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Journal articles on the topic 'All detection'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Zhang, Cuixian. "Direct Conversion X-Ray Detectors with High Sensitivity at Low Dose Rate Based on All-Inorganic Lead-Free Perovskite Wafers." Detection 09, no. 02 (2022): 13–27. http://dx.doi.org/10.4236/detection.2022.92002.

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Hadhrami, Ab. Ghani, Besar Rosli, Md Sani Zamani, et al. "Advances in lane marking detection algorithms for all-weather conditions." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (2021): 3365–73. https://doi.org/10.11591/ijece.v11i4.pp3365-3373.

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Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems

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Ab Ghani, Hadhrami, Rosli Besar, Zamani Md Sani, et al. "Advances in lane marking detection algorithms for all-weather conditions." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (2021): 3365. http://dx.doi.org/10.11591/ijece.v11i4.pp3365-3373.

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Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems.

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4

Kuo, Ho‐Chang, Chi‐Chun Lo, Yan‐Di Wang, Jheng‐Dao Wu, and Bor‐Shyh Lin. "Spectrogram for childhood asthma detection and analysis." Allergy 74, no. 9 (2019): 1783–86. http://dx.doi.org/10.1111/all.13768.

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5

Jackson, Anna, Hayden Allen, James H. Hull, et al. "Diagnosing exercise‐induced bronchoconstriction: Over‐or under‐detection?" Allergy 75, no. 2 (2019): 460–63. http://dx.doi.org/10.1111/all.14005.

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6

Muise, Christian. "Characterizing and Computing All Delete-Relaxed Dead-ends." Inteligencia Artificial 21, no. 62 (2018): 67. http://dx.doi.org/10.4114/intartif.vol21iss62pp67-74.

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Dead-end detection is a key challenge in automated planning, and it is rapidly growing in popularity. Effective dead-end detection techniques can have a large impact on the strength of a planner, and so the effective computation of dead-ends is central to many planning approaches. One of the better understood techniques for detecting dead-ends is to focus on the delete relaxation of a planning problem, where dead-end detection is a polynomial-time operation. In this work, we provide a logical characterization for not just a single dead-end, but for every delete-relaxed dead-end in a planning problem. With a logical representation in hand, one could compile the representation into a form amenable to effective reasoning. We lay the ground-work for this larger vision and provide a preliminary evaluation to this end

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Marnieros, S., L. Dumoulin, A. Benoit, et al. "All electron bolometer for radiation detection." Journal of Physics: Conference Series 150, no. 1 (2009): 012027. http://dx.doi.org/10.1088/1742-6596/150/1/012027.

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8

Wang, Dibo, Ran Zhuo, Yin Zhang, et al. "An All-Fiber FLRD System for SO2 Detection Based on Graphene-Coated Microfiber." Photonics 10, no. 8 (2023): 863. http://dx.doi.org/10.3390/photonics10080863.

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The accurate and effective detection of SF6 decomposition components inside a gas-insulated switchgear (GIS) is crucial for equipment fault diagnosis and condition assessment. The current method for detecting SF6 decomposition components involves gas extraction at the GIS inlet, which only provides limited information on the decomposition component content. Therefore, there is a need to explore more effective ways to obtain internal gas component information within GIS. In this study, we propose a graphene-coated microfiber gas detection method for SO2. We establish a physical simulation model of the microfiber and analyze the sensing mechanism of the microfiber diameter and cladding refractive index changes in its evanescent field. A graphene-coated microfiber gas sensor was prepared using a drop-coating method, and a fiber loop ring-down (FLRD) gas detection system was constructed for the experimental studies on SO2 gas detection. The results demonstrated that the graphene-coated microfiber exhibits an excellent gas-sensitive response to SO2 and achieves trace-level detection at room temperature. The concentration range of 0 to 200 ppm showed good linearity, with a maximum detection error of 4.76% and a sensitivity of 1.24 ns/ppm for SO2. This study introduces an all-fiber method for detecting SF6 decomposition components, offering a new approach for online monitoring of SF6 decomposition components in GIS equipment using built-in fiber-optic sensors.

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Gruner, Sol M. "Wide dynamic range detection and all that..." Acta Crystallographica Section A Foundations and Advances 75, a1 (2019): a42. http://dx.doi.org/10.1107/s0108767319099574.

