Relevant bibliographies by topics / Recognizing complete classifications

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Academic literature on the topic 'Recognizing complete classifications'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Recognizing complete classifications"

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Rocha, T. Coelho, J. Cunha, S. Torres, and A. Lopes. "The universe of brief psychosis." European Psychiatry 64, S1 (2021): S514—S515. http://dx.doi.org/10.1192/j.eurpsy.2021.1377.

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IntroductionNowadays, ‘Acute and transient psychotic disorders’ in ICD-10 and ‘Brief psychotic disorders’ in DSM-5 are both classifications of the same clinical entity. Over the years, several concepts have been formulated to define the same syndrome.ObjectivesTo explore the historical evolution of brief psychotic disorders and relate them to current nosologies.MethodsLiterature review, using the most relevant papers, with the keywords “brief psychosis”, “bouffée délirante”, “cycloid psychosis”, “psychogenic psychosis”, “atypical psychosis” and “holodysphrenia”.ResultsInitially, in 1896, Kahlb
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Wang, Yu, Quanjun Song, Tingting Ma, Yong Chen, Hao Li, and Rongkai Liu. "Transformation classification of human squat/sit-to-stand based on multichannel information fusion." International Journal of Advanced Robotic Systems 19, no. 4 (2022): 172988062211037. http://dx.doi.org/10.1177/17298806221103708.

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In existing rehabilitation training, research on the accuracy of recognizing completed actions has achieved good results; however, the reduction in the misjudgment rate in the action conversion process needs further research. This article proposes a multichannel information fusion method for the movement conversion process of squat/sit-to-stand, which can help online movement conversion classification during rehabilitation training. We collected a training dataset from a total of eight subjects performing three different motions, including half squat, full squat, and sitting, equipped with pla
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Kislitsyna, Maria Yurievna, and Yurii Nikolaevich Orlov. "Statistical analysis of the complete corpus of fiction in Russian and recognition of the author." Keldysh Institute Preprints, no. 17 (2024): 1–24. http://dx.doi.org/10.20948/prepr-2024-17.

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Statistics of reference trigrams for the complete corpus of literary texts in Russian, including translated foreign authors, have been collected. Distributions of distances from individual texts to standards are constructed. The nearest reference method for recognizing the author of the text has been tested. The error was determined by genres, subgroups of authors and by the corpus as a whole. A classification of errors has been carried out to develop a correction method.
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Kislitsyna, Maria Yurievna, and Yurii Nikolaevich Orlov. "The structure of errors in recognizing the author of the text by the trigram method." Keldysh Institute Preprints, no. 60 (2024): 1–24. http://dx.doi.org/10.20948/prepr-2024-60.

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Statistics of reference trigrams for the complete corpus of literary texts in Russian, including translated foreign authors, have been collected. Distributions of distances from individual texts to standards are constructed. The nearest reference method for recognizing the author of the text has been tested. The error was determined by genres, subgroups of authors and by the corpus as a whole. A classification of errors has been carried out to develop a correction method.
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BALA, J. W., and P. W. PACHOWICZ. "RECOGNIZING NOISY PATTERNS VIA ITERATIVE OPTIMIZATION AND MATCHING OF THEIR DESCRIPTIONS." International Journal of Pattern Recognition and Artificial Intelligence 06, no. 04 (1992): 513–37. http://dx.doi.org/10.1142/s0218001492000291.

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This paper presents an approach to the recognition of noisy patterns. We assume that learned concept descriptions contain noisy components. These descriptions can be optimized to gain better performance through the elimination of some less significant noisy components. Parametric control of such an optimization, however, is very difficult and a parameter value has to be found through the training process. This value can change over concept variations and time, and in consequence, it can decrease the system recognition effectiveness. We found that the classification decision can be based on the
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Leonardi, Matilde, Andrea Martinuzzi, Paolo Meucci, et al. "A Population Survey in Italy Based on the ICF Classification: Recognizing Persons with Severe Disability." Scientific World Journal 2012 (2012): 1–9. http://dx.doi.org/10.1100/2012/189097.

