In this investigation, we describe a chromatic confocal sensor based on a geometric phase lens for measuring the thicknesses of transparent plates. In order to design a compact sensor, a geometric phase lens, which has diffractive and polarizing characteristics, is used as a device to generate chromatic aberration, and a fiber optic module is adopted. The systematic error of the sensor is reduced with wavelength peak detection by Gaussian curve fitting and the common error compensation obtained by the repeatedly consecutive experimental results. An approach to calculate the plate thickness is derived and verified with sapphire and BK7 plates. Because of the simple and compact design of the proposed sensor with rapid measurement capability, it is expected to be widely used in thickness measurements of transparent plates as an alternative to traditional approaches.
Journal of the Korea Society of Computer and Information
/
v.25
no.12
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pp.1-15
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2020
In this paper, we propose a novel method for converting the existing 2D processes in the design and construction phase of civil engineering, to the future BIM-based processes. First, we compare and analyze the actual application processes of the outputs of the existing 2D method and the outputs of the 3D BIM method, for the whole process of BIM design of earthworks and road structures and integrated utilization of quantity, process(4D) and construction cost(5D), in view of life-cycle. The proposed method acquire the outputs of the design phase integrating IFC international common standard file information and CBS/OBS/WBS standard classification scheme information, and acquire the outputs of the construction stage by using an integrated utilization module for quantity, process(4D) and construction cost(5D). Ultimately, we intend to commercialize the step by step technologies for BIM design and construction in civil engineering by using the proposed method.
Kim, Hyo-Chul;Cho, Heung-Rae;Lee, Ju-Heun;Lee, Deok-Jae;An, Se-Hwan;Lee, Man-Hee;Joo, Ji-Han;Kim, Hong-Rak
The Journal of the Institute of Internet, Broadcasting and Communication
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v.22
no.2
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pp.35-42
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2022
In this paper, a method to increase the combining efficiency and isolation of the combiner, the core module of SSPA (solid state amplifier), was studied. Specifically, the isolation was secured by matching the common port and the isolation port in the waveguide combiner. The matching structure for matching is in the form of a circular disk and is engraved inside the waveguide combiner. The structure is very simple, so it is possible to secure stable performance. And this structure showed more than 60 times higher critical power performance compared to previous studies, confirming that it is suitable for high output. And by combining 1-stage T-junction and 2, 3 stage MagicT combiner, miniaturization was achieved and the combining efficiency was optimized by reducing the insertion loss. The fabricated waveguide coupler obtained an isolation of 16dB or more and a coupling efficiency of 86.2%.
While art and culture always actively intervene and send messages to social issues and issues, there are critics who say that the way they show them goes against environmental issues. Therefore, this study compared and analyzed the environment-friendly methods applied to four types of exhibitions held at existing domestic art museums in order to derive environmentally sustainable exhibition content planning and operation plans. By deriving the method commonly applied to the four exhibitions, the wooden temporary walls that are discarded through local remanufacturing, use of waste resources, and prefabricated module walls were minimized. In addition, when printing/publishing, there were methods such as grafting eco-friendly inks and materials or avoiding the production of unnecessary printed matter. Based on these common factors, a plan that can be applied to each stage of exhibition hall construction and construction, printing and publishing, and exhibition hall operation was derived. However, it is necessary to approach more diverse cases in the future, and it is necessary to supplement the points to enhance scientific explanatory power in quantitative terms.
Crack detection is essential for inspection of existing structures and crack segmentation based on deep learning is a significant solution. However, datasets are usually one of the key issues. When building a new dataset for deep learning, laborious and time-consuming annotation of a large number of crack images is an obstacle. The aim of this study is to develop an approach that can automatically select a small portion of the most informative crack images from a large pool in order to annotate them, not to label all crack images. An active learning method with difficulty learning mechanism for crack segmentation tasks is proposed. Experiments are carried out on a crack image dataset of a steel box girder, which contains 500 images of 320×320 size for training, 100 for validation, and 190 for testing. In active learning experiments, the 500 images for training are acted as unlabeled image. The acquisition function in our method is compared with traditional acquisition functions, i.e., Query-By-Committee (QBC), Entropy, and Core-set. Further, comparisons are made on four common segmentation networks: U-Net, DeepLabV3, Feature Pyramid Network (FPN), and PSPNet. The results show that when training occurs with 200 (40%) of the most informative crack images that are selected by our method, the four segmentation networks can achieve 92%-95% of the obtained performance when training takes place with 500 (100%) crack images. The acquisition function in our method shows more accurate measurements of informativeness for unlabeled crack images compared to the four traditional acquisition functions at most active learning stages. Our method can select the most informative images for annotation from many unlabeled crack images automatically and accurately. Additionally, the dataset built after selecting 40% of all crack images can support crack segmentation networks that perform more than 92% when all the images are used.