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Sharma, Susmeeta T., and Lynnette K. Nieman. "Cushing’s Syndrome: All Variants, Detection, and Treatment." Endocrinology and Metabolism Clinics of North America 40, no. 2 (2011): 379–91. http://dx.doi.org/10.1016/j.ecl.2011.01.006.

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11

Shamir, Lior. "Transient Detection Using Panoramic All-Sky Cameras." Astrophysics and Space Science 305, no. 2 (2006): 165–68. http://dx.doi.org/10.1007/s10509-006-9055-6.

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12

Koppelman, Stef J., Michel Witteveen, Lonneke JanssenDuijghuijsen, Joseph L. Baumert, Renger F. Witkamp, and Klaske Norren. "Detection of peanut allergens in serum: circumventing the inhibitory effect of immunoglobulins." Allergy 75, no. 7 (2020): 1835–36. http://dx.doi.org/10.1111/all.14330.

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13

Azhar, Mohammad Afiq Dzuan Mohd, Nurul Shazana Abdul Hamid, Wan Mohd Aimran Wan Mohd Kamil, and Nor Sakinah Mohamad. "Daytime Cloud Detection Method Using the All-Sky Imager over PERMATApintar Observatory." Universe 7, no. 2 (2021): 41. http://dx.doi.org/10.3390/universe7020041.

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In this study, we explored a new method of cloud detection called the Blue-Green (B-G) Color Difference, which is adapted from the widely used Red-Blue (R-B) Color Difference. The objective of this study was to test the effectiveness of these two methods in detecting daytime clouds. Three all-sky images were selected from a database system at PERMATApintar Observatory. Each selected all-sky image represented different sky conditions, namely clear, partially cloudy and overcast. Both methods were applied to all three images and compared in terms of cloud coverage detection. Our analysis revealed that both color difference methods were able to detect a thick cloud efficiently. However, the B-G was able to detect thin clouds better compared to the R-B method, resulting in a higher and more accurate cloud coverage detection.

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14

Dhanokar, Gopal. "All in One Robot for Military Purpose." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 3709–17. http://dx.doi.org/10.22214/ijraset.2024.62394.

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Abstract: The "All in One Robot for Military Purpose" project is an innovative and comprehensive robotic system designed to fulfil a range of critical functions for military operations. This multifunctional robot integrates various advanced features including line following, obstacle avoidance, IR remote control, voice control, and mobile application-based control, ensuring versatile and adaptable operation in diverse environments. Additionally, the robot incorporates specialized systems such as landmine detection, RADAR technology, unwanted activities detection, fire detection, GPS navigation, and solar panel power supply.

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Zhang, Zhi, Yongzong Lu, Yiqiu Zhao, et al. "TS-YOLO: An All-Day and Lightweight Tea Canopy Shoots Detection Model." Agronomy 13, no. 5 (2023): 1411. http://dx.doi.org/10.3390/agronomy13051411.

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Accurate and rapid detection of tea shoots within the tea canopy is essential for achieving the automatic picking of famous tea. The current detection models suffer from two main issues: low inference speed and difficulty in deployment on movable platforms, which constrain the development of intelligent tea picking equipment. Furthermore, the detection of tea canopy shoots is currently limited to natural daylight conditions, with no reported studies on detecting tea shoots under artificial light during the nighttime. Developing an all-day tea picking platform would significantly improve the efficiency of tea picking. In view of these problems, the research objective was to propose an all-day lightweight detection model for tea canopy shoots (TS-YOLO) based on YOLOv4. Firstly, image datasets of tea canopy shoots sample were collected under low light (6:30–7:30 and 18:30–19:30), medium light (8:00–9:00 and 17:00–18:00), high light (11:00–15:00), and artificial light at night. Then, the feature extraction network of YOLOv4 and the standard convolution of the entire network were replaced with the lightweight neural network MobilenetV3 and the depth-wise separable convolution. Finally, to compensate for the lack of feature extraction ability in the lightweight neural network, a deformable convolutional layer and coordinate attention modules were added to the network. The results showed that the improved model size was 11.78 M, 18.30% of that of YOLOv4, and the detection speed was improved by 11.68 FPS. The detection accuracy, recall, and AP of tea canopy shoots under different light conditions were 85.35%, 78.42%, and 82.12%, respectively, which were 1.08%, 12.52%, and 8.20% higher than MobileNetV3-YOLOv4, respectively. The developed lightweight model could effectively and rapidly detect tea canopy shoots under all-day light conditions, which provides the potential to develop an all-day intelligent tea picking platform.

