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Journal articles on the topic 'LMS'

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Published: 4 June 2021

Last updated: 1 June 2023

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1

Momoh, M. O., O. C. Ubadike, I. A. Kachalla, M. A. Isa-Bello, P. U. Chinedu, and M. B. Abdullahi. "VSS-LMS: LMS Algorithm Experimental Approach." MEKATRONIKA 3, no. 2 (July 30, 2021): 31–36. http://dx.doi.org/10.15282/mekatronika.v3i2.7136.

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Optimizing the error between the estimated signal and expected signal is the major goal of a filtering algorithm and the Least Mean Square (LMS) is a well-known adaptive filtering algorithm which plays a significant role in achieving this aim. Nonetheless, the LMS algorithm is usually characterised with low convergence speed in respect to the minimum Mean Square Error (MSE) and flexibility in application. In this paper the Least Mean Square (LMS) algorithm is dealt with a different approach. Contrary to designing LMS filters with fixed step size, variable step size is introduced to improve its convergence speed. An experimental study is considered to formulate a new method for adjusting the step size of the LMS algorithm in this work. Simulation results as well as performance evaluation of the formulated variable step size (VSS-LMS) are presented and compared with the conventional LMS algorithm in terms of MSE and convergence speed.

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2

Kang, Inae, Sunmi Jin, and Heeeun Bae. "Defining The Characteristics of LMS for Smart Learning Drawn from The Analysis of the Current Cases of LMS." Korean Association for Educational Information and Media 22, no. 2 (June 30, 2016): 195–222. http://dx.doi.org/10.15833/kafeiam.22.2.195.

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3

Auzinsh, J., and P. Sliede. "PROGRAM LMS." Vehicle System Dynamics 22, sup1 (January 1993): 74–78. http://dx.doi.org/10.1080/00423119308969472.

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4

&NA;. "LMS PharmacoEconomics." Inpharma Weekly &NA;, no. 864 (November 1992): 9. http://dx.doi.org/10.2165/00128413-199208640-00015.

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5

WANG, LIN, MINGHU JIANG, YINGHUA LU, MINFU SUN, and FRANK NOE. "A COMPARATIVE STUDY OF CLUSTERING METHODS FOR MOLECULAR DATA." International Journal of Neural Systems 17, no. 06 (December 2007): 447–58. http://dx.doi.org/10.1142/s0129065707001287.

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The research aim is to use three clustering technologies for establishing molecular data model of large size sets by comparison between low energy samples (LES) and local molecular samples (LMS). Hierarchical cluster of multi-level tree distance relation, competitive learning network of similar inputs falling into the same cluster and topological SOM are used to analyze 6242 LES and 5000 LMS. Our experiments show that in SOM, there are 24 to 25 Davies-Boulding clustering index and color map cluster units in the LES more than 10 to 12 in the LMS, which is consistent with the results of hierarchical cluster and competitive learning network in the rough. The hierarchical cluster reflects the biggest inter-cluster distance about 30 for the LES is far larger than that of LMS about 10. The intra-cluster distance of LES about 15 is also far bigger than that of LMS about 3. In SOM, there are more cluster borders of high values (black) reflecting large distance and more clusters in the D-matrix and U-matrix of LES than that of LMS, due to the biggest standard deviation range from -8 to 10 of samples feature of the LES is bigger than that of LMS from -2.5 to 2.5.

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6

Behera, Prakash Chandra, Somanjoli Mohapatra, and Chinmaya Dash. "Comparative Study on LCMS, LMS and CMS." International Journal of Information Science and Computing 4, no. 2 (2017): 79. http://dx.doi.org/10.5958/2454-9533.2017.00008.4.

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7

Srar, Jalal Abdulsayed, Kah-Seng Chung, and Ali Mansour. "Adaptive Array Beamforming Using a Combined LMS-LMS Algorithm." IEEE Transactions on Antennas and Propagation 58, no. 11 (November 2010): 3545–57. http://dx.doi.org/10.1109/tap.2010.2071361.

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8

Gan, W. S., J. J. Soraghan, R. W. Stewart, and T. S. Durrani. "Comparative analysis between noncanonical LMS and LMS adaptive filtering." Electronics Letters 27, no. 11 (May 23, 1991): 947–50. http://dx.doi.org/10.1049/el:19910592.

