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1
Kumaresh, Sakthi, and R. Baskaran. "Software Defect Prevention through Orthogonal Defect Classification (ODC)." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 3 (October 15, 2013): 2393–400. http://dx.doi.org/10.24297/ijct.v11i3.1166.
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“Quality is never an accident; it is always the result of intelligent effort†[10]. In the process of making quality software product, it is necessary to have effective defect prevention process, which will minimize the risk of making defects /errors in software deliverables. An ideal approach would involve effective software development process with an integrated defect prevention process. This paper presents a Defect Prevention Model in which Defect Prevention Process(DPP) is integrated into software development life cycle to reduce the defects at early stages itself, thereby reducing the defect arrival rate as the project progresses to the subsequent stages. Orthogonal Defect Classification (ODC) scheme involving defect trigger, defect type etc. are discussed in this work to illustrate how ODC can be used in the defect prevention process. ODC can be used to measure development progress with respect to product quality and identify process problems, which will help to come out with “Best Practices†to be followed to eradicate the defects in the subsequent projects.
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Liu, Xing Fang, Guo Sheng Sun, Jin Min Li, Yong Mei Zhao, J. Y. Li, L. Wang, Wan Shun Zhao, M. C. Luo, and Yi Ping Zeng. "Micro-Raman Investigation of Defects in a 4H-SiC Homoepilayer." Materials Science Forum 556-557 (September 2007): 387–90. http://dx.doi.org/10.4028/www.scientific.net/msf.556-557.387.
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Three types of defects, namely defect I, defect II, defect III, in the 4H-SiC homoepilayer were investigated by micro-raman scattering measurement. These defects all originate from a certain core and are composed of (I) a wavy tail region, (II) two long tails, the so called comet and (III) three plaits. It was found that there are 3C-SiC inclusions in the cores of defect II and defect III and the shape of inclusion determines the type of defect II or defect III. If the core contains a triangle-shaped inclusion, the defect III would be formed; otherwise, the defect II was formed. No inclusion was observed in the core of the defect I. The mechanisms of these defects are discussed.
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Park, Jungeun, Yongwoon Cha, Hamad Al Jassmi, Sangwon Han, and Chang-taek Hyun. "Identification of Defect Generation Rules among Defects in Construction Projects Using Association Rule Mining." Sustainability 12, no. 9 (May 9, 2020): 3875. http://dx.doi.org/10.3390/su12093875.
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This study aims to identify the defect generation rules between defects, to support effective defect prevention at construction sites. Numerous studies have been performed to identify the relations between defect causes, to prevent defects in construction projects. However, identifying the inter-causal pattern does not yet guarantee an ultimate grasp of what constitutes proper defect mitigation strategies, unless the underlying defect-to-defect generation rules are thoroughly understood too. Specifically, if a defect generated in a work process is ignored without taking necessary corrective action, then additional defects could be generated in its following works as well. Thus, to minimize defect generation, this study analyzes the defects in the sequence of a construction work. To achieve this, the authors collected 9054 defect data, and association rule mining is used to analyze the rules between the defects. Consequently, 216 rules are identified, and 152 rules are classified into 3 categories along with 4 experts (71 expected rules, 22 unexpected but explainable rules, and 59 unexpected and unexplainable rules). The generation rules between the defects identified in this study are expected to be used to regularize various defect types to determine those that require priority management.
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Park, Junmo, and Deokseok Seo. "Defect Index of Timberwork in House, Korea." Forests 12, no. 7 (July 8, 2021): 896. http://dx.doi.org/10.3390/f12070896.
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Wood is a material that is familiar to humans and environment-friendly, and it is used widely as a building material. However, as the dispute over housing defects have increased in Korea, various defects have occurred in timberwork and have become disputes. Notwithstanding, efforts to analyze defects in timberwork systematically to reasonably solve the problem are lacking. In this study, defects in timberwork from housing complexes in Korea were standardized, and critical defects were selected to suggest a method as a management standard. The standard for defects includes time, types of facility work, location and subject, and defect phenomenon. The defect time is categorized into before handover and after handover, whereas facility work is divided into woodwork, door and window work, finishing work, and miscellaneous work. Location and subject are categorized into 13 areas, such as ceiling, floor, and door, and phenomena concerned are of 14 types, including faults and no installation. Therefore, the standardized defect items according to such criteria are classified into a total of 63 types. Ten defect items, whose numbers of defect occurrences per defect and defect repair cost ratio above the average, were selected, including discoloration and breakage of the wooden floor. The repair cost ratio of these defect items accounted for 85.62% of the total repair costs. On the contrary, the repair cost for the defects from the timber work outlined in the Construction Appraisal Practice, a representative defect standard in Korea, was 54.54% of the total. Meanwhile, according to the Defect Judgment Standard, the defect repair cost attributed 45.54% of the total. Therefore, since the 10 defect items proposed in this study can explain the defects in the timberwork compared with other standards, it would be reasonable to designate these 10 defect items as essential defects.
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Bentham, James R., Arjun Gujral, Satish Adwani, Nick Archer, and Neil Wilson. "Does the technique of interventional closure of perimembranous ventricular septal defect reduce the incidence of heart block?" Cardiology in the Young 21, no. 3 (February 1, 2011): 271–80. http://dx.doi.org/10.1017/s1047951110002039.
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AbstractObjectiveTo describe the difficulties and differing techniques in the transcatheter placement of amplatz ventricular septal defect devices to close perimembranous ventricular septal defects and place these in the context of the expanding literature on ventricular septal defect catheter closure.BackgroundSurgery remains the established first-line therapy for closure of haemodynamically significant perimembranous ventricular septal defects. Transcatheter techniques appeared to promise a possible alternative, obviating the need for cardiac surgery. However, significant technical and anatomical constraints coupled with ongoing reports of a high incidence of heart block have prevented these hopes from being realised to any significant extent. It is likely that there are important methodological reasons for the high complication rates observed. The potential advantages of transcatheter perimembranous ventricular septal defect closure over surgery warrant further exploration of differing transcatheter techniques.MethodsBetween August, 2004 and November, 2009, 21 patients had a perimembranous ventricular septal defect closed with transcatheter techniques. Of these, 14 were closed with a muscular amplatz ventricular septal defect device. The median age and weight at device placement were 8 years, ranging from 2 to 19 years, and 18.6 kilograms, ranging from 10 to 21 kilograms, respectively.ResultsThere were 25 procedures performed on 23 patients using 21 amplatz ventricular septal defect devices. Median defect size on angiography was 7.8 millimetres, ranging from 4 to 14.3 millimetres, with a median device size of 8 millimetres, ranging from 4 to 18 millimetres, and a defect/device ratio of 1.1, with a range from 0.85 to 1.33. Median procedure time was 100 minutes, with a range from 38 to 235 minutes. Adverse events included device embolisation following haemolysis in one, and new aortic incompetence in another, but there were no cases of heart block. Median follow-up was 41.7 months, with a rangefrom 2 to 71 months.ConclusionsEvaluating transcatheter closure of perimembranous ventricular septal defect using amplatz ventricular septal defect devices remains important, if a technically feasible method with low and acceptable complication rates is to be identified. Incidence of heart block may be minimised by avoiding oversized devices, using muscular devices, and accepting defeat if an appropriately selected device pulls through. Given the current transcatheter technologies, the closure of perimembranous ventricular septal defects should generally be performed in children when they weigh at least 10 kilograms.
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Kawakita, Shirou, Mitsuru Imaizumi, Shogo Ishizuka, Hajime Shibata, Shigeru Niki, Shuichi Okuda, and Hiroaki Kusawake. "Characterization of Electron-Induced Defects in Cu (In, Ga) Se2 Thin Films by Photoluminescence." MRS Proceedings 1771 (2015): 157–61. http://dx.doi.org/10.1557/opl.2015.405.