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Spoerri, I., K. Scherer, S. Michel, S. Link, A. J. Bircher, and I. A. F. M. Heijnen. "Detection of nickel and palladium contact hypersensitivity by a flow cytometric lymphocyte proliferation test." Allergy 70, no. 3 (2014): 323–27. http://dx.doi.org/10.1111/all.12553.

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17

Sereme, Youssouf, Natacha Casanovas, Moïse Michel, et al. "IgG removal significantly enhances detection of microarray allergen‐specific IgE reactivity in patients' serum." Allergy 76, no. 1 (2020): 395–98. http://dx.doi.org/10.1111/all.14536.

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18

Wang, Wei, Li, Du, and Zhang. "Optical Parameters Optimization for All-Time Star Sensor." Sensors 19, no. 13 (2019): 2960. http://dx.doi.org/10.3390/s19132960.

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As an important development direction of star sensor technology, the All-Time star sensor technology can expand the application of star sensors to flight platforms inside the atmosphere. Due to intense atmospheric background radiation during the daytime, the commonly used star sensors operating in the visible wavelength range are significantly limited in their ability to detect stars, and hence the All-Time star sensor technology which is based on the shortwave infrared (SWIR) imaging system has become an effective research direction. All-Time star sensor detection capability is significantly affected by observation conditions and, therefore, an optimized selection of optical parameters, which mainly includes the field of view (FOV) and the detection wavelength band, can effectively improve the detection performance of All-Time star sensors under harsh observation conditions. This paper uses the model simulation method to analyze and optimize the optical parameters under various observation conditions in a high-altitude environment. A main parameter among those discussed is the analysis of detection band optimization based on the SWIR band. Due to the huge cost constraints of high-altitude experiments, we conducted experiments near the ground to verify the effectiveness of the detection band selection and the correctness of the SWIR star sensor detection model, which thereby proved that the optimization of the optical parameters for high altitudes was effective and could be used as a reference.

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19

Li, Meng, Mengpeng Hu, Hui Zhang, et al. "All-Fiber Photoacoustic Gas Sensing with Interferometric Location." Photonics 9, no. 8 (2022): 546. http://dx.doi.org/10.3390/photonics9080546.

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Photoacoustic spectroscopy (PAS) is a promising gas detection technique with high sensitivity, fast response, and good stability. Frequency-modulated continuous-wave (FMCW) interferometry offers precise distance detection with high spatial resolution. The combination of PAS and FMCW may lead to an optical technique for the simultaneous extraction of gas concentration and location information. Herein, we demonstrate this technique in an all-fiber sensing system by blending a fiber-pigtailed PAS sensor with an FMCW interferometer. As an example, we have measured the methane concentration and location by employing time-division multiplexing, showing a minimum detection limit of 28 ppm and a spatial resolution of 3.87 mm over a distance of ~4.9 m. This study enables the realization of a versatile technique for multiparameter gas sensing in gas leakage detection and gas emission monitoring.

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20

Wu, Xiujia, Panpan Li, Xiangfeng Wei, and Jiehua Liu. "All-Inorganic Perovskite Single Crystals for Optoelectronic Detection." Crystals 12, no. 6 (2022): 792. http://dx.doi.org/10.3390/cryst12060792.

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Due to their many varieties of excellent optoelectric properties, perovskites have attracted large numbers of researchers in the past few years. For the hybrid perovskites, a long diffusion length, long carrier lifetime, and high μτ product are particularly noticeable. However, some disadvantages, including high toxicity and instability, restrict their further large-scale application. By contrast, all-inorganic perovskites not only have remarkable optoelectric properties but also feature high structure stability due to the lack of organic compositions. Benefiting from these, all-inorganic perovskites have been extensively explored and studied. Compared with the thin film type, all-inorganic perovskite single crystals (PSCs) with fewer grain boundaries and crystalline defects have better optoelectric properties. Nevertheless, it is important to note that only a few reports to date have presented a summary of all-inorganic PSCs. In this review, we firstly make a summary and propose a classification method according to the crystal structure. Then, based on the structure classification, we introduce several representative materials and focus on their corresponding growth methods. Finally, applications for detectors of all-inorganic PSCs are listed and summarized. At the end of the review, based on the current research situation and trends, some perspectives and advice are proposed.