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9

Park, Hee Joo, Hyun Suk Ryoo, Jongkyum Kwon, and Ji Hoon Ryoo. "Change of Paradigm on LMS for Online Education: LMS Implementing Learning Analytics and Online Assessment." Institute for Educational Research 35, no. 2 (June 30, 2022): 49–72. http://dx.doi.org/10.35283/erft.2022.35.2.49.

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Purpose: Online education has increased due to the development of the information and communications technology and the Covid-19 pandemic, which requires to re-define foundational concepts including talented people. In this study, we examine and re-define concepts of roles and functions in LMS and demonstrate an example of LMS fitted to online education. Methods: Systematic review was applied to examine the roles and functions in LMS, which allows to re-define online education. Based on literature review and case study, we explored specific approaches of LMS to help student learning. Also, we demonstrated learning analytics and online assessment as primary functions of LMS via a well-developed LMS. Results: Study results summarize two-folds of LMS: the one is learning analytics and the other is online assessment. That is, LMS should be designated based on learning analytics that indicates student’s learning progress and predicts student’s achievement. LMS should also include ‘on-the-fly’ online assessment that measures student’s learning within online education. Based on these aspects of LMS, we introduced a LMS, called CLASS. Implications: Research on LMS for online education should be collaborated with learning analytics and online assessment, which boosts a convergence research encompassing three topics for online education. Results also inform that LMS plays a key role in cultivating people of talent for 4th industrial revolution and in improving fairness in educational opportunities.

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10

Levacic, Rosalind, and Eamon Marren. "Responding to LMS." Management in Education 6, no. 4 (November 1992): 22–25. http://dx.doi.org/10.1177/089202069200600409.

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11

Dixon, Rob. "Repercussions of LMS." Educational Management & Administration 19, no. 1 (January 1991): 52–61. http://dx.doi.org/10.1177/174114329101900106.

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12

Thomas, George. "Setting Up LMS." Educational Management & Administration 19, no. 2 (January 1991): 84–88. http://dx.doi.org/10.1177/174114329101900204.

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13

Ying-Chang Liang and F. P. S. Chin. "Coherent LMS algorithms." IEEE Communications Letters 4, no. 3 (March 2000): 92–94. http://dx.doi.org/10.1109/4234.831035.

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14

Chen, S., and G. R. Arce. "Microstatistic LMS filtering." IEEE Transactions on Signal Processing 41, no. 3 (March 1993): 1021–34. http://dx.doi.org/10.1109/78.205698.

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15

Pazaitis, D. I., and A. G. Constantinides. "LMS+F algorithm." Electronics Letters 31, no. 17 (August 17, 1995): 1423–24. http://dx.doi.org/10.1049/el:19951026.

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16

Fish, Joseph. "Open Source LMS." International Journal of Advanced Corporate Learning (iJAC) 8, no. 1 (March 9, 2015): 44. http://dx.doi.org/10.3991/ijac.v8i1.4396.

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17

Cracknell, Kenneth. "Book Reviews : Lms." Expository Times 106, no. 9 (June 1995): 283. http://dx.doi.org/10.1177/001452469510600918.

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18

Clarkson, P. M., and T. I. Haweel. "Median LMS algorithm." Electronics Letters 25, no. 8 (1989): 520. http://dx.doi.org/10.1049/el:19890356.

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19

Rigling, B. D., and P. Schniter. "Subspace Leaky LMS." IEEE Signal Processing Letters 11, no. 2 (February 2004): 136–39. http://dx.doi.org/10.1109/lsp.2003.821760.

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20

Poltmann, R. D. "Conversion of the delayed LMS algorithm into the LMS algorithm." IEEE Signal Processing Letters 2, no. 12 (December 1995): 223. http://dx.doi.org/10.1109/97.475854.

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21

Horn, C., and R. H. Kwong. "Convergence of matrix LMS algorithms with applications to LMS/Newton." Signal Processing 44, no. 1 (June 1995): 103–15. http://dx.doi.org/10.1016/0165-1684(95)00018-9.

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22

Boltayev, Telman Bakayevich, and Shukrilla Abdusaid ugli Murodov. "PREPARING THE EDUCA ARING THE EDUCATIONAL MATERIALS USING LMS ALS USING LMS PLATFORM." Scientific Reports of Bukhara State University 3, no. 2 (February 28, 2019): 253–56. http://dx.doi.org/10.52297/2181-1466/2019/3/2/11.