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ABSTRACTCIGS thin films were irradiated with 100 or 250 keV electrons to reveal the radiation defect by analyzing PL measurement. The PL intensity decreased due to non-radiative recombination defects induced by electron irradiation. Furthermore, the intensity 0.8 eV peak of the PL spectrum was observed from CIGS films irradiated with 250 eV electrons and is said to correspond to In-antisite defects in CIGS materials. The defects can usually change into InCu-VCu complex defects combined with VCu, since the formation energy of the complex defect is lower than that of each defect. Cu interstitial defects induced by 250 keV electron irradiation would diffuse to VCu of the complex defect, whereupon the complex defect might become an In-antisite defect due to 250 keV electron irradiation.
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Fukuda, Toyoki, Ichiro Kashima, and Shigeki Yoshiba. "Surgical treatment of an unusual atrial septal defect: the vestibular defect." Cardiology in the Young 14, no. 2 (April 2004): 212–14. http://dx.doi.org/10.1017/s1047951104002197.
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A 14-year-old female patient underwent surgical treatment of multiple atrial septal defects associated with unroofed coronary sinus and pulmonary valvar stenosis. One of the defects was that of the superior oval fossa and the other a large ellipsoidal defect positioned inferior to the inferior rim of the oval fossa. The patient underwent primary closure of the defects with a favorable result. To the best of our knowledge, this is the first surgical experience of an unusual atrial septal defect or the vestibular defect.
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HUQ, ABUL M. A., ABUHANIF K. BHUIYAN, KIN LIAO, and KHENG LIM GOH. "DEFECT–DEFECT INTERACTION IN SINGLE-WALLED CARBON NANOTUBES UNDER TORSIONAL LOADING." International Journal of Modern Physics B 24, no. 10 (April 20, 2010): 1215–26. http://dx.doi.org/10.1142/s021797921005510x.
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This paper presents an analysis of interactions between a pair of Stone–Wales (SW) defects in a single-walled carbon nanotube (SWCNT) that has been subjected to an external torque. Defect pairs, representing the different combinations of SW defect of A (SW-A) and B (SW-B) modes, were incorporated in SWCNT models of different chirality and diameter and solved using molecular mechanics. Defect–defect interaction was investigated by evaluating the C–C steric interactions in the defect that possesses the highest potential energy, E, as a function of inter-defect distance, D. This study reveals that the deformation of the C–C bond is attributed to bond stretching and bending. In the SW-B defects, there is an additional contributor arising from the dihedral angular deformation. The magnitude of E depends on the type of defect but the profile of the E versus D curve depends on the orientation of the defects. The largest indifference length, D0, beyond which two defects cease to interact, is approximately 30 Å. When the angular displacement of the tube increases two-fold, E increases, but the profile of the E versus D curve is not affected. The sense of rotation affects the magnitude of E but not the profile of the E versus D curve.
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Cao, Zhen, Da-Peng Hao, Gang Tang, Zhi-Peng Xun, and Hui Xia. "Influence of cluster shaped defects on fracture process of fiber bundle." Acta Physica Sinica 70, no. 20 (2021): 204602. http://dx.doi.org/10.7498/aps.70.20210310.
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Defects that exist inside composites have an important effect on the tensile fracture properties of composites. The fiber bundle model is a theoretical model commonly used to study the tensile fracture properties of disorder materials. Existing work on fiber bundle models with single fiber defects shows that after single fiber defects are introduced into the fiber bundle model, the defects have a significant effect on the tensile fracture properties of the model. Since there are more complex microscopic defect structures in actual materials, such as voids, gaps, impurities, dislocations, micro-cracks, etc, it is necessary to build a multi-size defect model. In order to study the defects of different sizes and damage degrees existing in actual materials, the spatial size of the defect, the degree of defect and the distribution of fiber damage levels within the defect and other influencing factors are introduced to construct an extended fiber bundle model with cluster shaped defects. For the model, it is first assumed that the degree of defect of the fiber inside each cluster decays linearly from the center to the outside in two spatial attenuation forms: exponential decay and constant degree of defect. In the fiber bundle model of this cluster-shaped defect, the two most important factors are the number of defects <i>α</i> and the upper limit of defect size <i>β</i>. The numerical simulation method is used to analyze the influence of the number of defects, the upper limit of defect size, and spatial distribution of degree of defective fibers inside defect on the macroscopic mechanical properties and statistical properties of fracture when the model is subjected to quasi-static load borne under the nearest neighbor stress redistribution. Through the simulation analysis, it is found that owing to the overlapping competition mechanism of the defect spatial distribution, when the upper limit <i>β</i> of the defect size is large, the influence of the number of defects on the system load capacity trends to saturation. Since the defect degree of the defect center fiber is proportional to the defect size, with the upper limit <i>β</i> of the defect size increasing, its influence on the load capacity of the model becomes more and more significant. When large size defects exist, even if the number of defects is small, the load bearing performance of the material will be significantly reduced. The spatial distribution function of the damage degree of fiber inside the defect has no substantial influence on the above rules, and only changes the specific value of each fracture property. The simulation analysis results in this paper have certain theoretical significance in improving the mechanical properties of composite materials.
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Yao, Zong Jian, Gui Lan Yu, Yue Sheng Wang, and Jian Bao Li. "Flexural Vibration in a Ternary Locally Resonant Phononic Crystal Thin Plate with Defects." Advanced Materials Research 150-151 (October 2010): 1282–85. http://dx.doi.org/10.4028/www.scientific.net/amr.150-151.1282.
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The improved supercell plane wave expansion method is applied to theoretically study the propagation of flexural waves in a ternary locally resonant phononic crystal thin plate with a point defect and linear defects. The thin concrete plate composed of a square array of steel cylinders hemmed around by rubber is considered here. Absolute band gaps in low frequency are obtained. For the point defect, the defect mode is localized around the defect, and the magnitude of the resonant defect mode is strongly dependent on the defect filling fraction, mass density and Young’s modulus of the defect cylinder. For the straight linear defects, several resonant linear defect bands appear inside the absolute band gap. And the displacement distributions show that the flexural waves could well propagate along the linear defects.
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Ling, Xiulan, Xin Chen, and Xiaofeng Liu. "Revisiting Defect-Induced Light Field Enhancement in Optical Thin Films." Micromachines 13, no. 6 (June 9, 2022): 911. http://dx.doi.org/10.3390/mi13060911.
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Based on a finite-difference time-domain method, we revisited the light field intensification in optical films due to defects with different geometries. It was found that defect can induce the local light intensification in optical films and the spherical defects resulted in the highest light intensification among the defect types investigated. Light intensification can increase with defect diameter and the relative refractive index between the defect and the film layer. The shallow defects tended to have the highest light intensification. Finally, the extinction coefficient of the defect had a significant effect on light intensification. Our investigations revealed that the light field intensification induced by a nano-defect is mainly attributed to the interference enhancement of incident light and diffracted or reflected light by defects when the size of the defect is in the subwavelength range.
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Wei, Jing, Zhengtao Zhang, Fei Shen, and Chengkan Lv. "Mask-Guided Generation Method for Industrial Defect Images with Non-uniform Structures." Machines 10, no. 12 (December 18, 2022): 1239. http://dx.doi.org/10.3390/machines10121239.
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Defect generation is a crucial method for solving data problems in industrial defect detection. However, the current defect generation methods suffer from the problems of background information loss, insufficient consideration of complex defects, and lack of accurate annotations, which limits their application in defect segmentation tasks. To tackle these problems, we proposed a mask-guided background-preserving defect generation method, MDGAN (mask-guided defect generation adversarial networks). First, to preserve the normal background and provide accurate annotations for the generated defect samples, we proposed a background replacement module (BRM), to add real background information to the generator and guide the generator to only focus on the generation of defect content in specified regions. Second, to guarantee the quality of the generated complex texture defects, we proposed a double discrimination module (DDM), to assist the discriminator in measuring the realism of the input image and distinguishing whether or not the defects were distributed at specified locations. The experimental results on metal, fabric, and plastic products showed that MDGAN could generate diversified and high-quality defect samples, demonstrating an improvement in detection over the traditional augmented samples. In addition, MDGAN can transfer defects between datasets with similar defect contents, thus achieving zero-shot defect detection.