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21

Adam, Jan, Jens Buss, Kai Brügge, Max Nöthe, and Wolfgang Rhode. "Cloud Detection and Prediction with All Sky Cameras." EPJ Web of Conferences 144 (2017): 01004. http://dx.doi.org/10.1051/epjconf/201714401004.

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22

Andonovic, I., L. Tancevski, M. Shabeer, and L. Bazgaloski. "Incoherent all-optical code recognition with balanced detection." Journal of Lightwave Technology 12, no. 6 (1994): 1073–80. http://dx.doi.org/10.1109/50.296202.

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23

Zhang Songlong, 张松龙, and 谢林柏 Xie Linbo. "Salient Detection Based on All Convolutional Feature Combination." Laser & Optoelectronics Progress 55, no. 10 (2018): 101502. http://dx.doi.org/10.3788/lop55.101502.

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24

Wang, Zexi, Zhiyi Zhang, and Changqing Xu. "All-Printed Microfluidic–Electrochemical Devices for Glucose Detection." Biosensors 14, no. 12 (2024): 569. http://dx.doi.org/10.3390/bios14120569.

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Free-standing capillary microfluidic channels were directly printed over printed electrodes using a particle/polymer mixture to fabricate microfluidic–electrochemical devices on polyethylene terephthalate (PET) films. Printed devices with no electrode modification were demonstrated to have the lowest limit of detection (LOD) of 7 μM for sensing glucose. The study shows that both a low polymer concentration in the mixture for printing the microfluidic channels and surface modification of the printed microfluidic channels using 3-aminopropyltrimethoxysilane can substantially boost the device’s performance. It also shows that both device structure and enzyme doping level of the devices play an important role in ensuring the best performance of the devices under various testing conditions.

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Apostolico, Alberto, Dany Breslauer, and Zvi Galil. "Parallel detection of all palindromes in a string." Theoretical Computer Science 141, no. 1-2 (1995): 163–73. http://dx.doi.org/10.1016/0304-3975(94)00083-u.

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26

Sadeghi, R., T. Ramqvist, Yilin Wang, M. Söderlund-Venermo, and K. Hedman. "Multiplex detection of all currently known human polyomaviruses." Journal of Clinical Virology 70 (September 2015): S121. http://dx.doi.org/10.1016/j.jcv.2015.07.281.

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27

Wang, X. X., C. J. Martoff, and E. Kaczanowicz. "All-thin-film GeAu thermistors for particle detection." Journal of Low Temperature Physics 93, no. 3-4 (1993): 349–54. http://dx.doi.org/10.1007/bf00693445.

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28

The Lancet Microbe. "“Global disease detection—free to all.” Or not." Lancet Microbe 4, no. 9 (2023): e657. http://dx.doi.org/10.1016/s2666-5247(23)00263-x.

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29

Amara, Pavan. "Cellulitis: symptoms and detection in all skin tones." Nursing Older People 35, no. 4 (2023): 16–17. http://dx.doi.org/10.7748/nop.35.4.16.s6.

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Amali, M. O., A. Sullivan, R. E. Jenkins та ін. "Detection of drug-responsive B lymphocytes and antidrug IgG in patients with β-lactam hypersensitivity". Allergy 72, № 6 (2016): 896–907. http://dx.doi.org/10.1111/all.13087.

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31

Shao, Junjie, Lingxiao Zhou, Sze Yan Fion Yeung, Ting Lei, Wanlong Zhang, and Xiaocong Yuan. "Pulmonary Nodule Detection and Classification Using All-Optical Deep Diffractive Neural Network." Life 13, no. 5 (2023): 1148. http://dx.doi.org/10.3390/life13051148.

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A deep diffractive neural network (D2NN) is a fast optical computing structure that has been widely used in image classification, logical operations, and other fields. Computed tomography (CT) imaging is a reliable method for detecting and analyzing pulmonary nodules. In this paper, we propose using an all-optical D2NN for pulmonary nodule detection and classification based on CT imaging for lung cancer. The network was trained based on the LIDC-IDRI dataset, and the performance was evaluated on a test set. For pulmonary nodule detection, the existence of nodules scanned from CT images were estimated with two-class classification based on the network, achieving a recall rate of 91.08% from the test set. For pulmonary nodule classification, benign and malignant nodules were also classified with two-class classification with an accuracy of 76.77% and an area under the curve (AUC) value of 0.8292. Our numerical simulations show the possibility of using optical neural networks for fast medical image processing and aided diagnosis.

