Improving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies

Detecting subtle defects in window frames, including dents and scratches, is vital for upholding product integrity and sustaining a positive brand perception. Conventional machine vision systems often struggle to identify these defects in challenging environments like construction sites. In contrast, modern vision systems leveraging machine and deep learning (DL) are emerging as potent tools, particularly for cosmetic inspections. However, the promise of DL is yet to be fully realized. A few manufacturers have established a clear strategy for AI integration in quality inspection, hindered mainly by issues like scarce clean datasets and environmental changes that compromise model accuracy. Addressing these challenges, our study presents an innovative approach that amplifies defect detection in DL models, even with constrained data resources. The paper proposes a new defect detection pipeline called InspectNet (IPT-enhanced UNET) that includes the best combination of image enhancement and augmentation techniques for pre-processing the dataset and a Unet model tuned for window frame defect detection and segmentation. Experiments were carried out using a Spot Robot doing window frame inspections . 16 variations of the dataset were constructed using different image augmentation settings. Results of the experiments revealed that, on average, across all proposed evaluation measures, Unet outperformed all other algorithms when IPT-enhanced augmentations were applied. In particular, when using the best dataset, the average Intersection over Union (IoU) values achieved were IPT-enhanced Unet, reaching 0.91 of mIoU

Size Matters: Microservices Research and Applications

In this chapter we offer an overview of microservices providing the introductory information that a reader should know before continuing reading this book. We introduce the idea of microservices and we discuss some of the current research challenges and real-life software applications where the microservice paradigm play a key role. We have identified a set of areas where both researcher and developer can propose new ideas and technical solutions.Comment: arXiv admin note: text overlap with arXiv:1706.0735

The selective elimination of messenger RNA underlies the mitosis–meiosis switch in fission yeast

The cellular programs for meiosis and mitosis must be strictly distinguished but the mechanisms controlling the entry to meiosis remain largely elusive in higher organisms. In contrast, recent analyses in yeast have shed new light on the mechanisms underlying the mitosis–meiosis switch. In this review, the current understanding of these mechanisms in the fission yeast Schizosaccharomyces pombe is discussed. Meiosis-inducing signals in this microbe emanating from environmental conditions including the nutrient status converge on the activity of an RRM-type RNA-binding protein, Mei2. This protein plays pivotal roles in both the induction and progression of meiosis and has now been found to govern the meiotic program in a quite unexpected manner. Fission yeast contains an RNA degradation system that selectively eliminates meiosis-specific mRNAs during the mitotic cell cycle. Mmi1, a novel RNA-binding protein of the YTH-family, is essential for this process. Mei2 tethers Mmi1 and thereby stabilizes the transcripts necessary for the progression of meiosis

KAGRA: 2.5 Generation Interferometric Gravitational Wave Detector

The recent detections of gravitational waves (GWs) reported by LIGO/Virgocollaborations have made significant impact on physics and astronomy. A globalnetwork of GW detectors will play a key role to solve the unknown nature of thesources in coordinated observations with astronomical telescopes and detectors.Here we introduce KAGRA (former name LCGT; Large-scale Cryogenic Gravitationalwave Telescope), a new GW detector with two 3-km baseline arms arranged in theshape of an "L", located inside the Mt. Ikenoyama, Kamioka, Gifu, Japan.KAGRA's design is similar to those of the second generations such as AdvancedLIGO/Virgo, but it will be operating at the cryogenic temperature with sapphiremirrors. This low temperature feature is advantageous for improving thesensitivity around 100 Hz and is considered as an important feature for thethird generation GW detector concept (e.g. Einstein Telescope of Europe orCosmic Explorer of USA). Hence, KAGRA is often called as a 2.5 generation GWdetector based on laser interferometry. The installation and commissioning ofKAGRA is underway and its cryogenic systems have been successfully tested inMay, 2018. KAGRA's first observation run is scheduled in late 2019, aiming tojoin the third observation run (O3) of the advanced LIGO/Virgo network. In thiswork, we describe a brief history of KAGRA and highlights of main feature. Wealso discuss the prospects of GW observation with KAGRA in the era of O3. Whenoperating along with the existing GW detectors, KAGRA will be helpful to locatea GW source more accurately and to determine the source parameters with higherprecision, providing information for follow-up observations of a GW triggercandidate

One-pot bio-synthesis: N-acetyl-d-neuraminic acid production by a powerful engineered whole-cell catalyst

Whole cell biocatalysis is an important tool for pharmaceutical intermediates synthesis, although it is hindered by some shortcomings, such as high cost and toxicity of inducer, mass transfer resistance caused by cell membrane and side reactions. Whole-cell catalysis using N-acetyl-d-glucosamine 2-epimerase (EC 5.1.3.8) and N-acetyl-d-neuraminic acid (Neu5Ac) aldolase (EC 4.1.3.3) is a promising approach for the production of Neu5Ac, a potential precursor of many anti-viral drugs. A powerful catalyst was developed by packaging the enzymes in an engineered bacterium and using a safe temperature-induced vector. Since the mass transfer resistance and the side reactions were substantially reduced, a high Neu5Ac amount (191 mM) was achieved. An efficient method was also presented, which allows one-pot synthesis of Neu5Ac with a safe and economic manner. The results highlight the promise of large-scale Neu5Ac synthesis and point at a potential of our approach as a general strategy to improve whole-cell biocatalysis