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Journal articles on the topic 'Feature management'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Hora, Parul, Neha Sheth, and Santosh K. Vishwakarma. "Disaster Management using Ontology Feature." International Journal of Computer Applications 183, no. 49 (January 18, 2022): 6–9. http://dx.doi.org/10.5120/ijca2022921901.

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2

Lamprecht, Anna-Lena, Stefan Naujokat, and Ina Schaefer. "Variability Management beyond Feature Models." Computer 46, no. 11 (November 2013): 48–54. http://dx.doi.org/10.1109/mc.2013.299.

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3

Beuche, Danilo, Holger Papajewski, and Wolfgang Schröder-Preikschat. "Variability management with feature models." Science of Computer Programming 53, no. 3 (December 2004): 333–52. http://dx.doi.org/10.1016/j.scico.2003.04.005.

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4

Bitton, Etty. "Lubricity feature enhances SLK management." Contact Lens and Anterior Eye 38 (February 2015): e27-e28. http://dx.doi.org/10.1016/j.clae.2014.11.037.

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5

Lamke, Gene G. "A Journal Feature–Personnel Management." Recreational Sports Journal 16, no. 1 (October 1991): 12. http://dx.doi.org/10.1123/nirsa.16.1.12.

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6

Govier, Ian. "Feature." Nursing Management 10, no. 9 (February 2004): 13–15. http://dx.doi.org/10.7748/nm.10.9.13.s12.

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7

Gattol, Valentin, Maria Sääksjärvi, Tripat Gill, and Jan Schoormans. "Feature fit." European Journal of Innovation Management 19, no. 4 (October 10, 2016): 589–607. http://dx.doi.org/10.1108/ejim-08-2015-0069.

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Purpose Previous research in the context of feature fit has examined the effects of congruence (i.e. more specifically, the extent to which a new feature and the product are similar in the hedonic-utilitarian benefits they provide to consumers). The purpose of this paper is to examine a second dimension of feature fit: complementarity (i.e. the extent to which a new feature is related and contributing to the main functionality of the product). Design/methodology/approach The role of feature fit is examined in two experimental studies (n=593) in the context of feature additions, and also for feature deletions. Findings The results showed that complementarity adds value to a product as an additional dimension of feature fit beyond congruence, complementarity matters more for a hedonic than for a utilitarian product, and complementarity can compensate for lack of congruence. Originality/value For a product developer, adding new features to a product offers an array of choices in terms of what feature(s) to include. Although having a large pool of potential features to choose from is attractive it can also prove problematic, as products may become overly complex and features do not fit well together. The results demonstrate the importance of both congruence and complementarity as predictors of feature fit when features are added to or deleted from products.

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8

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 22, no. 3 (July 1997): 111–24. http://dx.doi.org/10.1177/0256090919970312.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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9

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 23, no. 3 (July 1998): 91–104. http://dx.doi.org/10.1177/0256090919980312.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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10

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 24, no. 1 (January 1999): 93–106. http://dx.doi.org/10.1177/0256090919990111.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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11

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 24, no. 2 (April 1999): 69–82. http://dx.doi.org/10.1177/0256090919990209.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 24, no. 3 (July 1999): 71–84. http://dx.doi.org/10.1177/0256090919990310.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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13

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 24, no. 4 (October 1999): 81–94. http://dx.doi.org/10.1177/0256090919990411.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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14

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 25, no. 1 (January 2000): 127–42. http://dx.doi.org/10.1177/0256090920000120.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New DelhC this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 25, no. 4 (October 2000): 107–32. http://dx.doi.org/10.1177/0256090920000411.

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This section features abstracts of article covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Author desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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16

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 26, no. 1 (January 2001): 143–68. http://dx.doi.org/10.1177/0256090920010110.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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17

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 26, no. 2 (April 2001): 107–27. http://dx.doi.org/10.1177/0256090920010209.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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18

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 26, no. 4 (October 2001): 113–34. http://dx.doi.org/10.1177/0256090920010410.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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19

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 27, no. 1 (January 2002): 99–122. http://dx.doi.org/10.1177/0256090920020111.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for� inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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20

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 27, no. 2 (April 2002): 95–114. http://dx.doi.org/10.1177/0256090920020210.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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21

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 27, no. 3 (July 2002): 79–98. http://dx.doi.org/10.1177/0256090920020309.