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Zhai, Jiawei, Bin Luo, Aixue Li, Hongtu Dong, Xiaotong Jin, and Xiaodong Wang. "Unlocking All-Solid Ion Selective Electrodes: Prospects in Crop Detection." Sensors 22, no. 15 (2022): 5541. http://dx.doi.org/10.3390/s22155541.

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This paper reviews the development of all-solid-state ion-selective electrodes (ASSISEs) for agricultural crop detection. Both nutrient ions and heavy metal ions inside and outside the plant have a significant influence on crop growth. This review begins with the detection principle of ASSISEs. The second section introduces the key characteristics of ASSISE and demonstrates its feasibility in crop detection based on previous research. The third section considers the development of ASSISEs in the detection of corps internally and externally (e.g., crop nutrition, heavy metal pollution, soil salinization, N enrichment, and sensor miniaturization, etc.) and discusses the interference of the test environment. The suggestions and conclusions discussed in this paper may provide the foundation for additional research into ion detection for crops.

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Jingbo, Zhang, Ren Jie, and Wang Meiqi. "All-weather airport runway foreign object detection based on mixed attention." Scientific Insights and Discoveries Review 5 (October 14, 2024): 311–24. http://dx.doi.org/10.59782/sidr.v5i1.166.

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Foreign object detection on airport runways plays a vital role in the safe takeoff and landing of aircraft. However, the existing detection algorithms have the phenomenon of missed detection and false detection under different lighting and weather runway environments. Therefore, a YOLOv5 foreign object detection algorithm suitable for all-weather airport runway environment is proposed. Aiming at the problem of a certain degree of feature loss in the pooling process of the original network, a cross-stage local spatial pyramid pooling module is designed, which can adaptively extract deep feature semantic information and enhance the multi-scale representation ability of the network; a hybrid attention module is introduced in the feature fusion part, and the channel and spatial feature weights are redistributed to strengthen the feature difference between foreign objects and irrelevant background elements; in view of the fact that small foreign objects are difficult to identify and locate, resulting in missed detection, a multi-scale positioning loss function is designed, and the detection ability of small targets is improved by adding similarity measurement; the optimized training strategy is used to train the MS-FOD dataset. Experimental results show that the improved algorithm achieves 95.83%mAP and Recall, which are respectively improved 94.31% by and 15.69% compared with the original YOLOv5 3.68% , and the detection speed is 68 frames /s , which meets the needs of real-time foreign object detection. The effectiveness of the proposed algorithm for foreign object detection on airport runways is effectively verified.

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Li, Wunan, Yu Cao, Wenjing Zhang, Yu Ning, and Xiaojun Xu. "Cloud Detection Method Based on All-Sky Polarization Imaging." Sensors 22, no. 16 (2022): 6162. http://dx.doi.org/10.3390/s22166162.

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Sky cloud detection has a significant application value in the meteorological field. The existing cloud detection methods mainly rely on the color difference between the sky background and the cloud layer in the sky image and are not reliable due to the variable and irregular characteristics of the cloud layer and different weather conditions. This paper proposes a cloud detection method based on all-sky polarization imaging. The core of the algorithm is the “normalized polarization degree difference index” (NPDDI). Instead of relying on the color difference information, this index identifies the difference between degree of polarization (DoPs) of the cloud sky and the clear sky radiation to achieve cloud recognition. The method is not only fast and straightforward in the algorithm, but also can detect the optical thickness of the cloud layer in a qualitative sense. The experimental results show a good cloud detection performance.

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Thieme, Constantin J., Mohamed Abou‐el‐Enein, Enrico Fritsche, et al. "Detection of SARS‐CoV‐2‐specific memory B cells to delineate long‐term COVID‐19 immunity." Allergy 76, no. 8 (2021): 2595–99. http://dx.doi.org/10.1111/all.14827.

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Pastor-Vargas, C., A. S. Maroto, A. Díaz-Perales, et al. "Sensitive detection of major food allergens in breast milk: first gateway for allergenic contact during breastfeeding." Allergy 70, no. 8 (2015): 1024–27. http://dx.doi.org/10.1111/all.12646.