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This article discusses how to develop and apply a learning environment in a structured way, taking into account the student’s personal abilities, using the Moodle platform, which is part of the LMS system. One of the primary factors of increasing the effectiveness of training for the training of specialists who meet today’s requirements is the preparation of the above-mentioned training materials with scientifically-practical significance

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23

Флегантов, Леонід Олексійович. "Методична підтримка навчальних дисциплін засобами сучасних LMS." Theory and methods of e-learning 2 (February 4, 2014): 360–66. http://dx.doi.org/10.55056/e-learn.v2i1.298.

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У статті розглядається використання сучасних LMS (Learning Mamagement System) для методичної підтримки навчальних дисциплін. Проведено розмежування понять LMS, LCMS та навчальний портал. Наведено аргументацію на користь вибору LMS Moodle для організації системи дистанційного навчання вишу. Дано рекомендації щодо порядку розробки дистанційних навчальних курсів на прикладі створення системи дистанційного навчання Полтавської державної аграрної академії, м. Полтава, Україна.

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24

Ramadhani, Rahmi, Ermayanti Astuti, and Titin Setiawati. "THE IMPLEMENTATION OF LMS-GOOGLE CLASSROOM TO IMPROVING COMPETENCE SKILL OF SENIOR HIGH SCHOOL TEACHERS’ IN INDUSTRIAL REVOLUTION 4.0." AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT 3, no. 2 (August 5, 2019): 327–35. http://dx.doi.org/10.32696/ajpkm.v3i2.286.

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Kegiatan program kemitraan masyarakat stimulus (PKMS) yang dilakukan berupa pelatihan implementasi Learning Management System (LMS)-Google Classroom dalam proses pembelajaran untuk meningkatkan kompetensi guru SMA An-Nizam dalam menghadapi era Revolusi Industri 4,0. Jumlah peserta pelatihan ini sebanyak 25 orang guru. Target luaran kegiatan PKMS ini adalah 1) peningkatan pemahaman dan pengetahuan para guru dalam membuat konten bahan ajar, LKS hingga evaluasi penilaian berbasis LMS-Google Classroom dalam proses pembelajaran; 2) peningkatan keterampilan para guru dalam menggunakan LMS-Google Classroom; dan 3) peningkatan motivasi serta antusiasme para guru dalam menerapkan LMS-Google Classroom. Metode kegiatan PKMS ini dilakukan dalam empat tahapan. Tahap pertama adalah konfirmasi dan observasi pendahuluan pada sekolah mitra. Tahap kedua adalah pelaksanaan pelatihan yang diisi dengan turorial penggunaan LMS-Google Classroom. Tahap ketiga adalah implementasi LMS-Google Classroom yang telah dikembangkan (IN dan ON). Tahap keempat adalah evaluasi hasil implementasi. Hasil yang diperoleh dari kegiatan PKMS ini diantaranya 1) para guru mampu memahami cara membuat dan mengembangkan LMS-Google Classroom baik secara konten bahan ajar hingga alat evaluasi penilaian berbasis digital; 2) para guru mampu menggunakan LMS-Google Classroom yang telah dibuat; dan 3) para guru mampu mengundang siswa untuk bergabung dan mempelajari konten bahan ajar maupun evaluasi penilaian dalam LMS-Google Classroom secara antusias dan semangat.

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25

DeBrunner, V. E., and Dayong Zhou. "Hybrid filtered error LMS algorithm: another alternative to filtered-x LMS." IEEE Transactions on Circuits and Systems I: Regular Papers 53, no. 3 (March 2006): 653–61. http://dx.doi.org/10.1109/tcsi.2005.859574.

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26

Dorado, Alex Julián, Carolina González Serrano, and Jovani Alberto Jiménez Builes. "Model of Semantic interoperability between Learning Management Systems." Informador Técnico 79, no. 1 (June 30, 2015): 53. http://dx.doi.org/10.23850/22565035.137.

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Actualmente existen gran variedad de Sistemas de Gestión de Aprendizaje - Learning Management System (LMS) al servicio de todos los niveles educativos y las áreas académicas. Esta diversidad origina un problema de semántica en el conocimiento haciéndolo disperso e inexacto debido a que cada LMS maneja sus propios formatos, arquitecturas y especificaciones. Esto dificulta la interoperabilidad de la información entre diferentes plataformas afectando principalmente a los estudiantes. En el artículo se describe la propuesta de un modelo de interoperabilidad semántica para resolver las necesidades de intercambio de información caracterizadas de los LMS, a partir de las propuestas existentes de solución en el campo de las especificaciones de e-learning, los servicios Web y las ontologías en general.

