• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.

• 제어로봇시스템학회논문지
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• 제18권1호
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• pp.47-53
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• 2012

In cellular geo-location systems, positioning performance is influenced by hearability of receivers. Hearability can be enhanced by using long integration at the receiver. When unknown residual frequency remains in baseband signals, however, the coherent integration loss increases as the residual frequency becomes larger. Consequently, length of coherent integration is determined by the residual frequency. By precise estimation and compensation of the residual frequency, integration length can be enlarged. This paper presents a residual frequency estimator for WiBro geo-location and analyzes its performance in multipath environment. By computer simulation, an optimal receiver structure to enhance the hearability of WiBro geo-location is proposed.

• Environmental Engineering Research
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• 제10권4호
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• pp.155-164
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• 2005

This study investigated the possibility of reducing the residual aluminum (Al) in the treated water using polymers. Two raw waters (lake and river water) and three kinds of polymers (coagulant, flocculant, and filtration aids) were used for this purpose. This study found that coagulation at the high dose did not necessarily lead to the high concentration of the residual Al in the treated water. The coagulation efficacy was found more important in determining the residual Al than the coagulant dose. The use of a polymer enhanced the removal of turbidity as well as the residual Al. The coagulant aid removed the dissolved Al as well as the particulate Al by helping the coagulation and the solid-liquid separation. The flocculant aid and the filtration aid preferentially removed the particulate Al while helping the solid-liquid separation. The filtration aid reduced the residual Al substantially more effectively than the flocculant aid. The polyamine-based coagulant aid (FL) showed the better performance in reducing the residual Al and turbidity than DADMAC (WT). The cationic flocculant aid with weak charge density and the medium molecular weight (SC-020) showed the best performance in reducing the residual Al.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.684-690
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• 2015

This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.

• 제어로봇시스템학회논문지
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• 제16권7호
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• pp.720-725
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• 2010

In AGPS method, user position can be obtained even in the shadow region by improving signal sensitivity. A hybrid long integration scheme employing both coherent and non-coherent integration method is commonly used in AGPS receivers. Because coherent loss increases as residual frequency become large, residual frequency should be minimized to maximize coherent integration gain. This paper presents performance analysis of residual frequency estimator using FFT in fine-time assistance AGPS method. Considering the hardware complexity and the estimation accuracy, optimal length of FFT is proposed for GPS L1 C/A signal. Signal sensitivity for estimating the residual frequency is also analysed. By field experimental results, it is found that the residual frequency can be successfully estimated using 1 second snap-shot data when GPS signal strength is larger than -150 dBm and its RMS error is 3Hz.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.113-119
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• 2018

본 논문은 NM-MMA (Novel Mixed-Multi Modulus Algorithm) 알고리즘에서 고정 modulus 대신 adaptive modulus를 이용한 적응 등화 성능을 개선시킨 AM-NM-MMA (Adaptive Modulus-NM-MMA)에 관한 것이다. NM-MMA는 MMA의 정상 상태에서 적은 잔여량을 얻는 대신 수렴 속도가 느리며, SE-MMA는 수렴 속도가 빠르지만 잔여량이 증대되는 성능을 절충시키기 위해 등장하였다. 그러나 고정 modulus를 이용하므로 완전 등화 상태에서도 잔여량이 0이 되지 않아 등화 성능이 열화되므로 이를 개선하기 위하여 논문에서는 adaptive modulus를 적용하였으며, 이의 개선된 성능을 시뮬레이션을 통해 확인하였다. 이를 위하여 등화 성능 지수로 등화기 출력 성상도, 잔류 isi, MD, MSE 및 SER 성능을 적용하였다. 컴퓨터 시뮬레이션의 결과 AM-NM-MMA는 NM-MMA보다 등화 출력 신호의 성상도, 잔류 isi, MD, MSE에서 수렴 속도와 잔여량에서는 우월하였으나, SER 성능에서는 열화됨을 확인하였다.

• Earthquakes and Structures
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• 제10권2호
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• pp.409-428
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• 2016

To realise the full benefits of a self-centering seismic resilient system, the designer must ensure that the entire structure does indeed re-center following an earthquake. The idealised flag-shaped hysteresis response that is often used to define the cyclic behaviour of self-centering concrete systems seldom exists and the residual drift of a building subjected to an earthquake is dependent on the realistic cyclic hysteresis response as well as the dynamic loading history. Current methods that are used to ensure that re-centering is achieved during the design of self-centering concrete systems are presented, and a series of cyclic analyses are used to demonstrate the flaws in these current procedures, even when idealised hysteresis models were used. Furthermore, results are presented for 350 time-history analyses that were performed to investigate the expected residual drift of an example self-centering concrete wall system during an earthquake. Based upon the results of these time-history analyses it was concluded that due to dynamic shake-down the residual drifts at the conclusion of the ground motion were significantly less than the maximum possible residual drifts that were observed from the cyclic hysteresis response, and were below acceptable residual drift performance limits established for seismic resilient structures. To estimate the effect of the dynamic shakedown, a residual drift ratio was defined that can be implemented during the design process to ensure that residual drift performance targets are achieved for self-centering concrete wall systems.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1479-1494
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• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2002년도 추계공동학술대회논문집
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• pp.13-19
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• 2002

2-체널 링-코어 프럭스-게이트 콤파스(two-channel ring-core Flux-Gate Compass: FG-Compass)의 성능평가 시스템 설계와 구현방법 및, 다항회귀 모형 기반의 평가 절차와 방법을 기술했다. 성능평가 시스템은 스텝모터 구동 유닛과, 방위정보 전송 유닛, 다항회귀식을 이용한 평가 프로그램 등으로 구성하였다. 성능평가 실험결과, FG-Compass를 전체 잔차 $\pm$4$^{\circ}$, 고유 잔차 $\pm$2$^{\circ}$로 분석하였다. 이 결과는 일반적인 FG-Compass의 고유 잔차 $\pm$4$^{\circ}$와 비교하여 정밀한 것으로, 성능이 향상된 새로운 FG-Compass 설계가 가능함을 나타낸다. 또한, 자동으로 잔차를 추정하고 도정할 수 있는 스마트 FG-Compass 콤파스의 설계론에 관해서도 논의하였다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.203-211
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• 2021

Image tampering detection and localization have become an active area of research in the field of digital image forensics in recent times. This is due to the widespread of malicious image tampering. This study presents a new method for image tampering detection and localization that combines the advantages of dilated convolution, residual network, and UNET Architecture. Using the UNET architecture as a backbone, we built the proposed network from two kinds of residual units, one for the encoder path and the other for the decoder path. The residual units help to speed up the training process and facilitate information propagation between the lower layers and the higher layers which are often difficult to train. To capture global image tampering artifacts and reduce the computational burden of the proposed method, we enlarge the receptive field size of the convolutional kernels by adopting dilated convolutions in the residual units used in building the proposed network. In contrast to existing deep learning methods, having a large number of layers, many network parameters, and often difficult to train, the proposed method can achieve excellent performance with a fewer number of parameters and less computational cost. To test the performance of the proposed method, we evaluate its performance in the context of four benchmark image forensics datasets. Experimental results show that the proposed method outperforms existing methods and could be potentially used to enhance image tampering detection and localization.