in space based constellation network is discussed and a novel active user identification method is proposed in this paper. Active user identification code generated by transmitter address code and receiver address code is used to spread spectrum. Subspace-based method is used to process received signal and judgment model is established to identify active users according to the processing results. The proposed method is simulated under AWGN channel, Rician channel and Rayleigh channel respectively. Numerical results indicate that the proposed method obtains at least 1.16dB E_b/N₀ gains compared with reference methods when miss alarm rate reaches 10^-3.

• Journal of applied mathematics & informatics
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• 제41권2호
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• pp.273-286
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• 2023

In this paper we show that if T ∈ L(X) and S ∈ L(X) is a Riesz operator commuting with T and X_S(F) ∈ Lat(S), where F = {0} or F ⊆ ℂ ⧵ {0} is closed then T|X_S(F) and T|X_T(F) + S|X_S(F) share the local spectral properties such as SVEP, Dunford's property (C), Bishop's property (𝛽), decomopsition property (𝛿) and decomposability. As a corollary, if T ∈ L(X) and Q ∈ L(X) is a quasinilpotent operator commuting with T then T is Riesz if and only if T + Q is Riesz. We also study some spectral properties of Riesz operators acting on Banach spaces. We show that if T, S ∈ L(X) such that TS = ST, and Y ∈ Lat(S) is a hyperinvarinat subspace of X for which 𝜎(S|Y ) = {0} then 𝜎_*(T|Y + S|Y ) = 𝜎_*(T|Y ) for 𝜎_* ∈ {𝜎, 𝜎_loc, 𝜎_sur, 𝜎_ap}. Finally, we show that if T ∈ L(X) and S ∈ L(Y ) on the Banach spaces X and Y and T is similar to S then T is Riesz if and only if S is Riesz.

• Journal of applied mathematics & informatics
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• 제41권4호
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• 한국통신학회논문지
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• 제38A권5호
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• pp.401-408
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• 2013

LTE 및 LTE-A 시스템에서 8-PSK 성운을 알파벳으로 가지는 이중계층 차분 코드북을 제안한다. 인접하는 무선 채널의 시간 상관으로 선부호화 행렬은 천천히 변화하므로, 무선 채널 공간의 전체를 양자화 하지 않고, 시간 상관에 따른 채널 공간의 일부분의 차분 성분만을 양자화하여 피드백을 한다면, 기존과 동일한 크기의 코드북으로도 가상적으로는 코드북이 매우 커지는 효과를 얻을 수 있어 채널 용량이 증가한다. 특히 제안하는 코드북은 LTE release-8의 코드북 설계조건인 8-PSK 성운을 사용하는 동 이득 특성 및 이중 계층 코드북이 단일 계층 코드북을 포함하는 특성을 가지는 새로운 차분 코드북이다. 코드북 내 코드워드들의 인자들이 8-PSK 성운만을 사용하므로, 선부호화 및 복호 시에 계산량이 낮아지는 LTE 코드북의 장점을 그대로 유지할 수 있다. 또한 동 이득 성질은 상대적으로 저렴한 비선형 증폭기를 사용할 수 있는 장점이 있어 가격의 제한을 받는 단말기 설계에는 필수적인 요소이다. 컴퓨터 시뮬레이션을 통한 이중계층 선부호화 기법의 성능 분석에서, 동일한 피드백 비트 수를 갖는 같은 크기의 코드북에서 제안하는 차분 코드북은 정상상태에서 기존 LTE 코드북보다 최소 1.2dB 성능 향상을 보인다.