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Liu, Jing, Zhifeng Shi, and Yimin Shao. "A theoretical study for the influence of the combined defect on radial vibrations of a ball bearing." Industrial Lubrication and Tribology 70, no. 2 (March 12, 2018): 339–46. http://dx.doi.org/10.1108/ilt-04-2016-0086.
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Purpose Combined defects in ball bearings may be caused during the use or manufacturing process, which can significantly affect their vibration characteristics. The previous defect models in the literature can only describe single defects such as the surface waviness and localized defect. This paper aims to propose an in-depth understanding of radial vibrations of a ball bearing with the combined defect. Design/methodology/approach A dynamic model for a ball bearing with the combined defect including the surface waviness and localized defect on its races is proposed. The effects of the combined defect sizes on the radial bearing vibrations are investigated. The results from the proposed model considering the combined defect are compared with the available results from the previous methods considering the single defects. Findings The acceleration amplitude is significantly affected by the surface waviness, localized defect and the combined defect on its races. The effect of the combined defect on the acceleration amplitude is larger than that of the single defect. The amplitude and peak frequency of the spectrum of acceleration for the combined defect increases with the defect sizes. The RMS value of the accelerations for the combined defect increases with the combined defect sizes. Originality/value Consequently, the proposed model can predict more accurate and in-depth understanding of the radial vibrations caused by the combined defect in the ball bearing.
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Zhang, Zhongli, Can Wang, Xiaowen Hu, and Yushan Ni. "Shape Effect of Surface Defects on Nanohardness by Quasicontinuum Method." Micromachines 11, no. 10 (September 30, 2020): 909. http://dx.doi.org/10.3390/mi11100909.
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Nanoindentation on a platinum thin film with surface defects in a rectangular shape and triangular shape was simulated using the quasicontinuum method to study the shape effect of surface defects on nanohardness. The results show that the nanohardness of thin film with triangular defects is basically larger than those with rectangular defects, which is closely related to the height of the surface defects at the boundary near to the indenter. Moreover, the triangular defect might have an enhancement effect on nanohardness by a certain size of the defects and the boundary orientation of the defect, where such an enhancement effect increases as the defect grows. Furthermore, the nanohardness decreases when the defect is folded from wide to narrow in the same atom cavity, and particularly expresses a more obvious drop when the height of the defects increases. In addition, larger sizes of the rectangular defect induce more reduction in nanohardness, while the nanohardness of the triangular surface defect is sensitive to the periodic arrangement of atoms changed by the boundary orientation of the defect, which is well explained and demonstrated by the calculation formula theory of necessary load for dislocation emission.
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Kumaresh, Sakthi, and Ramachandran Baskaran. "Mining Software Repositories for Defect Categorization." Journal of Communications Software and Systems 11, no. 1 (March 23, 2015): 31. http://dx.doi.org/10.24138/jcomss.v11i1.115.
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Early detection of software defects is very important to decrease the software cost and subsequently increase the software quality. Success of software industries not only depends on gaining knowledge about software defects, but largely reflects from the manner in which information about defect is collected and used. In software industries, individuals at different levels from customers to engineers apply diverse mechanisms to detect the allocation of defects to a particular class. Categorizing bugs based on their characteristics helps the Software Development team take appropriate actions to reduce similar defects that might get reported in future releases. Classification, if performed manually, will consume more time and effort. Human resource having expert testing skills & domain knowledge will be required for labeling the data. Therefore, the need of automatic classification of software defect is high.This work attempts to categorize defects by proposing an algorithm called Software Defect CLustering (SDCL). It aims at mining the existing online bug repositories like Eclipse, Bugzilla and JIRA for analyzing the defect description and its categorization. The proposed algorithm is designed by using text clustering and works with three major modules to find out the class to which the defect should be assigned. Software bug repositories hold software defect data with attributes like defect description, status, defect open and close date. Defect extraction module extracts the defect description from various bug repositories and converts it into unified format for further processing. Unnecessary and irrelevant texts are removed from defect data using data preprocessing module. Finally grouping of defect data into clusters of similar defect is done using clustering technique. The algorithm provides classification accuracy more than 80% in all of the three above mentioned repositories.
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Luo, Yun, Chuanlong Wang, Wenchun Jiang, Yu Wan, Weiya Zhang, and Yu Wang. "Effects of Inner Defects on Creep Damage and Crack Initiation for a Brazed Joint." High Temperature Materials and Processes 37, no. 9-10 (October 25, 2018): 863–72. http://dx.doi.org/10.1515/htmp-2017-0098.
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AbstractIn the brazing process, some brazing defects like semicircular or straight type are generated due to incomplete filling. In this paper, the creep damage and creep crack initiation (CCI) time of Hastelloy C276-BNi2 brazed joint with defects are investigated by a ductility exhaustion damage model. The effects of defect dimension and filler metal thickness are also discussed. The results show that the different defects have different creep damage distributions and CCI times. The maximum creep damage is located at the defect frontier due to the larger stress concentration. With the increase of semicircular defect radius and straight defect length, the CCI time decreases. The creep fracture is inclined to generate in semicircular defect for the smaller defect area ratio, while it is easy to generate in straight defect for the bigger defect area ratio. As the filler metal thickness increases, the CCI time increases. For the thicker filler metal, the creep crack is easy to initiate in semicircular defect.
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., Rutu, Rakesh M R, Pooja L, and Hema C. "Product Defect Identification System." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 459–67. http://dx.doi.org/10.22214/ijraset.2023.51485.
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Abstract: Some uncontrollable defects will occur on the surface of metal work pieces during processing. The existence of surface defects not only affects the appearance of the finished product, but also affects the quality to a certain extent. Surface defect detection of metal work pieces can effectively improve product quality and production efficiency, and is an important link in the process of product quality control. This proposed system uses the convolutional neural network algorithm in deep learning to classify and detect metal surface defects. The surface defect recognition accuracy and defect detection rate of metal work is computed.
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Falessi, Davide, Aalok Ahluwalia, and Massimiliano DI Penta. "The Impact of Dormant Defects on Defect Prediction: A Study of 19 Apache Projects." ACM Transactions on Software Engineering and Methodology 31, no. 1 (January 31, 2022): 1–26. http://dx.doi.org/10.1145/3467895.
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Defect prediction models can be beneficial to prioritize testing, analysis, or code review activities, and has been the subject of a substantial effort in academia, and some applications in industrial contexts. A necessary precondition when creating a defect prediction model is the availability of defect data from the history of projects. If this data is noisy, the resulting defect prediction model could result to be unreliable. One of the causes of noise for defect datasets is the presence of “dormant defects,” i.e., of defects discovered several releases after their introduction. This can cause a class to be labeled as defect-free while it is not, and is, therefore “snoring.” In this article, we investigate the impact of snoring on classifiers' accuracy and the effectiveness of a possible countermeasure, i.e., dropping too recent data from a training set. We analyze the accuracy of 15 machine learning defect prediction classifiers, on data from more than 4,000 defects and 600 releases of 19 open source projects from the Apache ecosystem. Our results show that on average across projects (i) the presence of dormant defects decreases the recall of defect prediction classifiers, and (ii) removing from the training set the classes that in the last release are labeled as not defective significantly improves the accuracy of the classifiers. In summary, this article provides insights on how to create defects datasets by mitigating the negative effect of dormant defects on defect prediction.
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Li, Xiaofei, Binbin Wang, Tingting Song, Min Zhang, Tixian Zeng, Jiang Chen, and Feiquan Zhang. "Aggregation of ODC(I) and POL Defects in Bismuth Doped Silica Fiber." Micromachines 14, no. 2 (January 31, 2023): 358. http://dx.doi.org/10.3390/mi14020358.