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27

Vargas-Cubero, Ana Lorena, and Gabriela Villalobos-Torres. "Estrategias docentes para la promoción del aprendizaje autónomo en estudiantes universitarios que utilizan plataformas LMS." Revista Electrónica Calidad en la Educación Superior 10, no. 2 (November 28, 2019): 215–46. http://dx.doi.org/10.22458/caes.v10i2.2715.

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El aprendizaje autónomo en estudiantes universitarios que utilizan plataformas LMS implica el conocimiento teórico del concepto, así como la puesta en práctica de diversas estrategias que fomenten el aprendizaje autónomo en estos entornos. Es así como en un estudio realizado con docentes de asignaturas de la Escuela de Ciencias Sociales y Humanidades y estudiantes que actualmente cursan asignaturas a distancia híbridas, es decir que utilizan recursos y realizan algunas actividades en LMS se planteó el siguiente problema ¿de qué manera las y los docentes impulsan estrategias que promueven el aprendizaje autónomo en estudiantes de un modelo educativo a distancia que utilizan Learning Management System (LMS)? Los resultados obtenidos versan en un conocimiento por parte de docentes acerca del concepto de aprendizaje autónomo, lo cual concuerda con los postulados teóricos al respecto. Así mismo, se detallan características que identifican a un estudiante que aprende con autonomía y las estrategias empleadas por docentes para promover el aprendizaje autónomo mediante las plataformas LMS, mismas que contribuyen a obtener tanto resultados positivos como negativos y diversas manifestaciones en estudiantes sobre la aplicación de las mismas. Las conclusiones discurren sobre la importancia del trabajo colaborativo para el aprendizaje autónomo, la falta de conocimiento metodológico y aplicación de las estrategias en asignaturas a través de plataformas LMS y la necesidad de procesos de capacitación para minimizar el sesgo existente.

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28

Rastogi, Nupur. "Epethelioid LMS-A case report." Asian Pacific Journal of Health Sciences 6, no. 1 (March 2019): 110–13. http://dx.doi.org/10.21276/apjhs.2019.6.1.16.

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29

Gwadabe, Tajuddeen R., Mohammad Shukri Salman, and Hasan Abuhilal. "A Modified Leaky-LMS Algorithm." International Journal of Computer and Electrical Engineering 6, no. 3 (2014): 222–25. http://dx.doi.org/10.7763/ijcee.2014.v6.826.

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30

Pautier, Patricia, Anne Floquet, Didier Cupissol, Benjamin Lacas, Emmanuelle Bompas, Christine Chevreau, Frédéric Selle, et al. "LMS-02: A phase II single-arm multicenter study of doxorubicin in combination with trabectedin as a first-line treatment of advanced uterine leiomyosarcoma (u-LMS) and soft tissue LMS (ST-LMS): First results in patients with u-LMS." Journal of Clinical Oncology 31, no. 15_suppl (May 20, 2013): 10505. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.10505.

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10505 Background: U-LMS and ST-LMS are rare tumours with poor prognosis when metastatic or locally advanced, presenting moderate chemosensitivity mainly to doxorubicine (doxo), ifosfamide (ifo), cisplatin, gemcitabine (gem) and trabectidine (trab). Response rates (RR) in combination therapies (1stline) does not exceed 50% for U-LMS and 35% for ST-LMS. The most active ones are doxo combinations (most of the time with ifo or dacarbazine) and gem + docetaxel (in particular in U-LMS) with a mean response durations of 3 to 6 months. Trab was demonstrated a definite activity on pre-treated LMS (RR of approximately 20% in LMS overall [U-LMS in particular]). In view of these encouraging results on LMS, a study combining trab with doxo as first line therapy for LMS is of interest. Methods: Patients (pts) received every 3 weeks, 6 cycles of doxo 60 mg/m2 followed by trab 1.1 mg/m23-h at day 1, and pegfilgrastim 6 mg on Day 2. Study primary objective: to determine the disease control rate (DCR) (ORR+SD). Secondary objectives: PFS 12 wks, RR by RECIST and duration, OS and toxicities. Patients were stratified into U-LMS (n=45) and ST-LMS (n=62) group. Herein, we report the first results in pts with U-LMS; mature data will be shown in ASCO Meeting. Results: 45 pts with U-LMS have been enrolled until November 2012. Median age is 58 years, 38 where of with data collected for at least 1 cycle, 85% had metastatic disease (mostly lung 30/33, liver and bone), and 26 pts have received 6 cycles. For 33 pts with at least 1 disease assessment (every 2 cycles), the ORR was 55% (18 PR) and 13 SD (39%) had SD disease for a DCR of 94% at that time. Presently, the median PFS at 12 weeks is 94,3% [95%IC:86-100]. Main grade 3-4 toxicities in 187 cycles were neutropenia (51%), febrile neutropenia (7%), thrombopenia (14%), anemia (7%), fatigue (5%), vomiting (6%) and transiet transaminase increase (22%). Conclusions: The combination of trab plus doxo seems to be an effective first-line treatment for pts with U-LMS, with meaningful clinical benefits and an acceptable and manageable safety profile. Clinical trial information: 2009-012430-70.