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Abstract:

This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Uffice.

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22

Sarkar, Mitali. "Indian Management Research." Vikalpa: The Journal for Decision Makers 27, no. 4 (October 2002): 103–22. http://dx.doi.org/10.1177/0256090920020410.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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23

Komyanchina, K. "Quality management as new function and feature of modern management." Bulletin of the South Ural State University Series «Social Sciences and the Humanities» 16, no. 03 (2016): 68–72. http://dx.doi.org/10.14529/ssh160310.

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24

Wicaksono, Galih Wasis, Pamula Brian Nawisworo, Evi Dwi Wahyuni, and Yus Muhammad Cholily. "Canvas Learning Management System Feature Analysis Using Feature-Oriented Domain Analysis (FODA)." IOP Conference Series: Materials Science and Engineering 1077, no. 1 (February 1, 2021): 012041. http://dx.doi.org/10.1088/1757-899x/1077/1/012041.

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25

De Giovanni, Pietro. "Recursive Effects to Study Feature-Based Capabilities in Supply Chain Management." Logistics 4, no. 4 (November 2, 2020): 28. http://dx.doi.org/10.3390/logistics4040028.

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This paper explores the benefits that firms obtain when investing in feature-based capabilities. We investigate the external pressures when deciding their feature-based strategy. In addition, we analyze the consumers’ customization options and the needs for facilitators to mitigate the negative effects of excessive features. We assess the influence of feature-based capabilities on performance and search for an economically feasible loop that feature-based capabilities might entail. This latter is carried out by investigating the recursive effects in structural equation modeling. Our findings reveal that feature-based capabilities entail an economically feasible loop through competitors and supply chain partners but not also through facilitators and operational performance.

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26

Taha, Mohammed A., Hanaa M. Ahmed, and Saif O. Husain. "Iris Features Extraction and Recognition based on the Scale Invariant Feature Transform (SIFT)." Webology 19, no. 1 (January 20, 2022): 171–84. http://dx.doi.org/10.14704/web/v19i1/web19013.

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Iris Biometric authentication is considered to be one of the most dependable biometric characteristics for identifying persons. In actuality, iris patterns have invariant, stable, and distinguishing properties for personal identification. Due to its excellent dependability in personal identification, iris recognition has received more attention. Current iris recognition methods give good results especially when NIR and specific capture conditions are used in collaboration with the user. On the other hand, values related to images captured using VW are affected by noise such as blurry images, eye skin, occlusion, and reflection, which negatively affects the overall performance of the recognition systems. In both NIR and visible spectrum iris images, this article presents an effective iris feature extraction strategy based on the scale-invariant feature transform algorithm (SIFT). The proposed method was tested on different databases such as CASIA v1 and ITTD v1, as NIR images, as well as UBIRIS v1 as visible-light color images. The proposed system gave good accuracy rates compared to existing systems, as it gave an accuracy rate of (96.2%) when using CASIA v1 and (96.4%) in ITTD v1, while the system accuracy dropped to (84.0 %) when using UBIRIS v1.

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27

Sarkar, Mitali. "Abstracts Indian Management Research." Vikalpa: The Journal for Decision Makers 22, no. 4 (October 1997): 77–89. http://dx.doi.org/10.1177/0256090919970411.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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28

Sarkar, Mitali. "Abstracts Indian Management Research." Vikalpa: The Journal for Decision Makers 25, no. 2 (April 2000): 79–92. http://dx.doi.org/10.1177/0256090920000209.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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29

Sarkar, Mitali. "Abstracts Indian Management Research." Vikalpa: The Journal for Decision Makers 25, no. 3 (July 2000): 89–103. http://dx.doi.org/10.1177/0256090920000310.