International conference on construction engineering and project management
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2013.01a
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pp.252-259
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2013
Building Information Modeling (BIM) is utilizing CAD technology in a way that ultimately ties all the components of a building together as objects imbedded with information, and has been changing the way we design and build over the last 20-30 years. In Polytechnic Institute of NYU, there are four BIM courses offered which provide students with different levels of knowledge regarding BIM Technique, BIM Standards, BIM Guideline and Roadmap for Private and Public Implementation, BIM Application in Real Projects, the Cooperation of BIM and IPD for Public Works in New York City. With advanced BIM technology, BIM's integration into the construction process and its incorporation into project delivery systems, especially Integrated Project Delivery (IPD) are the bridges between technology, industry and research. This paper presents an integrated BIM curriculum with three modules: 1) BIM functions and Bid Preparation; 2) Time-Cost Trade-off Analysis; and 3) Problems Solving in BIM/IPD Environment. In this project-based curriculum developed by the common efforts of academia, public agency and industry, the objectives are: (1) to provide the information and skills needed to successfully implement BIM into the construction phase; (2) to identify BIM's role in construction and the project delivery system; (3) to develop a module in conjunction with leading BIM into project delivery system, particularly coordination between BIM and IPD; (4) to connect technology and research into industry. The course assessment was conducted and the results indicate that it is a successful reform in construction management education.
Yurim Jang;Ji Hyun Moon;Byung Kwan Jeon;Ho Jin Park;Hong Jin Lee;Do Yup Lee
Journal of Microbiology and Biotechnology
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v.33
no.10
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pp.1351-1360
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2023
Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.
Journal of The Korean Society of Integrative Medicine
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v.12
no.3
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pp.101-120
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2024
Purpose : This study aimed to carry out a scoping review to investigate the research trends in non-pharmacological interventions for physical rehabilitation following breast cancer treatment. Methods : A scoping review was conducted according to the five steps outlined by Arksey and O'Malley and PRISMA-ScR. We searched three domestic databases (ScienceOn, Riss, KCI) and two international databases (PubMed, Cochrane Central) between January 2014 and April 2024. The keywords used were 'breast cancer surgery', 'breast cancer treatment', 'breast cancer lymphedema', 'intervention', 'management', 'therapy', 'disorder', and 'dysfunction'. Results : In terms of publication, the number of studies in the past five years has increased compared to the previous five years, with most studies focusing on patients aged 41 to 60 and who underwent surgical treatment for breast cancer. A total of 43 different types of non-pharmacological interventions were applied: 21 single interventions and 22 combination interventions. Among the intervention methods, complete decongestive treatment (CDT), resistance training, and manual lymphatic drainage were the most frequently utilized. The most common duration of intervention turned out to be 4~5 weeks and more than 8 weeks, with frequencies of 2~3 sessions per week and more than 4 sessions per week. The most frequently used dependent variables included range of motion (ROM) and disabilities of the arm, shoulder and hand (DASH) for the function and disorder of the upper limb category; arm circumference or volume and bio-impedance for the lymphedema category; visual analogue scale (VAS) and numerical rating scale (NRS) for the pain category; and the European organization for research and treatment of cancer quality of life questionnaire breast cancer module (EORTC QLQ) and functional assessment of cancer therapy-breast (FACT-B) for the quality of life category. Conclusion : The findings of this scoping review provide valuable mapping data for non-pharmacological interventions for physical rehabilitation following breast cancer treatment. We recommend further research, particularly systematic reviews and meta-analyses, to build upon these findings.