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First-principles calculations were used to simulate the aggregation of the peroxy chain defect POL and the oxygen vacancy defect ODC(I). Defect aggregation’s electronic structure and optical properties were investigated. The two defects were most likely to accumulate on a 6-membered ring in ortho-position. When the two defects are aggregated, it is discovered that 0.75 ev absorption peaks appear in the near-infrared band, which may be brought on by the addition of oxygen vacancy defect ODC(I). We can draw the conclusion that the absorption peak of the aggregation defect of ODC(I) defect and POL is more prominent in the near infrared region and visible light area than ODC(I) defect and POL defect.
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Mastap, Sushardi, Tibertius Agus Prayitno, Yustinus Suranto, and Ganis Lukmandaru. "Suitability of Teak Log Quality from Gunung Kidul and Bantul Yogyakarta Community Forest for Export Meubel Purpose." Journal of Sylva Indonesiana 4, no. 02 (August 30, 2021): 78–86. http://dx.doi.org/10.32734/jsi.v4i02.6347.
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Natural defect or poor log quality are common in community teak forests. Furniture manufacturers typically use these log types for export purposes. The aim of this study is to determine the effect of community teak forest location and teak stand age affect on teak wood quality. Three teak forest locations were Bantul and two locations in Gunung Kidul. The teak stand age class namely 6, 8, and 10 years old. The data was analyzed using SPSS 20.0 with Tukey test. The result showed that brittleness defect, sapwood defect, and different wooden knot defects were significant in all locations, while log straightness defect was found only in Dlingo. Similarly, all teak stand age (6, 8, and 10 years old) also produced the same defects such as brittleness defect, sapwood defect, and wood knot defect, while the straightness defect at the age of 10 years old was different from to other two teak stand age (6 and 8-year-old). Average teak log defects were straightness defect 1.87-3.53%, brittleness defect 1.19–6.21%, sapwood defect 1.49-4.82 cm, and wood knot defect 5.10-11.46 cm. However, the teak log quality still met the SNI 7534.2-2010 and 7535.2-2010 as raw material for exporting furniture.
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Dong, Yukun, Li Zhang, Shanchen Pang, Wenjing Yin, Mengying Wu, Meng Wu, and Haojie Li. "Automatic Repair of Semantic Defects Using Restraint Mechanisms." Symmetry 12, no. 9 (September 22, 2020): 1563. http://dx.doi.org/10.3390/sym12091563.
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Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired.
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Almazova, L. A., and O. S. Sedova. "SIMULATION OF THE SURFACE DEFECTS INFLUENCE ON THE ALUMINUM ALLOY BEHAVIOUR UNDER THE CYCLIC LOAD CONDITIONS." Frontier materials & technologies, no. 1 (2022): 7–14. http://dx.doi.org/10.18323/2782-4039-2022-1-7-14.
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Aluminum and its alloys, such as the Al–Si–Mg alloy, are widely used in various industrial and engineering fields due to their mechanical properties. In this case, the defects occurring during the casting process adversely affect the behavior of this alloy under cyclic load conditions. Therefore, the study aimed to investigate the surface defect influence on the material's fatigue strength is currently of great importance. The paper presents a numerical investigation based on the finite element method intended to evaluate the effect of the interaction of the complex-shaped defects on the stress of the Al–Si–Mg aluminum alloy. The developed complex-defect model consists of a hemispherical main (base) defect and a secondary defect at the bottom of the main one. The authors use the Chaboche model to describe the material’s behavior under the cyclic load conditions. The paper contains the computational solution constructed with the ANSYS Workbench platform. The authors supposed that it is possible to approximate the considered complex defect form by an equivalent simplified defect. The study shows that the maximum von Mises stress values for the complex-shaped defects are achieved at the joint of the secondary defect with the main one. In the case of an equivalent defect, the maximum values are observed at the defect's bottom and on the periphery. The authors comparatively estimated the uncertainty obtained using an equivalent defect and the cases of three complex-shaped defects and three hemispherical defects without additional (secondary) damage. This estimation shows that in the case of a complex-shaped defect, the equivalent defect model has an error of 14.5 %, which is 6.5 % greater than in the case of the hemispherical defects without secondary damages at the bottom.
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Naumenko, E. A., O. V. Rozhkova, and I. A. Kovaleva. "Comprehensive study of characteristic signs of defects detected during magnetic powder control at the final stage of production of seamless hot‑rolled pipes." Litiyo i Metallurgiya (FOUNDRY PRODUCTION AND METALLURGY), no. 1 (March 13, 2023): 69–72. http://dx.doi.org/10.21122/1683-6065-2023-1-69-72.
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Defects on the outer surface of seamless hot‑rolled steel pipes are formed both as a result of the defects’ transformation in the surface and macrostructure of the initial workpiece, and due to non‑compliance with the rolling technology. Timely detection of defects and elimination of the causes of their formation, allows you to get high‑quality products with high operational reliability. Detection of violations of technology, control of the technological process, carrying out metallographic studies allow classifying defects and establishing the nature and causes of their formation.The article presents the results of a metallographic study of a defect on the outer surface of a hot‑rolled seamless pipe. The genetic and morphological signs of the defect were determined. Descriptions of the appearance of the defect, the microstructure in the defect zone are given. A comparative analysis of the defect detected during magnetic powder control with defects on experimental pipe blanks with artificial defects was carried out. Based on the data obtained, the causes of the defect formation are determined, its classification is given.
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Koh, Jason L., Kevin C. Jacob, Rohan Kulkarni, Zachary Vasilion, and Farid M. L. Amirouche. "Consequences of Progressive Full-Thickness Focal Chondral Defects Involving the Medial and Lateral Femoral Condyles After Meniscectomy: A Biomechanical Study Using a Goat Model." Orthopaedic Journal of Sports Medicine 10, no. 3 (March 1, 2022): 232596712210785. http://dx.doi.org/10.1177/23259671221078598.
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Background: Full-thickness chondral defects alter tibiofemoral joint homeostasis and, if left untreated, have the potential to progress to osteoarthritis. Purpose: To assess the effects of isolated and dual full-thickness chondral defect size and location on the biomechanical properties of the lateral femoral condyle (LFC) and medial femoral condyle (MFC) during dynamic knee flexion in goat knees without menisci. Methods: In 12 goat knees, we created progressively increasing full-thickness circular chondral defects (3-, 5-, and 7.5-mm diameter) in the weightbearing contact area of flexion and extension in the MFC, the LFC, or both. Each knee was fixed into a custom steel frame and attached to a motor with sensors inserted intra-articularly. For each testing condition, the knee was loaded to 100 N and underwent a dynamic range of motion between 90° of flexion and 30° of extension. The following parameters were collected: contact area, contact pressure, contact force, peak area, and peak pressure. Study Design: Controlled laboratory study. Results: The peak pressure at the defect rim of the MFC at full extension increased by 51.51% from no defect (1.887 MPa) to a 7.5-mm defect (2.859 MPa) ( P < .001), and the peak pressure at the defect rim of the LFC at full extension increased by 139.14% from no defect (1.704 MPa) to a 7.5-mm defect (4.075 MPa) ( P < .001). The peak pressures for LFC defects at all 3 diameters were significantly greater when compared with dual defects consisting of increasing LFC defect diameter and constant MFC defect diameter ( P < .001 for all). Conclusion: Extremely large increases in peak pressure were seen at the rim of articular cartilage defects when evaluated under dynamic loading conditions. Isolated LFC defects experienced a greater increase in defect rim stress concentrations when compared with isolated MFC defects for equivalent increases in defect size. Defect size played a significant role independent of location for peak pressures on the MFC and LFC. Clinical Relevance: Significant rim-loading effects increase with defect size under dynamic loading and may result in increasingly rapid progression of articular cartilage lesions. Within the context of this goat model, findings suggest that lateral compartment chondral lesions are more likely to progress than medial compartment lesions of equivalent size.