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This section features abstracts of articles covering empirical studies, experiences, ideas, and theories published in Indian and international journals. Sponsored by the Indian Council of Social Science Research, New Delhi, this service is intended to facilitate Indian management research. Authors desirous of having their publications considered for inclusion in this feature may please send reprints of their articles to Vikalpa Editorial Office.

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30

Zenios, Stavros A., and David Saunders. "Feature Cluster: Operational Research for Risk Management." European Journal of Operational Research 185, no. 3 (March 2008): 1402–3. http://dx.doi.org/10.1016/j.ejor.2006.09.001.

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31

Zhou, Peng, Ni Wang, and Shu Zhao. "Online group streaming feature selection considering feature interaction." Knowledge-Based Systems 226 (August 2021): 107157. http://dx.doi.org/10.1016/j.knosys.2021.107157.

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32

Choi, Jinmu, Jeong Chang Seong, Bora Kim, and E. Lynn Usery. "Innovations in Individual Feature History Management—The Significance of Feature-based Temporal Model." GeoInformatica 12, no. 1 (March 27, 2007): 1–20. http://dx.doi.org/10.1007/s10707-007-0019-y.

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33

Seny Kan, Konan Anderson, Ababacar Mbengue, Mahamadou Biga-Diambeidou, and dt ogilvie. "Introduction to the Thematic Feature." La recherche en management internationale et l’Afrique — Une perspective de recherche-action 26, no. 3 (July 6, 2022): 127–39. http://dx.doi.org/10.7202/1090298ar.

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This article shows how international business/management (IB/IM) research can be articulated to an in-depth understanding of Africa to serve both academic knowledge development and African priorities. It critically recalls the central characteristics of IB/IM as a field of research, shows how Africa is studied in this field, suggests “African management” as one response to some of the major criticisms of current research in IB/IM, outlines some crossovers between IB/IM and African management, and discusses the contribution of Africa-focused publications in the journal International Management to some of the foundations of the proposed cross-fertilization between IB/IM and African management.

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34

N M Bazlur Rashid, A., and Tonmoy Choudhury. "Knowledge management overview of feature selection problem in high-dimensional financial data: cooperative co-evolution and MapReduce perspectives." Problems and Perspectives in Management 17, no. 4 (December 26, 2019): 340–59. http://dx.doi.org/10.21511/ppm.17(4).2019.28.

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The term “big data” characterizes the massive amounts of data generation by the advanced technologies in different domains using 4Vs – volume, velocity, variety, and veracity - to indicate the amount of data that can only be processed via computationally intensive analysis, the speed of their creation, the different types of data, and their accuracy. High-dimensional financial data, such as time-series and space-time data, contain a large number of features (variables) while having a small number of samples, which are used to measure various real-time business situations for financial organizations. Such datasets are normally noisy, and complex correlations may exist between their features, and many domains, including financial, lack the al analytic tools to mine the data for knowledge discovery because of the high-dimensionality. Feature selection is an optimization problem to find a minimal subset of relevant features that maximizes the classification accuracy and reduces the computations. Traditional statistical-based feature selection approaches are not adequate to deal with the curse of dimensionality associated with big data. Cooperative co-evolution, a meta-heuristic algorithm and a divide-and-conquer approach, decomposes high-dimensional problems into smaller sub-problems. Further, MapReduce, a programming model, offers a ready-to-use distributed, scalable, and fault-tolerant infrastructure for parallelizing the developed algorithm. This article presents a knowledge management overview of evolutionary feature selection approaches, state-of-the-art cooperative co-evolution and MapReduce-based feature selection techniques, and future research directions.

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35

LI, R. K., C. Y. LIN, and H. H. WU. "Feature modification framework for feature based design systems." International Journal of Production Research 33, no. 2 (February 1995): 549–63. http://dx.doi.org/10.1080/00207549508930165.

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36

Verma, A. K., and S. Rajotia. "Feature vector: a graph-based feature recognition methodology." International Journal of Production Research 42, no. 16 (August 15, 2004): 3219–34. http://dx.doi.org/10.1080/00207540410001699408.