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37

Men, Kuo, Ziwei Lian, Hailing Tu, et al. "An All-Dielectric Metamaterial Terahertz Biosensor for Cytokine Detection." Micromachines 15, no. 1 (2023): 53. http://dx.doi.org/10.3390/mi15010053.

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In this paper, we report an all-dielectric metamaterial terahertz biosensor, which exhibits a high Q factor of 35 at an 0.82 resonance peak. A structure with an electromagnetically induced transparency effect was designed and fabricated to perform a Mie resonance for the terahertz response. The biosensor exhibits a limit of detection of 100 pg/mL for cytokine interleukin 2 (IL-2) and a linear response for the logarithm of the concentration of IL-2 in the range of 100 pg/mL to 1 μg/mL. This study implicates an important potential for the detection of cytokines in serum and has potential application in the clinical detection of cytokine release syndrome.

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Zhu, Juncai, Zhizhong Wang, Songwei Wang, and Shuli Chen. "Moving Object Detection Based on Background Compensation and Deep Learning." Symmetry 12, no. 12 (2020): 1965. http://dx.doi.org/10.3390/sym12121965.

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Detecting moving objects in a video sequence is an important problem in many vision-based applications. In particular, detecting moving objects when the camera is moving is a difficult problem. In this study, we propose a symmetric method for detecting moving objects in the presence of a dynamic background. First, a background compensation method is used to detect the proposed region of motion. Next, in order to accurately locate the moving objects, we propose a convolutional neural network-based method called YOLOv3-SOD for detecting all objects in the image, which is lightweight and specifically designed for small objects. Finally, the moving objects are determined by fusing the results obtained by motion detection and object detection. Missed detections are recalled according to the temporal and spatial information in adjacent frames. A dataset is not currently available specifically for moving object detection and recognition, and thus, we have released the MDR105 dataset comprising three classes with 105 videos. Our experiments demonstrated that the proposed algorithm can accurately detect moving objects in various scenarios with good overall performance.

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Hofmann, S. C., J. Fischer, C. Eriksson, O. Bengtsson Gref, T. Biedermann та T. Jakob. "IgE detection to α/β/γ-gliadin and its clinical relevance in wheat-dependent exercise-induced anaphylaxis". Allergy 67, № 11 (2012): 1457–60. http://dx.doi.org/10.1111/all.12020.

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Mahdi, Yasmeen, Bassam Hameed, Fahim Mahmood, Khalid Qassim, and Hind Al-Mamoori. "DETECTION OF ETV6/RUNX1 FUSION GENE USING FISH TECHNIQUE DETECTION IN PEDIATRIC ALL PATIENTS." Iraqi Journal of Medical Sciences 17, no. 3-4 (2019): 201–6. http://dx.doi.org/10.22578/ijms.17.3-4.6.

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Background:One of the commonest genetic subtypes of acute lymphoblastic leukemia (ALL) is t (12;21) (ETV6/RUNX1) being associated with favorable prognosis and distinctive clinical and pathological features. There are few studies about this abnormality in Iraq. Objective:To detect the expression ETV6/RUNX1 fusion gene in B-ALL pediatric patients by using FISH technique. Methods:This cross-sectional study was conducted from April 2018 to September 2018. Forty-eight newly diagnosed children with B-ALL were enrolled in this study. Fresh peripheral heparinized blood sample (3 ml) were taken from the patient at admission before chemotherapy, and ETV6-RUNX1 probe was applied and reading done by florescent microscope. Results:The mean age of study group was (4.01±0.19) years, their median age was 4.1 years, ranging between (2-7.2) years at diagnosis, ETV6/RUNX1 chimeric transcript product was found in 19 of 48 (39.6%) pediatric B- ALL patients. Conclusion:The frequency of investigated translocation [t(12;21)/ETV6/RUNX1 in a sample of Iraqi pediatric B-ALL patients, was among the higher reported frequencies worldwide, and that ETV6/RUNX1 fusion gene is independent prognostic factor not related to other hematological and clinical parameters. Keywords:ETV6/RUNX1 fusion gene, pediatric ALL, FISH Citation:Mahdi YM, Hameed BM, Mahmood FM, Qassim KW, Al-Mamoori HS. Detection of ETV6/RUNX1 fusion gene using FISH technique detection in pediatric all patients. Iraqi JMS. 2019; 17(3&4): 201-206. doi: 10.22578/IJMS.17.3&4.6

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Law, Casey J., and Geoffrey C. Bower. "ALL TRANSIENTS, ALL THE TIME: REAL-TIME RADIO TRANSIENT DETECTION WITH INTERFEROMETRIC CLOSURE QUANTITIES." Astrophysical Journal 749, no. 2 (2012): 143. http://dx.doi.org/10.1088/0004-637x/749/2/143.