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Lin, Horng-Horng, Harshad Kumar Dandage, Keh-Moh Lin, You-Teh Lin, and Yeou-Jiunn Chen. "Efficient Cell Segmentation from Electroluminescent Images of Single-Crystalline Silicon Photovoltaic Modules and Cell-Based Defect Identification Using Deep Learning with Pseudo-Colorization." Sensors 21, no. 13 (June 23, 2021): 4292. http://dx.doi.org/10.3390/s21134292.
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Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate the effectiveness of solar PV modules, manufacturing defects are required to be identified. Conventional defect inspection in industries mainly depends on manual defect inspection by highly skilled inspectors, which may still give inconsistent, subjective identification results. In order to automatize the visual defect inspection process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based defect detection system with pseudo-colorization of defects is designed in this paper. High-resolution Electroluminescence (EL) images of single-crystalline silicon (sc-Si) solar PV modules are used in our study for the detection of defects and their quality inspection. Firstly, an automatic cell segmentation methodology is developed to extract cells from an EL image. Secondly, defect detection can be actualized by CNN-based defect detector and can be visualized with pseudo-colors. We used contour tracing to accurately localize the panel region and a probabilistic Hough transform to identify gridlines and busbars on the extracted panel region for cell segmentation. A cell-based defect identification system was developed using state-of-the-art deep learning in CNNs. The detected defects are imposed with pseudo-colors for enhancing defect visualization using K-means clustering. Our automatic cell segmentation methodology can segment cells from an EL image in about 2.71 s. The average segmentation errors along the x-direction and y-direction are only 1.6 pixels and 1.4 pixels, respectively. The defect detection approach on segmented cells achieves 99.8% accuracy. Along with defect detection, the defect regions on a cell are furnished with pseudo-colors to enhance the visualization.
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Meng, Yunji, Renxia Ning, Kun Ma, Zheng Jiao, Haijiang Lv, and Youwen Liu. "Defect solitons supported by nonlinear fractional Schrödinger equation with a defective lattice." Journal of Nonlinear Optical Physics & Materials 28, no. 02 (June 2019): 1950021. http://dx.doi.org/10.1142/s0218863519500218.
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We investigate numerically the existence and stability of defect solitons in nonlinear fractional Schrödinger equation. For positive defects, defect solitons are only existent in the semi-infinite gap and are stable in their whole existence domain irrespective of Lévy index. For moderate deep defects, defect solitons are existent in both the semi-infinite gap and first gap, and their instability domains occur in the low-power region of the semi-infinite gap. While for deep enough defects, stable defect solitons can be found in the second gap. Increasing the strength of defect (or Lévy index) will narrow (or broaden) the existence and stability domains.
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Guo, Ling, Koji Kamei, Kenji Momose, and Hiroshi Osawa. "Evaluation and Reduction of Epitaxial Wafer Defects Resulting from Carbon-Inclusion Defects in 4H-SiC Substrate." Materials Science Forum 897 (May 2017): 39–42. http://dx.doi.org/10.4028/www.scientific.net/msf.897.39.
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In this study, we investigated the epitaxial surface defects resulting from the carbon-inclusion defects in 4H-SiC substrate. Most carbon-inclusion defects developed into one of three types of epitaxial surface defects under normal epitaxial growth conditions. Among them, we found a regular hexagonal pit by high-resolution microscopy, which we regarded as a large-pit defect, and which had an adverse impact on the reverse electrical characteristics of Schottky barrier diodes. Conversion of a carbon-inclusion defect to a large-pit defect or a triangular defect could be reduced by reducing the C/Si ratio.
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Tri Basuki, Rahmat, and Uly Amrina. "Rahmat Tri Basuki, Uly Amrina." Go-Integratif : Jurnal Teknik Sistem dan Industri 3, no. 02 (November 30, 2022): 87–97. http://dx.doi.org/10.35261/gijtsi.v3i02.6942.
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PT Bumimulia Indah Lestari found defects in the oil bottle packaging products it produces, which include perforated bottles, black spots on bottles, and defects on labels. The type of defect on the bottle label is the highest defect in the period from July to December 2021 compared to other defects. This research is focused on the problem of defects in the inverted label as the dominant defect of the entire defect label. Researchers use the DMAIC method to solve these problems. The improvement resulting from the DMAIC method is the manufacture of a jig tool called Jig Go No Go which aims to reduce the number of defects and increase productivity in bottle products. The implementation of the jig can reduce the defect label as a whole from 5.8% to 3.3% and the sigma value increases from 2.488 to 2.493.
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Yang, R. S., C. X. Ding, L. Y. Yang, P. Xu, and C. Chen. "Hole Defects Affect the Dynamic Fracture Behavior of Nearby Running Cracks." Shock and Vibration 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/5894356.
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Effects of defects on the dynamic fracture behavior of engineering materials cannot be neglected. Using the experimental system of digital laser dynamic caustics, the effects of defects on the dynamic fracture behavior of nearby running cracks are studied. When running cracks propagate near to defects, the crack path deflects toward the defect; the degree of deflection is greater for larger defect diameters. When the running crack propagates away from the defect, the degree of deflection gradually reduces and the original crack path is restored. The intersection between the caustic spot and the defect is the direct cause of the running crack deflection; the intersection area determines the degree of deflection. In addition, the defect locally inhibits the dynamic stress intensity factor of running cracks when they propagate toward the defect and locally promotes the dynamic stress intensity factor of running cracks when they propagate away from the defect.
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CHANG, CHING-PAO. "INTEGRATING ACTION-BASED DEFECT PREDICTION TO PROVIDE RECOMMENDATIONS FOR DEFECT ACTION CORRECTION." International Journal of Software Engineering and Knowledge Engineering 23, no. 02 (March 2013): 147–72. http://dx.doi.org/10.1142/s0218194013500022.
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Reducing software defects is an essential activity for Software Process Improvement. The Action-Based Defect Prediction (ABDP) approach fragments the software process into actions, and builds software defect prediction models using data collected from the execution of actions and reported defects. Though the ABDP approach can be applied to predict possible defects in subsequent actions, the efficiency of corrections is dependent on the skill and knowledge of the stakeholders. To address this problem, this study proposes the Action Correction Recommendation (ACR) model to provide recommendations for action correction, using the Negative Association Rule mining technique. In addition to applying the association rule mining technique to build a High Defect Prediction Model (HDPM) to identify high defect action, the ACR builds a Low Defect Prediction Model (LDPM). For a submitted action, each HDPM rule used to predict the action as a high defect action and the LDPM rules are analyzed using negative association rule mining to spot the rule items with different characteristics in HDPM and LDPM rules. This information not only identifies the attributes required for corrections, but also provides a range (or a value) to facilitate the high defect action corrections. This study applies the ACR approach to a business software project to validate the efficiency of the proposed approach. The results show that the recommendations obtained can be applied to decrease software defect removal efforts.
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Khoury, Muin J., José F. Cordero, Joseph Mulinare, and John M. Opitz. "Selected Midline Defect Associations: A Population Study." Pediatrics 84, no. 2 (August 1, 1989): 266–72. http://dx.doi.org/10.1542/peds.84.2.266.
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Using data from the population-based Metropolitan Atlanta Congenital Defects Program, the association of seven relatively common and easily ascertainable groups of midline defects was studied. These defects were neural tube defects (575 patients), oral clefts (633 patients), omphalocele (141 patients), esophageal atresia/tracheoesophageal fistula (88 patients), imperforate anus (151 patients), conotruncal heart defects (289 patients), and diaphragmatic hernia (75 patients). Known syndromes were excluded from the analysis. Of 1743 infants with at least one midline defect, 86 (4.9%) had at least a second midline defect, and 9 (0.5%) had two additional midline defects. Pairwise analysis of the seven defects shows that, although most midline defects tend to be statistically associated with other midline defects, specific combinations of midline defects are seen. For example, neural tube defects are more strongly associated with cleft lip with or without cleft palate than with cleft palate alone; imperforate anus is more strongly associated with spina bifida than with anencephaly or encephalocele. Moreover, some combinations of defects are not observed (eg, neural tube defect and conotruncal heart defect, clefts and diaphragmatic hernia, omphalocele and esophageal atresia/tracheoesophageal fistula). These data point to the need for further refinement in the study of the association of midline defects in terms of embryologic and pathogenetic mechanisms because most midline defects tend to occur as an isolated defect, some midline defects occur with nonmidline defects (such as limb defects), and specific associations among midline defects are observed.
