• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.198-204
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• 2007

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.877-893
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• 2022

With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• Journal of architectural history
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• v.19 no.1
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• pp.27-50
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• 2010

This paper was to analyze the fusion between the organic and inorganic characteristics performed in architecture and urbanism, especially on the characteristics found in the works of Archigram group who was very active during 1960s and 70s. Generally, it was thought that Archigram drew its ideas mainly from a mechanist metaphor and that the diagrams of its members were based on the notion of the material obsolescence, which could be placed in a British tectonic tradition. But, Archigram's works has been continually influenced by the biological-organic analogy from the birth of the group to its dissolution. Simply, the importance that the biological-organic analogy takes in the works of Archigram has changed periodically according to the change of its members. We can divide generally Archigram group in two parts : on one hand, nascent members such as Peter Cook, Dennis Greene, Michael Webb ; on the another hand, three members who participated from LCC such as Warren Chalk, Ron Herron, Dennis Crompton. As the new three LCC members participated, Archigram Group focalized on the technological part more than ever. But, when its members dispersed geographically and professionally, its biological-organic analogy came out again at the surface of their works. However, Archigram's organic and inorganic characteristics did not always adhere in opposing position with each other and took the form of coexistence in harmony at the same period. That is, the works of Archigram were persuing the creation of community that nature, technology and architecture could communicate and harmonize with each other through the intergration between organic and inorganic characteristics. The reason why Archigram became the one of the most excellent architectural avant-garde group in the 60s was mainly to receive asssitance with the fact that two small groups having contradictory tendencies got together and formed the Archigram group.

• Safety and Health at Work
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• v.13 no.2
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• pp.148-154
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• 2022

Background: Bus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. Methods: We evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. Results: Results showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. Conclusion: Elderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.65-69
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• 2018

In this paper, we propose an interworking architecture for building indoor air quality monitoring server (BEMS) using IIoT (Industrial Internet of Things). The proposed monitoring server adopts IIoT-based standard protocol so that interaction with BEMS installed in existing buildings can be performed easily. It can effectively communicate with indoor air quality measurement sensor installed in the building based on IIoT, Indoor air quality monitoring is possible. We implemented a proposed monitoring server, and confirmed the availability and monitoring of data from sensors in the building.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.4
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• pp.1111-1129
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• 2014

A 9300 TEU container carrier was equipped in 2006 with instrumentation aimed at wave induced accelerations, and motions. In 2010 the system was extended with strain sensors to include structural loads. Section loads for vertical bending could be readily obtained but the originally intended derivation of horizontal bending and torsion from the measured strains was found to be unreliable. This paper addresses an alternative approach that was adopted in the post processing of results. In particular the concept to use acceleration sensors to capture global hull deformations along the length of the hull, and the use of a data fusion procedure to obtain section loads from combined sensor data and finite element calculations. The approach is illustrated by comparison of actually measured accelerations and local strains with values obtained from the data fusion model. It is concluded that the approach is promising but in need of further validation and development. In particular the number and shapes of the modes used may not have been sufficient to represent the true deflection and thus strain distributions along the high loaded areas.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.268-273
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• 2005

We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.199-200
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• 2016

전 세계적으로 효율이 높은 LED 조명이 각광 받기 시작하면서 기존의 조명보다 에너지 효율이 높은 LED 조명을 보다 효율적으로 사용하기 위한 다양한 방법들에 대한 관심이 높아지고 있다. 이에 본 논문에서는 기존의 스위치 구조의 제품을 분석하여 한계점을 파악하고, 사용자가 스위치를 교체하는 단순한 방식으로도 스마트 조명을 경험 할 수 있도록 LED조명을 효율적으로 사용하기 위한 벽면형 스위치 구조를 디자인 하고자한다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.670-684
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• 2014

Ship Information Systems (SISs) have been one of the main research focuses in ship design and become a multidisciplinary area. With these growing research trends, it is important to consolidate the latest knowledge and information to keep up with the research needs. In this paper, the SIS and its different forms are introduced and discussed. The beginning of this paper discusses the history and evolution of SIS. The next part of this paper focuses on different fields and research areas such as networking technology, information fusion, information decision, message display, ship control in real-time SISs. A Semi-Physical Simulation Platform (SPSIM) designed for SIS research and its running effect through a new Fuzzy-PID fusion algorithm are introduced in this paper then. A brief literature survey and possible future direction concerning each topic is included.