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Yao, Xincheng, Chongyang Zhang, Ruoqi Li, Jun Sun, and Zhenyu Liu. "One-for-All: Proposal Masked Cross-Class Anomaly Detection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (2023): 4792–800. http://dx.doi.org/10.1609/aaai.v37i4.25604.

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One of the most challenges for anomaly detection (AD) is how to learn one unified and generalizable model to adapt to multi-class especially cross-class settings: the model is trained with normal samples from seen classes with the objective to detect anomalies from both seen and unseen classes. In this work, we propose a novel Proposal Masked Anomaly Detection (PMAD) approach for such challenging multi- and cross-class anomaly detection. The proposed PMAD can be adapted to seen and unseen classes by two key designs: MAE-based patch-level reconstruction and prototype-guided proposal masking. First, motivated by MAE (Masked AutoEncoder), we develop a patch-level reconstruction model rather than the image-level reconstruction adopted in most AD methods for this reason: the masked patches in unseen classes can be reconstructed well by using the visible patches and the adaptive reconstruction capability of MAE. Moreover, we improve MAE by ViT encoder-decoder architecture, combinational masking, and visual tokens as reconstruction objectives to make it more suitable for anomaly detection. Second, we develop a two-stage anomaly detection manner during inference. In the proposal masking stage, the prototype-guided proposal masking module is utilized to generate proposals for suspicious anomalies as much as possible, then masked patches can be generated from the proposal regions. By masking most likely anomalous patches, the “shortcut reconstruction” issue (i.e., anomalous regions can be well reconstructed) can be mostly avoided. In the reconstruction stage, these masked patches are then reconstructed by the trained patch-level reconstruction model to determine if they are anomalies. Extensive experiments show that the proposed PMAD can outperform current state-of-the-art models significantly under the multi- and especially cross-class settings. Code will be publicly available at https://github.com/xcyao00/PMAD.

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Zaliova, Marketa, Leona Reznickova, Eva Fronkova, et al. "MRD Monitoring Reveals a Specific Biology of BCR/ABL-Positive ALL." Blood 112, no. 11 (2008): 2529. http://dx.doi.org/10.1182/blood.v112.11.2529.2529.