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Xiao, Zhong Yin, Jian Xiang Wen, Wen Yun Luo, Wen Kai Wu, Ren Xiang Gong, Jian Chong Yin, and Ting Yun Wang. "Formation of Thermally Induced Defects in Silica Optical Material." Advanced Materials Research 853 (December 2013): 62–67. http://dx.doi.org/10.4028/www.scientific.net/amr.853.62.
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Characteristics of silica optical material largely depend on its thermal history. In this paper, formation of thermally induced defects in silica optical material is studied. The formation process of defect is analyzed in detail. The results show that there is an obvious difference in defect formation induced by heating treatment when the composition of silica optical material changes. Defect formation mainly displays as the produce process when the initial defects of the silica material are zero. However, defect formation expresses as the produce and annealing process when the initial defects of the silica material are not zero. The initial defect concentration can be decreased significantly when the silica material is heated in high temperature. At the same time, the new defect is also produced. These theoretic results are consistent with the previous experimental ones.
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Kersemans, Mathias, Erik Verboven, Joost Segers, Saeid Hedayatrasa, and Wim Van Paepegem. "Non-Destructive Testing of Composites by Ultrasound, Local Defect Resonance and Thermography." Proceedings 2, no. 8 (July 30, 2018): 554. http://dx.doi.org/10.3390/icem18-05464.
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Different non-destructive testing techniques have been evaluated for detecting and assessing damage in carbon fiber reinforced plastics: (i) ultrasonic C-scan, (ii) local defect resonance of front/back surface and (iii) lock-in infrared thermography in reflection. Both artificial defects (flat bottom holes and inserts) and impact damage (barely visible impact damage) have been considered. The ultrasonic C-scans in reflection shows good performance in detecting the defects and in assessing actual defect parameters (e.g., size and depth), but it requires long scanning procedures and water coupling. The local defect resonance technique shows acceptable defect detectability, but has difficulty in extracting actual defect parameters without a priori knowledge. The thermographic inspection is by far the fastest technique, and shows good detectability of shallow defects (depth < 2 mm). Lateral sizing of shallow damage is also possible. The inspection of deeper defects (depth > 3–4 mm) in reflection is problematic and requires advanced post-processing approaches in order to improve the defect contrast to detectable limits.
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Jing, Yan Hong, Hong Xing Lu, Da Quan Li, and Qiang Zhu. "Analysis on Internal Defect of 319S Aluminum Alloy Impeller by Semi-Solid Thioxcasting." Materials Science Forum 850 (March 2016): 219–25. http://dx.doi.org/10.4028/www.scientific.net/msf.850.219.
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In the present investigation a batch of impellers made of 319S aluminum alloy with about 300 pieces and produced by semi-solid thixocasting process were subjected the ultrasonic testing (UT). The experimental results revealed that the equivalent size of the defects in the impellers was not more than φ0.4mm FBH+12dB. And there were two main types of defects in 12 mm depth area from the machined surface, where defect was apt to form. One type was single defect and the other was intensive defect. Moreover, other nondestructive testing (NDT) was used to test some impellers containing typical defect, and the result suggests that UT was more sensitive than x-ray testing. The defects existed in the impellers were investigated by Optical Microscope (OM) and Scanning Electron Microscope (SEM) equipped with Energy Dispersive Spectrometer (EDS). The observation showed that the both types of defects existed in eutectic zone. The single defect derived from billet and the intensive defect came from die casting process.
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Jóźwik, Wojciech, and Tomasz Samborski. "Influence of Geometrical Features of Material Defects on the Identification Level by the Eddy Current Method." Solid State Phenomena 237 (August 2015): 136–41. http://dx.doi.org/10.4028/www.scientific.net/ssp.237.136.
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The article presents the results of the influence of geometrical features of defects in materials on the level of identification by the eddy current method. The study involved the inner ring of the tapered roller bearing. Four test defects, located at a constant distance from the inner surface, and a subsurface marker defect were performed in the treadmill of the tested ring. The test defects had a constant cross-sectional area in a perpendicular direction to the surface of the eddy current head. The geometrical features of each defect were the following: shape, the perimeter of the defect projected onto the surface of the ring, and the width and height of the defect projected on the face of the measuring head. The study involved an inner surface (subsurface defect detection) and external surface (the study of surface defects). It has been shown that the shape of the defect affects the level of detection using the eddy current method.
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Jeon, Su-Hee, Young Woo Song, Jae-Kook Cha, Jeong-Won Paik, Sang-Sun Han, and Seong-Ho Choi. "Scanning Electron Microscopic Evaluation of the Internal Fit Accuracy of 3D-Printed Biphasic Calcium Phosphate Block: An Ex Vivo Pilot Study." Materials 14, no. 6 (March 22, 2021): 1557. http://dx.doi.org/10.3390/ma14061557.
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The aim of this study was to assess the internal fit accuracy of a three-dimensional (3D)-printed biphasic calcium phosphate (BCP) block compared with a 3D-milled poly methyl methacrylate (PMMA) block by scanning electron microscope (SEM) analysis. In a total of 20 porcine rib bones, two different types of defects having two adjacent walls and a floor were produced: a defect with a flat floor (flat defect; N = 10) and a defect with a concave floor (curved defect; N = 10). Each defect was grafted with either the 3D-printed BCP block or the 3D-milled PMMA block fabricated following the computer aided design. The defects were then cut cross-sectionally and evaluated under the SEM. The extents of internal contact and gap were measured and statistically analyzed (p < 0.05). All blocks in both BCP and PMMA groups were successfully fit to the flat and curved defects. The internal contact ratio was significantly higher in the BCP group (flat defect: 0.47 ± 0.10; curved defect: 0.29 ± 0.05) compared with the PMMA group (flat defect: 0.21 ± 0.13; curved defect: 0.17 ± 0.04; p < 0.05). The internal gap area was similar between the two groups regardless of the defect types (p > 0.05). The internal fit accuracy of the 3D-printed BCP block was reliable in both the flat and curved defects when compared with the accuracy of the 3D-milled PMMA block.
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Wei, Jinfeng, Guangnan Xu, Guolin Liu, Jinwei Guo, Wang Zhu, and Zengsheng Ma. "Quantitative Characterization of Interfacial Defects in Thermal Barrier Coatings by Long Pulse Thermography." Coatings 12, no. 12 (November 26, 2022): 1829. http://dx.doi.org/10.3390/coatings12121829.
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The non-contact long pulse thermography method is commonly used to detect the defects in thermal barrier coatings (TBCs). The profile of interfacial defect in TBCs can be monitored by infrared camera under the irradiation of the excitation source. Unfortunately, the defect profile is always blurry due to heat diffusion between the defect area and the intact area. It is difficult to quantify the size of defect size in TBCs. In this work, combined with derived one-dimensional heat conduction analytical model, a non-contact long pulse thermography (LPT) method is applied to quantitatively investigate the interface defects in TBCs. Principal component analysis (PCA) and background subtraction method are used to improve the contrast of the defect profile in collected thermal images. By fitting the results between the profile of the interface defect in thermal images and the predicted shape of the model, the interface defect size can be determined. Furthermore, a simple extension of proposed method for interfacial defects with irregular shape is presented. The predicted errors for round defect with diameters of 3 mm, 5 mm and 7 mm are roughly distributed in the range of 3%~6%, which are not affected by the defect diameter.
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Kamei, Koji, Ling Guo, Kenji Momose, and Hitoshi Osawa. "Structure of Straight-Line Defect and its Effect on the Electrical Properties of Schottky Barrier Diodes." Materials Science Forum 858 (May 2016): 213–16. http://dx.doi.org/10.4028/www.scientific.net/msf.858.213.