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31

Socola, Francisco, Dao M. Nguyen, Roberto Enrique Ochoa, Caio Max S. Rocha Lima, and Peter Joel Hosein. "A retrospective cohort study to determine the prognostic factors in metastatic colorectal cancer (mCRC) patients (pts) undergoing lung metastatectomy." Journal of Clinical Oncology 31, no. 4_suppl (February 1, 2013): 565. http://dx.doi.org/10.1200/jco.2013.31.4_suppl.565.

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565 Background: Resection of liver metastases is now accepted as a potentially curative strategy in some pts with mCRC. Resection of lung metastases (LMs) may also be beneficial but this is not well established. We hypothesized that resection of LMs may lead to prolonged survival in highly selected pts with mCRC. Methods: In this IRB-approved retrospective cohort study, cases were defined as mCRC pts with LMs as their only site of disease who underwent metastatectomy. Controls consisted of mCRC pts who had LMs but did not undergo resection. Charts were reviewed for clinical characteristics; survival data was obtained from the institutional tumor registry. The primary endpoint was overall survival (OS) in the cases versus controls. The secondary endpoint was to determine prognostic factors associated with better survival. Results: We included 26 consecutive cases of mCRC undergoing resection of LMs and randomly selected 26 controls. All pts in the both groups were treated with contemporary chemotherapy, as well as bevacizumab and anti-EGFR monoclonals when appropriate. The median OS from the time of diagnosis with LMs was 29.8 months (95% CI 22.9-36.6) in the control group versus 56.6 months (95% CI 47.3-65.8) for the cases who underwent resection (log rank p=0.04). A number of baseline factors were significantly different between the cases and controls. The control group contained more pts with poorly differentiated tumors (p=0.016); had more pts with synchronous versus metachronous presentation of LM's (p=0.001); had more pts with multiple vs solitary LM's (p<0.001); and had more pts with bilateral vs unilateral LMs (p<0.001). The interval from initial diagnosis to the onset of LMs was significantly longer in the resection group vs controls (22.9 vs 2.9 months, p<0.001). Conclusions: In this retrospective study, pts with mCRC to the lung who were referred for resection were more likely to have well differentiated, solitary, unilateral tumors, with a long interval between the original diagnosis and the onset of LMs. Pts selected using these criteria may have a significant survival benefit from surgical resection of their LMs.

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32

Shang, Yong, Shunjun Wu, and Haige Xiang. "Parallel delayed LMS algorithm." Science in China Series F Information Sciences 44, no. 6 (December 2001): 438–44. http://dx.doi.org/10.1007/bf02713947.

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33

Huckman, Lynda. "LMS in Primary Schools." Management in Education 8, no. 2 (June 1994): 32–34. http://dx.doi.org/10.1177/089202069400800215.

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34

Solo, V. "The stability of LMS." IEEE Transactions on Signal Processing 45, no. 12 (1997): 3017–26. http://dx.doi.org/10.1109/78.650261.

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35

Liu, J. C., and T. P. Lin. "LMS-based DHT analyser." Electronics Letters 24, no. 8 (1988): 483. http://dx.doi.org/10.1049/el:19880328.

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36

Prextová, Tatiana. "Testing in Adaptive LMS." International Journal of Information and Communication Technologies in Education 5, no. 1 (August 1, 2016): 59–71. http://dx.doi.org/10.1515/ijicte-2016-0004.