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Abstract Minimal residual disease (MRD) monitoring is an essential tool for current leukaemia therapy. The only standard method for MRD monitoring in childhood ALL is the quantitative detection of clonal immunoglobulin (Ig) and T-cell receptor (TCR) genes rearrangements. The quantitative detection of fusion genes or transcripts provides an alternative option for MRD monitoring. We aimed to compare the significance of these MRD methods by parallel monitoring of fusion transcripts/genes and Ig/TCR targets during the follow-up of children from the three most common ALL genotype groups. We analysed 117, 109 and 191 bone marrow samples from 28 TEL/AML1-positive, 7 MLL fusion-positive and 16 BCR/ABL-positive patients, respectively. To keep the comparability of different MRD approaches, we used qPCR detection systems with similar sensitivity (at least 10−4), we adopted ESG-MRD-ALL principles for MRD quantification and we related the MRD level in follow-up samples to the diagnostic level for all MRD methods. We found a very good correlation of fusion transcript- and Ig/TCR-based approaches (R2=0.903) with only 7% of samples differing by more than 1 log in a cohort of TEL/AML1-positive patients. A good correlation was also found between fusion transcript- and Ig/TCR-based MRD in MLL fusion-positive patients (R2=0.8419). Only 10% of samples differed by more than 1 log, being underestimated by Ig/TCR in 4.5% and by MLL-fusion transcript in 5.5%. For the follow-up of MLL-fusion-positive patients we further employed the monitoring of MLL-fusions on genomic level. The MRD based on genomic MLLfusion genes showed a very good correlation with Ig/TCR -based method (R2=0.9124) with only 5% of samples differing by more than 1 log, and it also closely correlated with MLL-fusion transcript levels (R2=0.9195). Strikingly, in BCR/ABL-positive patients we found a limited correlation of fusion transcript-based and Ig/TCR-based MRD (R2=0.6880) with 1/3 (34%) of samples differing by more than 1 log. In contrast to the MLL cases, the underestimation of MRD by individual methods was “asymmetrical”: 8% of the discordant samples had higher MRD measured by Ig/TCR and 26% by BCR/ABL transcript. Despite identical sensitivity of both methods, in 19% of samples the MRD positivity was revealed only by BCR/ABL approach while Ig/TCR approach gave negative results. Detailed analysis showed clinical significance of the discordant BCR/ABL vs. Ig/TCR MRD information. Altogether, 13 relapses occurred during the follow-up of our cohort. We compared number of BCR/ABL and Ig/TCR -positive samples among all BM specimens taken 6 and 12 months before relapse. While the majority of samples preceding relapse were BCR/ABL-positive (14/18 and 22/36 six and twelve months before relapse) only a minority of samples showed Ig/TCR positivity (7/18 and 12/36, respectively). The non-equal distribution of the BCR/ABL and Ig/TCR-positive samples was statistically significant (p=0.04 and p=0.03 for the two time-points, respectively). Our study shows, that in TEL/AML1 and MLL fusion-positive patients, fusion gene/transcript-based MRD monitoring provides information highly concordant to the standard Ig/TCR approach and thus it is useful as a complementary method in patients with absent or inadequate Ig/TCR targets (particularly in MLL cases where clonal Ig/TCR rearrangements are rare). The situation is different in BCR/ABL patients, where the MRD information from both approaches is discordant in a high subset of samples. This result probably reflects the dissimilar biology of this ALL subtype and the fact, that BCR/ABL-positive (prae-)leukaemic stem cell is different and multilineage involvement more common. Thus, in some cases, the fusion transcript monitoring reveals the existing pool of cells that increase the risk of relapse despite the Ig/TCR negativity. We conclude that MRD in all BCR/ABL–positive patients should be monitored not only by the standard Ig/TCR approach but in parallel also by the quantitative fusion transcript-based detection. Support: MSM0021620813, MZO00064203.

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Ouyang, Ao, Huan Zhou, Pintu Ghosh, and Qiang Li. "The Detection of Acetylcholinesterase Based on All-Dielectric Nanoantennas." Journal of Physics: Conference Series 1838, no. 1 (2021): 012022. http://dx.doi.org/10.1088/1742-6596/1838/1/012022.

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Baždarić, Ksenija. "Plagiarism detection – quality management tool for all scientific journals." Croatian Medical Journal 53, no. 1 (2012): 1–3. http://dx.doi.org/10.3325/cmj.2012.53.1.

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Shan, Nana, and Yonghai Wang. "All Zero Block Detection of Transform Coefficients in HEVC." IJEMR 6, no. 1 (2022): 1–7. http://dx.doi.org/10.22662/ijemr.2022.6.1.001.

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Rao, Jayasimha, Noora Partamies, Olga Amariutei, Mikko Syrjasuo, and Koen E. A. van de Sande. "Automatic Auroral Detection in Color All-Sky Camera Images." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7, no. 12 (2014): 4717–25. http://dx.doi.org/10.1109/jstars.2014.2321433.

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Cui, Jing, Ruiqin Xiong, Xinfeng Zhang, et al. "Hybrid All Zero Soft Quantized Block Detection for HEVC." IEEE Transactions on Image Processing 27, no. 10 (2018): 4987–5001. http://dx.doi.org/10.1109/tip.2018.2837351.

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Klare, Peter. "Adenoma detection rate – is it all about adding water?" Endoscopy 49, no. 05 (2017): 427–28. http://dx.doi.org/10.1055/s-0043-105483.

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Nakakita, Yasukazu, Toshihiro Takahashi, Youichi Tsuchiya, Junji Watari, and Ken Shinotsuka. "A Strategy for Detection of All Beer-Spoilage Bacteria." Journal of the American Society of Brewing Chemists 60, no. 2 (2002): 63–67. http://dx.doi.org/10.1094/asbcj-60-0063.

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