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37

Ippakayala, Vinay Kumar, and Hosam El-Ocla. "OLMS: Online Learning Management System for E-Learning." World Journal on Educational Technology: Current Issues 6, no. 3 (August 5, 2017): 130. http://dx.doi.org/10.18844/wjet.v6i3.1973.

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In this paper we introduce a learning management system that provides a management system for centralized control of course content. A secure system to record lectures is implemented as a key feature of this application. This feature would be accessed through web camera and mobile recording. These features are mainly designed for e-learning environment. In addition, we integrate a learning management system with a platform for social activities and student assessment analysis is developed. Users Including students, professors, and administrators are able to manage schedules, lectures, assignments, jobs, events, discussions, and research.

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Ippakayala, Vinay Kumar, and Hosam El-Ocla. "OLMS: Online Learning Management System for E-Learning." World Journal on Educational Technology: Current Issues 9, no. 3 (July 5, 2017): 130–38. http://dx.doi.org/10.18844/wjet.v9i3.1973.

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In this paper we introduce a learning management system that provides a management system for centralized control of course content. A secure system to record lectures is implemented as a key feature of this application. This feature would be accessed through web camera and mobile recording. These features are mainly designed for e-learning environment. In addition, we integrate a learning management system with a platform for social activities and student assessment analysis is developed. Users Including students, professors, and administrators are able to manage schedules, lectures, assignments, jobs, events, discussions, and research.

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39

Lee, Se-Jin, Byung-Jae Park, Jong-Hwan Lim, and Dong-Woo Cho. "Feature map management for mobile robots in dynamic environments." Robotica 28, no. 1 (April 28, 2009): 97–106. http://dx.doi.org/10.1017/s026357470900561x.

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SUMMARYThis paper presents a new approach to the management of the environmental map for mobile robots in dynamic environments. The environmental map is built of primitive features, such as lines, points, and even circles, extracted from ambiguous data captured by the robot's sonar sensor ring. The feature map must be managed because the indoor surroundings where mobile robots operate are continuously changing due to nonstationary objects, such as wastebaskets, tables, and people. The features are processed by trimming, division, or removal, depending on the dynamic circumstances. All processing refers to the occupancy probabilities of grid squares generated for the map features. The occupancy probabilities of the squares are updated using the Bayesian updating model with the sonar sensor data. Experimental results demonstrate the validity of the proposed method.

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40

Posada-Vanegas, Gregorio, Gerardo Durán-Valdez, Rodolfo Silva-Casarin, Maria Elena Maya-Magaña, and Jose Antonio Salinas-Prieto. "VULNERABILITY TO COASTAL FLOODING INDUCED BY TROPICAL CYCLONES." Coastal Engineering Proceedings 1, no. 32 (January 31, 2011): 19. http://dx.doi.org/10.9753/icce.v32.management.19.

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Hurricanes are a recurrent feature on Mexican coasts; they create floods whose economic and social damages are evident. The necessity to evaluate the natural hazard related to storm surge is fundamental to reduce risk in coastal areas. In order to generate flooding hazard maps, storm surge associated to different return periods is computed with a 2D numerical model. The first part of this work is related with the data and numerical models used to calculate the storm surge, the second part contain the results obtained with the simulations. This work has been done for the entire Mexican coastline but only results for the Gulf of Mexico are presented

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Bouikni, Nadjib, Alain Desrochers, and Louis Rivest. "A Product Feature Evolution Validation Model for Engineering Change Management." Journal of Computing and Information Science in Engineering 6, no. 2 (February 10, 2006): 188–95. http://dx.doi.org/10.1115/1.2194909.