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Aim of this paper is to describe functioning of subjects with “severe disability” collected with a protocol based on the International Classification of Functioning, Disability, and Health. It included sections on body functions and structures (BF and BS), activities and participation (A&P), and environmental factors (EF). In A&P, performance without personal support (WPS) was added to standard capacity and performance. Persons with severe disability were those reporting a number of very severe/complete problems in BF or in A&P-capacity superior to mean + 1SD. Correlations between
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Yaqoub, Muntazir, and Dr Gurinder Kaur Sodhi. "Classification of Diabetic Retinopathy Disease Using Retina Images: A Review." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 2260–66. http://dx.doi.org/10.22214/ijraset.2022.48454.

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Abstract: Retinal lesions that impair vision are a typical symptom of diabetic retinopathy, result of diabetes mellitus. Blindness may develop if it is not detected in time. Tragically, there is no known cure for DR, and therapy only works to stop vision loss. DR diagnosis and treatment can significantly lower risk of eyesight loss. Contrary to computer-aided methods, physical examination in case of DR visual image acquisition through optometrists is time-, effort-, and premium and prone to error. Deep learning recently emerged as popular techniques in boosting expertise in number of fields, i
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Setiawan, Johan, Dita Amalia, and Iwan Prasetiawan. "Data Mining Techniques for Predictive Classification of Anemia Disease Subtypes." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 8, no. 1 (2024): 10–17. http://dx.doi.org/10.29207/resti.v8i1.5445.

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Anemia, characterized by insufficient red blood cells or reduced hemoglobin, hinders oxygen transport in the body. Understanding the different types of anemia is vital to tailor effective prevention and treatment. This research explores the role of data mining in predicting and classifying anemia types, focusing on complete blood count (CBC) and demographic data. Data mining is the key to building models that help healthcare professionals diagnose and treat anemia. Employing the cross-industry standard process for data mining (CRISP-DM), with its six phases, facilitates this effort. Our study
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Kong, Guanghui, Zhiyong Wang, Xiuchao Wan, and Fengjun Xue. "Automatic segmentation and recognition of red and white cells in stool microscopic images of human." E3S Web of Conferences 185 (2020): 03024. http://dx.doi.org/10.1051/e3sconf/202018503024.

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Aiming to solve the problem of low efficiency in manually recognizing the red and white cells in stool microscopic images, we propose an automatic segmentation method based on iterative corrosion with marker-controlled watershed segmentation and an automatic recognition method based on support vector machine (SVM) classification. The method first obtains saliency map of the images in HSI and Lab color spaces through saliency detection algorithm, then fuses the salient images to complete the initial segmentation. Next, we segment the red and white cells completely based on the initial segmentat
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Valentyn, Yesilevskyi, Tevyashev Andriy, and Koliadin Anton. "A method of air object recognition based on the normalized contour descriptors and a complex-valued neural network." Eastern-European Journal of Enterprise Technologies 6, no. 4(108) (2020): 48–57. https://doi.org/10.15587/1729-4061.2020.220035.

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This paper reports a study into the methods for recognizing the type of an air object on a digital image acquired from an air situation video monitoring system. A method has been proposed that is based on the application of a specific neural network, which solves the problem of categorizing multidimensional complex vectors of objects’ features based on complex calculations. In this case, a feature vector for recognizing the type of an air object is built on the basis of a Fourier transform for the sequence of coordinates of its two-dimensional contour. A technique has been proposed to tr
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Book chapters on the topic "Recognizing complete classifications"

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Bansal, Kanishk, and Amar Singh Rana. "Landmark Recognition Using Ensemble-Based Machine Learning Models." In Advances in Medical Technologies and Clinical Practice. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7188-0.ch005.

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Recognizing landmarks in images with machine learning is an excellent topic for research today. Landmark recognition is an important field in computer vision. In this field, we train the machine learning models to identify and recognize the closed distinctly distinguishable objects in a digital image. In general, if we consider a digital image to be a set of coordinates of different pixels, a landmark is said to be enclosed in that closed polygon formed by the pixels that may be considered as a distinct and distinguishable thing in one or the other sense. Landmark recognition is an important s
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Ye, Yunwen, Kumiyo Nakakoji, Yasuhiro Yamamoto, and Kouichi Kishida. "The Co-Evolution of Systems and Communities in Free and Open Source Software Development." In Free/Open Source Software Development. IGI Global, 2005. http://dx.doi.org/10.4018/978-1-59140-369-2.ch003.