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Abstract For a number of years now, the research activity at the Department of Information and Communication Technologies at the Pedagogical Faculty of the University of Ostrava has been aimed at improving the quality of instruction. A team of experts has been assembled who can create new study materials that can be used in the electronic environment and are able to adapt to students’ individual characteristics and needs. As feedback is an integral part of instruction (be it the e-learning or the classic one), the proposition of electronic adaptive testing has been included in the process. In the proposition, the authors ponder a number of alternative possibilities of adapting test tasks - suitably formulated tasks, suitable reactions to the student’s correct and incorrect answers, suitable selection of individual test tasks. This paper aims to introduce the basic principles and rules of electronic adaptive testing and consider other adaptation options.

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37

Klubal, Libor, Kateřina Kostolányová, and Vojtěch Gybas. "Gamification in LMS Courses." International Journal of Information and Communication Technologies in Education 7, no. 2 (October 1, 2018): 46–50. http://dx.doi.org/10.1515/ijicte-2018-0009.

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Abstract This paper attempts to respond to the use of the elements of gamification in education. With the help of research papers, we have chosen three different systems in which the elements of gamification are included and we have focused on their use in education.

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38

Godavarti, M., and A. O. Hero. "Partial update LMS algorithms." IEEE Transactions on Signal Processing 53, no. 7 (July 2005): 2382–99. http://dx.doi.org/10.1109/tsp.2005.849167.

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39

Bergmans, Jan W. M., Maria Yu Lin, David Modrie, and Rob Otte. "Asynchronous LMS adaptive equalization." Signal Processing 85, no. 7 (July 2005): 1301–13. http://dx.doi.org/10.1016/j.sigpro.2004.12.006.

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40

Leung, S. H., and B. L. Chan. "Fast converging LMS equaliser." Electronics Letters 29, no. 10 (May 13, 1993): 829–30. http://dx.doi.org/10.1049/el:19930554.

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41

Lim, Sliao-Jen, and J. G. Harris. "Combined LMS/F algorithm." Electronics Letters 33, no. 6 (1997): 467. http://dx.doi.org/10.1049/el:19970311.

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42

Oh, Kil Nam. "A Modified Decision-Directed LMS Algorithm." Journal of the Institute of Electronics and Information Engineers 53, no. 7 (July 25, 2016): 3–8. http://dx.doi.org/10.5573/ieie.2016.53.7.003.

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43

Yazdi, H. Sadoghi, M. Lotfizad, and M. Fathy. "Car tracking by quantised input LMS, QX-LMS algorithm in traffic scenes." IEE Proceedings - Vision, Image, and Signal Processing 153, no. 1 (2006): 37. http://dx.doi.org/10.1049/ip-vis:20045043.

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44

Rupp, M. "Saving complexity of modified filtered-X-LMS and delayed update LMS algorithms." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 44, no. 1 (1997): 57–60. http://dx.doi.org/10.1109/82.559371.

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45

Slock, D. T. M. "On the convergence behavior of the LMS and the normalized LMS algorithms." IEEE Transactions on Signal Processing 41, no. 9 (1993): 2811–25. http://dx.doi.org/10.1109/78.236504.

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46

Hémery, Daniel. "D'une bureaucratie asiatique à la bourgeoisie cubaine..." Le Mouvement Social 194, no. 1 (2001): 3. http://dx.doi.org/10.3917/lms.194.0003.

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Poisson, Emmanuel. "L'infrabureaucratie vietnamienne au Bac Ky (Tonkin) de l'indépendance au protectorat." Le Mouvement Social 194, no. 1 (2001): 7. http://dx.doi.org/10.3917/lms.194.0007.

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Winocur, Marcos. "Les calculs politiques de la bourgeoisie face à la révolution de Fidel Castro." Le Mouvement Social 194, no. 1 (2001): 25. http://dx.doi.org/10.3917/lms.194.0025.

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Daviet-Vincent, Marie-Bénédicte. "De l'honneur de la corporation à l'honneur de la patrie." Le Mouvement Social 194, no. 1 (2001): 39. http://dx.doi.org/10.3917/lms.194.0039.

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Kott, Sandrine. "Le don comme rituel en R.D.A. 1949-1989." Le Mouvement Social 194, no. 1 (2001): 67. http://dx.doi.org/10.3917/lms.194.0067.

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