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Product design integrates several disciplines in a concurrent engineering (CE) environment. Each one of these disciplines has a specific point of view on the product being developed. While each discipline exerts its own expertise and methods on the definition of the product and its related processes, information must remain consistent for all disciplines and through the evolution of the product definition. This paper proposes a product feature evolution validation (PFEV) model that aims at controlling the information flow needed to support a product definition evolution (PDE) while insuring its validation by all disciplines involved. The model applies both to the product design and modification phases, i.e., before and after releasing its definition. The PFEV model thus supports CE and enables managing the product feature evolution throughout the product life cycle. The PFEV model defines an exchange protocol between the disciplines in order to preserve the consistency of the numerical model, which includes the complete numerical information characterizing the product. The model addresses two qualities of an information system: dispatching relevant PDE information to appropriate disciplines and providing this information according to specific views. This is achieved by centralizing the product numerical model and by exploiting the product’s features rather than managing product model as black boxes. Links between features are formalized in a shared product features table that is used to dynamically identify all disciplines impacted by a product feature evolution (PFE). A PFE is also characterized by its potential impact, detrimental or beneficial, on every discipline previously identified as impacted. In the case of a detrimental impact, the discipline is asked to validate the evolution. If the impact is beneficial, the discipline is simply notified about the evolution. Specific views are generated for the impacted disciplines based on feature filtering and adaptation mechanisms.

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42

Corallo, Angelo, Manuela Marra, and Claudio Pascarelli. "Knowledge-Based Manufacturing: Management and Deployment of Manufacturing Rules through Product Lifecycle Management Systems." Aerospace 6, no. 4 (April 6, 2019): 41. http://dx.doi.org/10.3390/aerospace6040041.

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In manufacturing companies, computer-aided design (CAD)/computer-aided manufacturing (CAM) feature-based approaches have been developed for faster numerical control (NC) programming. They allow to automatically generate toolpath, recognizing both standard and custom machining features, and defining for each of them the best or preferred machining process based on predefined rules. The definition of Feature Based Manufacturing (FBM) rules requires advanced competences and skills; furthermore, the standardization required by these instruments is too rigorous for real machining practices. It is therefore necessary to extend the Product Lifecycle Management (PLM) environment in order to be able to make explicit and manage manufacturing rules based on industrial best practice. The paper addresses these problems presenting a possible solution to optimize FBM information management and integration within the product lifecycle. A data model extension, covering new items such as “manufacturing rules” and “tool setting preferences”, and a new methodology for rules management and deployment are proposed.

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Dianiya, Vicky. "Management Privacy dalam Penggunaan Fitur “Close Friend” di Instagram." Jurnal Studi Komunikasi (Indonesian Journal of Communications Studies) 5, no. 1 (February 16, 2021): 249. http://dx.doi.org/10.25139/jsk.v5i1.2652.

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Social media is basically to share information and self-disclosures by the account owner. However, there is an attitude of caution in expressing which must also be considered and needs to be considered. Technological developments make more and more new features appear on various social media platforms, one of them is the close friend feature on Instagram that can be used to limit users in sharing information that is considered more privacy. This study uses the Communication Privacy Management theory as a framework for investigating how Instagram users, especially young adults, use and respond to the use of the close friend feature. Overall, the results of interviews with five informants found evidence of five basic assumptions in using CPM implied on social media and showed that there is confidence in the disclosure of privacy when using the close friend feature.

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Cohen, Maxime C., Ilan Lobel, and Renato Paes Leme. "Feature-Based Dynamic Pricing." Management Science 66, no. 11 (November 2020): 4921–43. http://dx.doi.org/10.1287/mnsc.2019.3485.

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We consider the problem faced by a firm that receives highly differentiated products in an online fashion. The firm needs to price these products to sell them to its customer base. Products are described by vectors of features and the market value of each product is linear in the values of the features. The firm does not initially know the values of the different features, but can learn the values of the features based on whether products were sold at the posted prices in the past. This model is motivated by applications such as online marketplaces, online flash sales, and loan pricing. We first consider a multidimensional version of binary search over polyhedral sets and show that it has a worst-case regret which is exponential in the dimension of the feature space. We then propose a modification of the prior algorithm where uncertainty sets are replaced by their Löwner-John ellipsoids. We show that this algorithm has a worst-case regret which is quadratic in the dimension of the feature space and logarithmic in the time horizon. We also show how to adapt our algorithm to the case where valuations are noisy. Finally, we present computational experiments to illustrate the performance of our algorithm. This paper was accepted by Yinyu Ye, optimization.