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Because a Free and Open Source Software (F/OSS) project is unlikely to sustain a long-term success unless there is an associated community that provides the platform for developers, users, and user-turned-developers to collaborate with each other, understanding the well-observed phenomenon that F/OSS systems experience “natural product evolution” cannot be complete without understanding the structure and evolution of their associated communities. This chapter examines the structure of F/OSS communities and the co-evolution of F/OSS systems and communities based on a case study. Although F/OSS
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Ye, Yunwen, Kumiyo Nakakoji, Yasuhiro Yamamoto, and Kouichi Kishida. "The Co-Evolution of Systems and Communities in Free and Open Source Software Development." In Global Information Technologies. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-939-7.ch265.

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Because a Free and Open Source Software (F/OSS) project is unlikely to sustain a long-term success unless there is an associated community that provides the platform for developers, users, and user-turned-developers to collaborate with each other, understanding the well-observed phenomenon that F/OSS systems experience “natural product evolution” cannot be complete without understanding the structure and evolution of their associated communities. This chapter examines the structure of F/OSS communities and the co-evolution of F/OSS systems and communities based on a case study. Although F/OSS
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"Strategies for Restoring River Ecosystems: Sources of Variability and Uncertainty in Natural and Managed Systems." In Strategies for Restoring River Ecosystems: Sources of Variability and Uncertainty in Natural and Managed Systems, edited by G. R. PESS, T. J. BEECHIE, J. E. WILLIAMS, D. R. WHITALL, J. I. LANGE, and J. R. KLOCHAK. American Fisheries Society, 2003. http://dx.doi.org/10.47886/9781888569469.ch8.

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<em>Abstract</em>.—A major challenge in planning and executing aquatic ecosystem restoration strategies is the need to make decisions without complete understanding of ecosystems or processes affecting their conditions. Information-gathering tools such as stream classification systems, riparian-growth and wood-recruitment models, watershed assessments, historical reconstruction, and decision-support models can help reduce uncertainty in defining a path for aquatic restoration activities. We demonstrate how these tools can be used to systematically gather information for achieving i
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"Introduction." In Atypical Diabetes: Pathophysiology, Clinical Presentations, and Treatment Options. American Diabetes Association, 2018. http://dx.doi.org/10.2337/9781580406666.intro.

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Classification of diabetes includes a long list of common, rare, and not-so-rare conditions characterized by hyperglycemia of variable degrees. Whereas the majority of patients with diabetes are easily classified as having type 1 or type 2 diabetes, the other forms of diabetes, in aggregate, account for approximately 10% of diabetes cases. These cases may be grouped under the umbrella of rare forms of diabetes or “atypical diabetes.” Even though individually rare, these atypical types of diabetes are frequent enough that every practitioner is likely to encounter such cases in his or her practi
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Conference papers on the topic "Recognizing complete classifications"

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"Classification of families of DNA-recognizing protein domains based on structural features of DNA-protein complexes." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-176.

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Gao, Shuming, and Jami J. Shah. "Automatic Recognition of Interacting Machining Features Based on Minimal Condition Sub-Graph." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/cie-4277.

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Abstract This paper presents a new approach for automatic recognition of machining features from the B-Reps of the part. In this approach we combine the conventional graph based recognition method with the hint based feature recognition idea so as to efficiently handle feature interactions and provide alternative interpretations of interacting features. A Manufacturing Face Adjacency Graph proposed here is useful for improving the recognition of isolated features and effectively reducing the search space for virtual links, unifiable faces and features. Isolated (non-intersecting) features are
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Nenashev, V. A., and S. A. Nenashev. "Classification and Recognition of Ground Objects in the Stream of Radar Frames Based on a Neural Network Approach in the Forward Field of View of Airborne Radars of a Multi-position System." In 33rd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2023. http://dx.doi.org/10.20948/graphicon-2023-572-580.

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Classification and recognition of ground objects in the stream of radar frames based on a neural network approach in the forward field of view of the onboard radar of a multi-position system. This article discusses the features of effective classification and recognition of ground objects in the video stream of radar frames formed in the forward field of view of the on-board radar of a multi- position system. The issues of building spatially distributed systems for on-board radar automated monitoring of the earth's surface are covered, modern requirements for the resolution of radar frames are
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Nair, Aravind, Vivek Jaiswal, Olav Fyrileiv, et al. "A New Rigid Jumper VIV Response Model: JIP Development." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-19024.