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We have investigated the “straight-line defect,” which has not been classified separately and is quite similar to the carrot defect. We found that the straight-line defect differed structurally from the carrot defect. The presence of a particle on the substrate-epi layer interface seemed to be the cause of the defect; a layer of poly-type (3C-SiC) extended from the particle to the epi-layer surface. The straight-line defect likely resulted from shape change from the 3C-SiC triangular defect. This change in shape from triangular to straight-line defects depended on the C/Si ratio. To investigate the electrical characteristics, we fabricated a Schottky barrier diode (SBD) structure on a silicon carbide (SiC) epi wafer. With application of a high voltage, destruction occurred on both the upstream and the downstream side of the step flow of straight-line defects in the reverse voltage test. This reverse direction characteristic differed from that observed with triangular defects.
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Zhang, Haigang, Dong Wang, Zhibin Chen, and Ronghui Pan. "Adaptive visual detection of industrial product defects." PeerJ Computer Science 9 (March 15, 2023): e1264. http://dx.doi.org/10.7717/peerj-cs.1264.
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Visual inspection of the appearance defects on industrial products has always been a research hotspot pursued by industry and academia. Due to the lack of samples in the industrial defect dataset and the serious class imbalance, deep learning technology cannot be directly applied to industrial defect visual inspection to meet the real application needs. Transfer learning is a good choice to deal with insufficient samples. However, cross-dataset bias is unavoidable during simple knowledge transfer. We noticed that the appearance defects of industrial products are similar, and most defects can be classified as stains or texture jumps, which provides a research basis for building a universal and adaptive industrial defect detection model. In this article, based on the idea of model-agnostic meta-learning (MAML), we propose an adaptive industrial defect detection model through learning from multiple known industrial defect datasets and then transfer it to the novel anomaly detection tasks. In addition, the Siamese network is used to extract differential features to minimize the influence of defect types on model generalization, and can also highlight defect features and improve model detection performance. At the same time, we add a coordinate attention mechanism to the model, which realizes the feature enhancement of the region of interest in terms of two coordinate dimensions. In the simulation experiments, we construct and publish a visual defect dataset of injection molded bottle cups, termed BC defects, which can complement existing industrial defect visual data benchmarks. Simulation results based on BC defects dataset and other public datasets have demonstrated the effectiveness of the proposed general visual detection model for industrial defects. The dataset and code are available at https://github.com/zhg-SZPT/MeDetection.
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Lee, Y. K., Young Pyo Kim, M. W. Moon, Woong Ho Bang, Kyu Hwan Oh, and Woo Sik Kim. "The Prediction of Failure Pressure of Gas Pipeline with Multi Corroded Region." Materials Science Forum 475-479 (January 2005): 3323–26. http://dx.doi.org/10.4028/www.scientific.net/msf.475-479.3323.
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The failure assessment for the defects in multiple corroded region has been considered with the real-size pipeline burst tests and the associated Finite Element Method. The corroded gas pipeline made of X65 steel with various types of artificially machined pits has been used for a number of series of burst tests on gas pipeline. The failure pressures for the designed multiple corroded defect on gas pipelines have been measured by using in-situ burst testing and classified with respect to each designed defect sizes - length, width and depth - and distance between defects. The result from the experiments has been modeled and compared with Finite Element Method. As the result of FEM simulation, the failure pressure in multiple defects is lower than that in single defect, and closer to failure pressure in single defect of total length of defects in multiple defects as the distance between each defect is closer.
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Jo, Soo-Ho, and Byeng D. Youn. "A Phononic Crystal with Differently Configured Double Defects for Broadband Elastic Wave Energy Localization and Harvesting." Crystals 11, no. 6 (June 5, 2021): 643. http://dx.doi.org/10.3390/cryst11060643.
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Several previous studies have been dedicated to incorporating double defect modes of a phononic crystal (PnC) into piezoelectric energy harvesting (PEH) systems to broaden the bandwidth. However, these prior studies are limited to examining an identical configuration of the double defects. Therefore, this paper aims to propose a new design concept for PnCs that examines differently configured double defects for broadband elastic wave energy localization and harvesting. For example, a square-pillar-type unit cell is considered and a defect is considered to be a structure where one piezoelectric patch is bonded to a host square lattice in the absence of a pillar. When the double defects introduced in a PnC are sufficiently distant from each other to implement decoupling behaviors, each defect oscillates like a single independent defect. Here, by differentiating the geometric dimensions of two piezoelectric patches, the defects’ dissimilar equivalent inertia and stiffness contribute to individually manipulating defect bands that correspond to each defect. Hence, with adequately designed piezoelectric patches that consider both the piezoelectric effects on shift patterns of defect bands and the characteristics for the output electric power obtained from a single-defect case, we can successfully localize and harvest the elastic wave energy transferred in broadband frequencies.
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Goyal, Anuj, Kiran Mathew, Richard G. Hennig, Aleksandr Chernatynskiy, Christopher R. Stanek, Samuel T. Murphy, David A. Andersson, Simon R. Phillpot, and Blas P. Uberuaga. "The Conundrum of Relaxation Volumes in First-Principles Calculations of Charged Defects in UO2." Applied Sciences 9, no. 24 (December 4, 2019): 5276. http://dx.doi.org/10.3390/app9245276.
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The defect relaxation volumes obtained from density-functional theory (DFT) calculations of charged vacancies and interstitials are much larger than their neutral counterparts, seemingly unphysically large. We focus on UO2 as our primary material of interest, but also consider Si and GaAs to reveal the generality of our results. In this work, we investigate the possible reasons for this and revisit the methods that address the calculation of charged defects in periodic DFT. We probe the dependence of the proposed energy corrections to charged defect formation energies on relaxation volumes and find that corrections such as potential alignment remain ambiguous with regards to its contribution to the charged defect relaxation volume. We also investigate the volume for the net neutral defect reactions comprising individual charged defects, and find that the aggregate formation volumes have reasonable magnitudes. This work highlights the issue that, as is well-known for defect formation energies, the defect formation volumes depend on the choice of reservoir. We show that considering the change in volume of the electron reservoir in the formation reaction of the charged defects, analogous to how volumes of atoms are accounted for in defect formation volumes, can renormalize the formation volumes of charged defects such that they are comparable to neutral defects. This approach enables the description of the elastic properties of isolated charged defects within an overall neutral material.
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Liu, Jie, Cangming Liang, Jintao Feng, Anhong Xiao, Hui Zeng, Qujin Wu, and Tonglan Yu. "A Multi-Feature Fusion-Based Automatic Detection Method for High-Severity Defects." Electronics 12, no. 14 (July 14, 2023): 3075. http://dx.doi.org/10.3390/electronics12143075.
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It is crucial to detect high-severity defects, such as memory leaks that can result in system crashes or severe resource depletion, in order to reduce software development costs and ensure software quality and reliability. The primary cause of high-severity defects is usually resource scheduling errors, and in the program source code, these defects have contextual features that require defect context to confirm their existence. In the context of utilizing machine learning methods for defect automatic confirmation, the single-feature label method cannot achieve high-precision defect confirmation results for high-severity defects. Therefore, a multi-feature fusion defect automatic confirmation method is proposed. The label generation method solves the dimensionality disaster problem caused by multi-feature fusion by fusing features with strong correlations, improving the classifier’s performance. This method extracts node features and basic path features from the program dependency graph and designs high-severity contextual defect confirmation labels combined with contextual features. Finally, an optimized Support Vector Machine is used to train the automatic detection model for high-severity defects. This study uses open-source programs to manually implant defects for high-severity defect confirmation verification. The experimental results show that compared with existing methods, this model significantly improves the efficiency of confirming high-severity defects.
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He, Min, Qinnan Zhao, Huanhuan Gao, Xinying Zhang, and Qin Zhao. "Image Segmentation of a Sewer Based on Deep Learning." Sustainability 14, no. 11 (May 28, 2022): 6634. http://dx.doi.org/10.3390/su14116634.
