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| 1 | Differential gene expression and lipid metabolism in fatty liver induced bv acute ethanol treatment in mice显示文摘 | Hu-Quan Yin Mingoo Kim Ju-Han Kim el al | 2007 | Toxicology and Appplied Pharmacology2007，223，： | 1 |
| 2 | Variation-tolerant, ultra- Low-voltage microprocessor with a low-overhead, within- a-cycle in-situ timing-error detection and correction technique显示文摘 | Seongjong Kim Mingoo Seok | 2015 | IEEE Journal of Solid-State Circuits2015，50，6： | 1 |
| 3 | ArrayXPath: mapping and visualizing microarray geneexpression data with integrated biological pathway resources using Scalable Vector Graphics显示文摘 | Hee-Joon Chung Mingoo Kim Chan Hee Park | 2004 | Nucleic Acids Res2004，32，： | 1 |
| 4 | Real-Time Anomaly Detection in Packaged Food X-Ray Images Using Supervised Learning显示文摘Physical contamination of food occurs when it comes into contact with foreign objects.Foreign objects can be introduced to food at any time during food delivery and packaging and can cause serious concerns such as broken teeth or choking.Therefore,a preventive method that can detect and remove foreign objects in advance is required.Several studies have attempted to detect defective products using deep learning networks.Because it is difficult to obtain foreign object-containing food data from industry,most studies on industrial anomaly detection have used unsupervised learning methods.This paper proposes a new method for real-time anomaly detection in packaged food products using a supervised learning network.In this study,a realistic X-ray image training dataset was constructed by augmenting foreign objects with normal product images in a cut-paste manner.Based on the augmented training dataset,we trained YOLOv4,a real-time object detection network,and detected foreign objects in the test data.We evaluated this method on images of pasta,snacks,pistachios,and red beans under the same conditions.The results show that the normal and defective products were classified with an accuracy of at least 94%for all packaged foods.For detecting foreign objects that are typically difficult to detect using the unsupervised learning and traditional methods,the proposed method achieved high-performance realtime anomaly detection.In addition,to eliminate the loss in high-resolution X-ray images,the false positive rate and accuracy could be lowered to 5%with patch-based training and a new post-processing algorithm. | Kangjik Kim Hyunbin Kim Junchul Chun Mingoo Kang Min Hong Byungseok Min | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 5 | Fingerprint-Based Millimeter-Wave Beam Selection for Interference Mitigation in Beamspace Multi-User MIMO Communications显示文摘Millimeter-wave communications are suitable for application to massive multiple-input multiple-output systems in order to satisfy the ever-growing data traffic demands of the next-generation wireless communication.However,their practical deployment is hindered by the high cost of complex hardware,such as radio frequency(RF)chains.To this end,operation in the beamspace domain,through beam selection,is a viable solution.Generally,the conventional beam selection schemes focus on the feedback and exhaustive search techniques.In addition,since the same beam in the beamspace may be assigned to a different user,conventional beam selection schemes suffer serious multi-user interference.In addition,some RF chains may be wasted,since they do not contribute to the sum-rate performance.Thus,a fingerprint-based beam selection scheme is proposed to solve these problems.The proposed scheme conducts offline group-based fingerprint database construction and online beam selection to mitigate multi-user interference.In the offline phase,the contributing users with the same best beam are grouped.After grouping,a fingerprint database is created for each group.In the online phase,beam selection is performed for purposes of interference mitigation using the information contained in the group-based fingerprint database.The simulation results confirm that the proposed beam selection scheme can achieve a signal-to-interference-plus-noise ratio and sum-rate performance which is close to those of a fully digital system,and having much higher energy efficiency. | Sangmi MoonHyeonsung Kim Seng-Phil Hong Mingoo Kang Intae Hwang | 2021 | Computers, Materials & Continua2021，，1： | 0 |
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