Beauveria bassiana (Cordycipitaceae, Hypocreales, Ascomycota) is an anamorphic fungus having a potential to be used as a biological control agent because it parasitizes a wide range of arthropod hosts including termites, aphids, beetles and many other insects. A number of bioactive secondary metabolites (SMs) have been isolated from B. bassiana and functionally verified. Among them, beauvericin and bassianolide are cyclic depsipeptides with antibiotic and insecticidal effects belonging to the enniatin family. Non-ribosomal peptide synthetases (NRPSs) play a crucial role in the synthesis of these secondary metabolites. NRPSs are modularly organized multienzyme complexes in which each module is responsible for the elongation of proteinogenic and non-protein amino acids, as well as carboxyl and hydroxyacids. A minimum of three domains are necessary for one NRPS elongation module: an adenylation (A) domain for substrate recognition and activation; a tholation (T) domain that tethers the growing peptide chain and the incoming aminoacyl unit; and a condensation (C) domain to catalyze peptide bond formation. Some of the optional domains include epimerization (E), heterocyclization (Cy) and oxidation (Ox) domains, which may modify the enzyme-bound precursors or intermediates. In the present study, we analyzed genomes of B. bassiana and its allied species in Hypocreales to verify the distribution of NRPS-encoding genes involving biosynthesis of beauvericin and bassianolide, and to unveil the evolutionary processes of the gene clusters. Initially, we retrieved completely or partially assembled genomic sequences of fungal species belonging to Hypocreales from public databases. SM biosynthesizing genes were predicted from the selected genomes using antiSMASH program. Adenylation (A) domains were extracted from the predicted NRPS, NRPS-like and NRPS-PKS hybrid genes, and used them to construct a phylogenetic tree. Based on the preliminary results of SM biosynthetic gene prediction in B. bassiana, we analyzed the conserved gene orders of beauvericin and bassianolide biosynthetic gene clusters among the hypocrealean fungi. Reciprocal best blast hit (RBH) approach was performed to identify the regions orthologous to the biosynthetic gene cluster in the selected fungal genomes. A clear recombination pattern was recognized in the inferred A-domain tree in which A-domains in the 1st and 2nd modules of beauvericin and bassianolide synthetases were grouped in CYCLO and EAS clades, respectively, suggesting that two modules of each synthetase have evolved independently. In addition, inferred topologies were congruent with the species phylogeny of Cordycipitaceae, indicating that the gene fusion event have occurred before the species divergence. Beauvericin and bassianolide synthetases turned out to possess identical domain organization as C-A-T-C-A-NM-T-T-C. We also predicted precursors of beauvericin and bassianolide synthetases based on the extracted signature residues in A-domain core motifs. The result showed that the A-domains in the 1st module of both synthetases select D-2-hydroxyisovalerate (D-Hiv), while A-domains in the 2nd modules specifically activate L-phenylalanine (Phe) in beauvericin synthetase and leucine (Leu) in bassianolide synthetase. antiSMASH ver. 2.0 predicted 15 genes in the beauvericin biosynthetic gene cluster of the B. bassiana genome dispersed across a total length of approximately 50kb. The beauvericin biosynthetic gene cluster contains beauvericin synthetase as well as kivr gene encoding NADPH-dependent ketoisovalerate reductase which is necessary to convert 2-ketoisovalarate to D-Hiv and a gene encoding a putative Gal4-like transcriptional regulator. Our syntenic comparison showed that species in Cordycipitaceae have almost conserved beauvericin biosynthetic gene cluster although the gene order and direction were sometimes variable. It is intriguing that there is no region orthologous to beauvericin synthetase gene in Cordyceps militaris genome. It is likely that beauvericin synthetase was present in common ancestor of Cordycipitaceae but selective gene loss has occurred in several species including C. militaris. Putative bassianolide biosynthetic gene cluster consisted of 16 genes including bassianolide synthetase, cytochrome P450 monooxygenase, and putative Gal4-like transcriptional regulator genes. Our synteny analysis found that only B. bassiana possessed a bassianolide synthetase gene among the studied fungi. This result is consistent with the groupings in A-domain tree in which bassianolide synthetase gene found in B. bassiana was not grouped with NRPS genes predicted in other species. We hypothesized that bassianolide biosynthesizing cluster genes in B. bassiana are possibly acquired by horizontal gene transfer (HGT) from distantly related fungi. The present study showed that B. bassiana is the only species capable of producing both beauvericin and bassianolide. This property led to B. bassiana infect multiple hosts and to be a potential biological control agent against agricultural pests.
Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.
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