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Lee, Jaejoon, and Dirk Muthig. "Feature-oriented variability management in product line engineering." Communications of the ACM 49, no. 12 (December 2006): 55–59. http://dx.doi.org/10.1145/1183236.1183266.

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Mezini, Mira, and Klaus Ostermann. "Variability management with feature-oriented programming and aspects." ACM SIGSOFT Software Engineering Notes 29, no. 6 (November 2004): 127–36. http://dx.doi.org/10.1145/1041685.1029915.

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Forsberg, Kevin. "Introduction to This Special Feature on Knowledge Management." INSIGHT 14, no. 1 (April 2011): 7–8. http://dx.doi.org/10.1002/inst.20111417.

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LI, JIANPING, ZHENYU CHEN, LIWEI WEI, WEIXUAN XU, and GANG KOU. "FEATURE SELECTION VIA LEAST SQUARES SUPPORT FEATURE MACHINE." International Journal of Information Technology & Decision Making 06, no. 04 (December 2007): 671–86. http://dx.doi.org/10.1142/s0219622007002733.

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In many applications such as credit risk management, data are represented as high-dimensional feature vectors. It makes the feature selection necessary to reduce the computational complexity, improve the generalization ability and the interpretability. In this paper, we present a novel feature selection method — "Least Squares Support Feature Machine" (LS-SFM). The proposed method has two advantages comparing with conventional Support Vector Machine (SVM) and LS-SVM. First, the convex combinations of basic kernels are used as the kernel and each basic kernel makes use of a single feature. It transforms the feature selection problem that cannot be solved in the context of SVM to an ordinary multiple-parameter learning problem. Second, all parameters are learned by a two stage iterative algorithm. A 1-norm based regularized cost function is used to enforce sparseness of the feature parameters. The "support features" refer to the respective features with nonzero feature parameters. Experimental study on some of the UCI datasets and a commercial credit card dataset demonstrates the effectiveness and efficiency of the proposed approach.

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KASYMBEKOV, A. S., and A. R. KHASANOV. "ORGANIZATIONAL AUTOMATED CONTROL SYSTEMS AND FEATURE." Q A Iasaýı atyndaǵy Halyqaralyq qazaq-túrіk ýnıversıtetіnіń habarlary (fızıka matematıka ınformatıka serııasy), no. 1 (March 15, 2022): 7–17. http://dx.doi.org/10.47526/2022-2/2524-0080.01.

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The article discusses the automated management systems of the organization and the study of the features of the automation process of software development. The main directions of automation of the management process, functional and structural parts of automated management systems of the organization and their classification are described. It provides for scripting or automating a wide range of software tasks for compiling and packaging code, performing automated tests, implementing software and creating documentation using the example of the integrated automated management system "University".

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Riady, Sasmitoh Rahmad, Khalis Sofi, Jafar Shadiq, and Rita Wahyuni Arifin. "Selection of Feature Driven Development (FDD) Model in Agile Method for Developing Information System of Mosque Management." Journal of Computer Networks, Architecture and High Performance Computing 4, no. 2 (July 19, 2022): 127–36. http://dx.doi.org/10.47709/cnahpc.v4i2.1469.

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This paper discusses about software development for building a project using the Feature Driven Development (FDD) model contained in the agile method. As in other agile methods, the Feature Driven Development model has additional properties to implement functions and needs in a short iteration. In terms of the characteristics contained in several other agile models almost all of them have similarities so that makes the stakeholder confusion in determining which model will be chosen as a method of software development. This study focuses on the search for a number of suitable project specifications in the selection of Feature Driven Development models for software development. From the research that has been done on several papers there are several aspects of design and construction in software development by emphasizing the quality and high level of features in developing a software using the Feature Driven Development model. In facilitating the results of the Feature Driven Development model, we will provide a case study of Mosque Management Information System which has several features, such as content management, information of prayer time, online reading Qur’an, and Petty Cash Mosque management. This case is implemented by Feature Driven Development model with short iteration, because this project had done in several months

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