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Abstract Recognizing the need to address the challenges associated with the VIV assessment of rigid jumpers, a joint industry project (JIP) was launched in December 2014. The JIP was based on the model test data supplied by ExxonMobil. Through the JIP study, measured responses from tow tests were used to develop new response curves for jumper systems and compared against the existing DNV GL-RP-F105 curves. This paper presents details of the validation of model test data; processing of test data for response curve development; classification and interpretation of jumper response and; the two ne
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Ge, Yuncheng, Yewei Huang, Ye Julei, Huazixi Zeng, Hechong Su, and Zengyao Yang. "DMGR: Divisible Multi-complex Gesture Recognition Based on Word Segmentation Processing." In 2024 AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2024 Hawaii Edition). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005654.

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In the realm of gesture recognition and computer algorithm optimization, traditional approaches have predominantly focused on recognizing isolated gestures. However, this paradigm proves inadequate when confronted with complex gestural sequences, resulting in cumbersome recognition processes and diminished accuracy. Contemporary human-computer interaction (HCI) applications often necessitate users to perform intricate series of gestures, rather than isolated movements. Consequently, there is a pressing need for systems capable of not only recognizing individual gestures but also accurately seg
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da Silva, Jonathan Cristovão Ferreira, Vicente José Peixoto de Amorim, Pedro Sebastião de Oliveira Lazaroni, Ricardo Augusto Rabelo Oliveira, and Mateus Coelho Silva. "Towards novel smart wearable sensors to classify subject-specific human walking activities." In Anais Estendidos do Simpósio Brasileiro de Engenharia de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sbesc_estendido.2022.228153.

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In this century, smart devices are increasingly present in our lives, such as at work, sports, or household chores. In this context, we have wearable devices that can help people with health monitoring or physical performance in sports activities. With the integration of artificial intelligence (AI), these wearable devices can identify injuries in athletes or care for the elderly in rehabilitation from human activity recognition (HAR). AI techniques are commonly applied for pattern recognition, such as image classification or HAR. In this context, we seek to develop a smart wearable device to
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Dinar, Mahmoud, and David W. Rosen. "A Design for Additive Manufacturing Ontology." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60196.

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Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal OWL/RDF representations in the Protégé tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark stud
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Qiu, Tianchen, Xingjian Lai, and Jun Ni. "Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring." In ASME 2020 15th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/msec2020-8496.

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Abstract Progressive (die) stamping is a widely used sheet metal forming process in the manufacturing of automobiles and consumer electronics. Current literature suggests limited knowledge of online health monitoring and fault detection capability. This paper aims to propose a data-driven, empirical approach for diagnosing potential abnormal health conditions of the progressive stamping machine. The proposed signal features and selected novelty detection algorithm work together for fault diagnosis and compensate for the lack of theoretical knowledge of this high-volume high-speed production pr
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Chen, Mengyuan, Jin Tang, Ding Zhu, and Alfred Daniel Hill. "Classification and Localization of Low-Frequency DAS Strain Rate Patterns with Convolutional Neural Networks." In SPE Europec featured at 82nd EAGE Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205136-ms.

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Abstract Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, to examine well stimulation efficacy, and to estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture-hits as hydraulic fractures propagate and create strain rate variations. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated li
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Ji, Dejie, Maximilian Flormann, Joana M. Warnecke, Roman Henze, and Thomas M. Deserno. "Set-Up of an In-Car System for Investigating Driving Style on the Basis of the 3D-Method." In 2024 Stuttgart International Symposium. SAE International, 2024. http://dx.doi.org/10.4271/2024-01-3001.

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<div class="section abstract"><div class="htmlview paragraph">Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving styles based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement syst
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Reports on the topic "Recognizing complete classifications"

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Azuara Herrera, Oliver, Laura Ripani, and Eric Torres Ramirez. AI and the Increase of Productivity and Labor Inequality in Latin America: Potential Impact of Large Language Models on Latin American Workforce. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013152.

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We assess the potential effect of large language models (LLMs) on the labor markets of Chile, Mexico, and Peru using the methodology of Eloundou et al. (2023). This approach involves detailed guidelines (rubrics) for each job to assess whether access to LMM software would reduce the time required for workers to complete their daily tasks. Adapting this methodology to the Latin American context necessitated developing a comprehensive crosswalk between the Occupational Information Network (O*NET) and regional occupational classifications, SINCO-2011 and ISCO-2008. When we use this adaptation, th
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