426 research outputs found
sj-pdf-1-jit-10.1177_15280837211073361 – Supplemental Material for A fully textile-based skin pH sensor
No full textSupplemental Material, sj-pdf-1-jit-10.1177_15280837211073361 for A fully textile-based skin pH sensor by Choi Minyoung, Minji Lee, Ji-Hye Kim, Sooyoung Kim, Jonghoon Choi, Ju-Hee So and Hyung-Jun Koo in Journal of Industrial Textiles</p
Application of Machine-learning (ML) technology for the use of big data in the design and construction stages of the Engineering, Procurement, Construction (EPC) project
No full textThe risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.1
Automatic Conversion of Table Contents from PDF Technical Specification Documents into Database Using AI Optical Character Recognition (OCR)
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A Comparative Study of Reinforcement Learning and Analytical Methods for Optimal Control
No full textNumerous reinforcement learning (RL) algorithms have been introduced to resolve challenging tasks like game playing, natural language processing, and control. Particularly, RL can be used to find a good policy for control systems for which the optimal control sequence is difficult to find by analytical methods. This paper compares RL and analytical methods for optimal control in an inverted pendulum environment. Dynamic programming (DP) and model predictive control (MPC) are considered for the analytical methods. The control results of RL, DP, and MPC are qualitatively and quantitatively compared in terms of total reward, state response, and control sequence to investigate the relationships between them. Because they have similar problem formulations, the relationships can be explained by RL parameters: discounting factor and exploration rate. This comparative study is expected to provide insights to those studying RL algorithms and optimal control theories. © 2023 IEEE
RNN‐EdgeQL: An auto‐scaling and placement approach for SFC
No full textThis paper proposes a prediction-based scaling and placement of service function chains (SFCs) to improve service level agreement (SLA) and reduce operation cost. We used a variant of recurrent neural network (RNN) called gated recurrent unit (GRU) for resource demand prediction. Then, considering these predictions, we built an intuitive scale in/out algorithm. We also developed an algorithm that applies Q-Learning on Edge computing environment (EdgeQL) to place these scaled-out VNFs in appropriate locations. The integrated algorithm that combines prediction, scaling, and placement are called RNN-EdgeQL. RNN-EdgeQL (v2) is further improved to achieve application agnostic group level elasticity in the chain, independent of applications installed on the VNFs. We tested our algorithm on two realistic temporal dynamic load models including Internet traffic (Abilene) and an application specific traffic (Wiki) on an OpenStack testbed. The contribution of this article is threefold. First, prediction model prepares the target SFC for the upcoming load. Second, an application agnostic characteristics of the algorithm achieves the group-level elasticity in SFC. Finally, the EdgeQL placement model minimizes the end-to-end path of an SFC in multi-access edge computing (MEC) environment. As a result, RNN-EdgeQL (v2) gives the lowest overall latency, lowest SLA violations, and lowest VNFs requirement, compared to RNN-EdgeQL (v1) and Threshold-Openstack default placement.11Nsciescopu
High Doses of Caffeine during the Peripubertal Period in the Rat Impair the Growth and Function of the Testis
No full textPrenatal caffeine exposure adversely affects the development of the reproductive organs of male rat offspring. Thus, it is conceivable that peripubertal caffeine exposure would also influence physiologic gonadal changes and function during this critical period for sexual maturation. This study investigated the impact of high doses of caffeine on the testes of prepubertal male rats. A total of 45 immature male rats were divided randomly into three groups: a control group and 2 groups fed 120 and 180 mg/kg/day of caffeine, respectively, via the stomach for 4 weeks. Caffeine caused a significant decrease in body weight gain, accompanied by proportional decreases in lean body mass and body fat. The caffeine-fed animals had smaller and lighter testes than those of the control that were accompanied by negative influences on the histologic parameters of the testes. In addition, stimulated-testosterone ex vivo production was reduced in Leydig cells retrieved from the caffeine-fed animals. Our results demonstrate that peripubertal caffeine consumption can interfere with the maturation and function of the testis, possibly by interrupting endogenous testosterone secretion and reducing the sensitivity of Leydig cells to gonadotrophic stimulation. In addition, we confirmed that pubertal administration of caffeine reduced testis growth and altered testis histomorphology