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An accurate assessment of the type and extent of sewer damage is an important prerequisite for maintenance and repair. At present, distinguishing drainage pipe defect types in the engineering field mainly relies on the human eye, which is time consuming, labor intensive, and subjective. Some studies have used deep learning to classify the types of pipe defects, but this method can only identify one main pipe defect. However, sometimes a combination of defects, such as corrosion and precipitation on a section of pipe wall, can be classified as one category by picture classification, which is significantly different from the reality. Furthermore, the deep learning method for defect classification is unable to pinpoint the precise location and severity of a defect or estimate the number of flaws and the cost of maintenance and repair. Therefore, an image segmentation method based on deep convolutional neural networks is proposed to achieve pixel-level image segmentation of defect regions while classifying pipe defects. Compared with the deep learning network for defect classification, it can segment a variety of defects and reduce the number of samples, which is convenient for defect measurement. First, the image defect locations of seven typical defects were manually labeled to create the dataset. Then, a model based on the SegNet network was used to label defect areas automatically in an image. The pipeline image dataset was used to test the previously trained model using the CamVid dataset. Finally, the model was applied to drainage pipe network images that were provided by periscope and closed-circuit television inspection cameras, and the pixel accuracy of image segmentation reached 80%. From the results, it can be concluded that image segmentation and annotation technology based on deep learning is applicable to sewer defect detection. The identification results of pipeline defects were accurate. The SegNet model is a reliable method for image analysis of pipeline defects, which can accurately evaluate the type and degree of sewer damage.
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Jian, Chuan Xia, Jian Gao, and Xin Chen. "A Review of TFT-LCD Panel Defect Detection Methods." Advanced Materials Research 734-737 (August 2013): 2898–902. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.2898.
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TFT-LCD panel defect detection has been one of the difficulties in this field because of fuzzy defect boundary, low contrast between defects and background, and low detection speed. The structure of TFT-LCD panels and classification are introduced. Through the analysis of panel defect features, current detection methods for the TFT-LCD panel defects are reviewed. The key technologies of feature extraction and defect classification are analyzed in the defect image recognition of TFT-LCD panel. Meanwhile the methods of fuzzy boundary defect segmentation, image subtraction and image filtering are also discussed. Finally, the characteristics and advantages of these detection methods are concluded, and several key issues for the TFT-LCD defect detection have been proposed for future development.
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BERRY, B. W., and E. C. GREEN. "Inspection Systems and Mechanical Removal Systems for Bone and Cartilage Particles in Ground Beef Patties." Journal of Food Protection 51, no. 5 (May 1, 1988): 369–72. http://dx.doi.org/10.4315/0362-028x-51.5.369.
Full textAbstract:
Ground beef patties were processed from boneless beef which was subjected to two different inspection systems for bone and cartilage defects. One system permitted a higher (“high”) level of defects (USDA Food Safety and Inspection Service, Meat and Poultry Inspection Requirements), while the other system (USDA PP-B-2120 Federal Purchasing Specification) permitted only a lower (“low”) level of defects. Before formation into patties, the ground beef was subjected to three processing systems for defect removal (none, Weiler Bone Collector System, Speco Spiral Groove Plate System). A sensory approach (teeth and tongue) for detecting defects with cooked patty samples revealed more bone and cartilage defects in the “high” than the “low” formulation regardless of defect removal system. While the defect removal systems reduced the levels of detected defects in the “high” formulation, neither system produced patties with defect levels achieved through inspection procedures required to produce “low” levels of these defects. However, it appears that much of the bone remaining as a defect in boneless beef is reduced in size during grinding so as to be undetectable by sensory approaches.
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Pond, R. C. "TEM studies of line defects in interfaces." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 586–87. http://dx.doi.org/10.1017/s0424820100104996.
Full textAbstract:
Line defects are ubiquitious features in interfaces, and have important structural and mechanistic role. Recently, a crystallographic theory of such defects has been presented which appears to offer a comprehensive framework for their classification. The object of the present paper is firstly to outline the characterisation and classification of defects according to this treatment. Secondly, we illustrate examples of defects in the distinctive classes observed using tern, and discuss the various imaging techniques which have been employed.In the absence of a rigorous treatment of line defects in single crystals and interfaces, which would require the development of a discrete field theory, approximate methods of defect characterisation are used. The most popular method involves mapping a contour, initially constructed around a defect of interest, into a reference space. For defeats in single crystals this Burgers circuit method, introduced by Frank, is very helpful, but suffers from certain procedural inconveniences in the case of interfacial defects.
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Chen, Shuguang, Jingyang Gao, Di Zhao, Pinjie Xu, and Tian Zhang. "Detection of Chip Layered Defects Based on Dual Focus Mechanism." Journal of Physics: Conference Series 2216, no. 1 (March 1, 2022): 012091. http://dx.doi.org/10.1088/1742-6596/2216/1/012091.
Full textAbstract:
Abstract Chip layering defects affect the performance of chips and lead to the failure of chips, so chip layering defects detection is an important step in the quality acceptance of chip production. Chip layering defects, which are characterized by insignificant color change in defect area, small defect area and difficult localization, bring challenges to traditional detection. In recent years, deep learning has shown its powerful ability to solve complex problems in computer vision. In this paper, semantic segmentation method is used to study the problem of chip hierarchical defect detection. Dual focus mechanism first applies whiteboard network structure to identify the true hierarchical area. Afterwards the defective layer area and the original map, the layered defect is recognized in the whiteboard attention. Since the contrast of the layered defect is not obvious, the precise layered defect tag extraction is another important factor affecting network performance. Based on the fuzzy-c-mean clustering algorithm and expert acceptance principle, obtaining the precise layered defect label, the practicality of this method is further enhanced. The effectiveness of the method for detecting the chip layering defects is verified by testing the chip image provided by Huawei.
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Jadi, Supri, and A. Setiadi. "Structural Shifting and Electronic Properties of Stone-Wales Defect in Armchair Edge (5,5) Carbon Nanotube." Advanced Materials Research 772 (September 2013): 380–85. http://dx.doi.org/10.4028/www.scientific.net/amr.772.380.
Full textAbstract:
Stone Wales (SW) defect is one type of topological defect on the CNT, in this study we performed first principles calculations of SW defects in armchair edge (5,5) carbon nanotube (CNT) by the density functional theory (DFT). Two different defects were studied such as longitudinal and circumference types. Our calculation results show that a longitudinal SW defect is more stable than circumference SW defect. However barrier energy as parameter to control the SW defect in CNT was studied, in calculation we applied Nudge Elastic Band (NEB) method to find minimum energy path (MEP) and barrier energy for SW defect transitions. The result shows that barrier energy of circumference SW defect is lower than another one. We also found that in the case of circumference SW defect, armchair edge (5,5) CNT become semiconductor with the band gap of 0.0544 eV.
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Liang, Yingjing, Hongfa Qin, Jianzhang Huang, Sha Huan, and David Hui. "Mechanical properties of boron nitride sheet with randomly distributed vacancy defects." Nanotechnology Reviews 8, no. 1 (November 12, 2019): 210–17. http://dx.doi.org/10.1515/ntrev-2019-0019.
Full textAbstract:
Abstract Defects and temperature effects on the mechanical properties of hexagonal boron nitride sheet (h-BN) containing randomly distributed defects are investigated by molecular dynamics simulations and the reasons of the results are discussed. Results show that defect deteriorate the mechanical performance of BNNS. The mechanical properties are reduced by increasing percentage of vacancy defects including fracture strength, fracture strain and Young’s modulus. Simulations also indicate that the mechanical properties decrease with the temperature increasing. Moreover, defects affect the stable configuration at high temperature. With the percentage of defect increases the nanostructures become more and more unstable. Positions of the defect influent the mechanical properties. The higher the temperature and the percentage of defect are, the stronger the position of the randomly distributed defect affects the mechanical properties. The study provides a theoretical basis for the preparation and performance optimization of BNNSs.