Effectiveness of Immersive Virtual Reality-based Communication for Construction Projects
No full textThough computer-mediated communication technologies such as immersive virtual reality (IVR) have recently shown considerable promise, their effectiveness as methods of communication among the participants in construction projects has yet to be systematically investigated. This study helps fill this gap via a detailed comparison of traditional face-to-face (FtF) discussion of Building Information Modeling (BIM) information displayed on a monitor screen against IVR-based communication with BIM information embedded in the immersive environment. The results of experiments in which groups of participants discussed and chose optimal design options indicated that there is no large statistical difference in IVR-based and FtF communication in terms of discussion quality (level of effectiveness and satisfaction experienced), communication richness (detailed responses and vivid messages), and openness (enjoyableness and open-mindedness) during the communication. However, for the accuracy of communication (information communicated correctly and understood properly), FtF communication was better than IVR-based communication, which is assumed due to weak human-human to interaction in IVR. In addition, the communication appropriateness (behavioral acts such as politeness or social norms), IVR-based communication was significantly less than FtF communication, indicating that communicating with others only seeing virtual avatar could make it difficult to discern participant' reactions or identify appropriate moments to speak. These results could confirm certain advantages of adopting IVR-based communication while further improvement for real-like interaction between people needs to be made for more effective use of IVR communication.
첨단 운전자 보조 시스템을 위한 차량 내부 네트워크 분석
No full text내부 네트워크, 첨단 운전자 보조 시스템, 차량용 이더넷, Controller area network (CAN), 영역 기반 아키텍처Ⅰ. Introduction 1
Ⅱ. Background 4
2.1 Advanced Driver Assistance System (ADAS) 4
2.2 In-Vehicle Network (IVN) 7
2.2.1 Controller Area Network (CAN) 8
2.2.2 Automotive Ethernet 10
2.3 Network Architecture 13
Ⅲ. Factor of End-to-End Latency for ADAS 15
3.1 IVN Latency 16
3.2 Computing Latency 18
3.2 Actuation Latency 18
Ⅳ. Analysis of Latency for ADAS 19
4.1 Simulation Configuration 19
4.1.1 OMNeT++ 19
4.1.2 Simulation Design 21
4.2 Simulation Analysis 23
4.2.1 Simulation Result 23
4.2.2 Analysis of end-to-end latency 30
Ⅴ. Conclusion 35MasterdCollectio
Efficient Reference-based Video Super-Resolution (ERVSR): Single Reference Image Is All You Need
No full textReference-based video super-resolution (RefVSR) is a promising domain of super-resolution that recovers high-frequency textures of a video using reference video. The multiple cameras with different focal lengths in mobile devices aid recent works in RefVSR, which aim to super-resolve a low-resolution ultra-wide video by utilizing wide-angle videos. Previous works in RefVSR used all reference frames of a Ref video at each time step for the super-resolution of low-resolution videos. However, computation on higher-resolution images increases the runtime and memory consumption, hence hinders the practical application of RefVSR. To solve this problem, we propose an Efficient Reference-based Video Super-Resolution (ERVSR) that exploits a single reference frame to super-resolve whole low-resolution video frames. We introduce an attention-based feature align module and an aggregation upsampling module that attends LR features using the correlation between the reference and LR frames. The proposed ERVSR achieves 12× faster speed, 1/4 memory consumption than previous state-of-the-art RefVSR networks, and competitive performance on the RealMCVSR dataset while using a single reference image
Big Fun
No full textThis thesis comprises roughly the first half of the in-progress novel Big Fun. It is told from two perspectives: Minji Choi, a university drop-out hikikomori, and Simon Koo, a recently fired philosophy professor. When Simon loses his wife’s cherished beagle, he steals Minji’s beagle, thinking it is the same dog. Before Simon can return the dog to Minji, it is kidnapped by his former students who hold the dog for ransom. Not wanting to be found out about kidnapping the dog in the first place, Simon secretly passes the ransom notes along to Minji. As Minji struggles to overcome her depression and find her dog, and as Simon struggles to save his marriage and recover professionally, one unlikely event after another brings their paths together into a big mess.This thesis has been embargoed for 10 years. It will not be available until April 2032 at the earliest
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