Relevant bibliographies by topics / Scheins embedding mechanisms

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  1. Dissertations / Theses
  2. Book chapters
  3. Conference papers

Academic literature on the topic 'Scheins embedding mechanisms'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Dissertations / Theses on the topic "Scheins embedding mechanisms"

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Forsell, Johannes, and Hedda Billstein. "En enhetlig organisationskultur i en decentraliserad verksamhet : En fallstudie av Handelsbanken." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434516.

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Tidigare forskning indikerar att organisationskultur är en viktig aspekt för organisatorisk framgång. Hur arbetet mot en gemensam organisationskultur i praktiken sker finns däremot motstridiga åsikter kring. Att sträva efter en väletablerad och stark organisationskultur kan försvåras av ett flertal aspekter, varav en decentraliserad organisationsstruktur är ett exempel. Syftet med undersökningen var att identifiera praktiska tillvägagångssätt för att stödja och förstärka en enhetlig organisationskultur i en verksamhet präglad av decentralisering. Undersökningen avsåg testa
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Book chapters on the topic "Scheins embedding mechanisms"

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Rennaker, Mark A., and Dan Novak. "Culture." In Advances in Human Resources Management and Organizational Development. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-533-9.ch003.

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Culture represents a pattern of beliefs, values, assumptions, and behaviors that both develops and persists over time within a social unit. Cultural patterns might be observed at multiple levels including beliefs or assumptions (Schein, 2004), multiple layers including corporate or global (Marquardt & Engel, 1993), multiple factors including religion and family (Marquardt & Engel, 1993), and multiple dimensions including power-distance and uncertainty avoidance (Hofstede, 2001). The multiple locations and individual cultures represented by distributed team members suggests that creation and enhancement of culture by distributed team leaders is more complex than in face-to-face teams. Culture-building tools available to leaders include primary embedding mechanisms such as what leaders pay attention to and who leaders recruit, along with secondary embedding mechanisms including philosophies and creeds (Schein, 2004).
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Santhi, V., and D. P. Acharjya. "Intelligence-Based Adaptive Digital Watermarking for Images in Wavelet Transform Domain." In Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8654-0.ch012.

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Advances in technologies facilitate the end users to carry out unauthorized manipulation and duplication of multimedia data with less effort. Because of these advancements, the two most commonly encountered problems are (1) copyright protection and (2) unauthorized manipulation of multimedia data. Thus a scheme is required to protect multimedia data from those two above said problems. Digital Watermarking is considered as one of the security mechanisms to protect copyrights of multimedia data. The literature review reveals that the calculation of scaling and embedding parameters are not completely automated. In order to automate the procedure of calculating scaling and embedding parameters the computational intelligence need to be incorporated in the watermarking algorithm. Moreover the quality of the watermarked images could also be preserved by combining computational intelligence concepts. Thus watermarking schemes utilizing computational intelligence concepts could be called as intelligence based watermarking schemes and it is presented in this chapter in detail.
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Santhi, V., and D. P. Acharjya. "Intelligence-Based Adaptive Digital Watermarking for Images in Wavelet Transform Domain." In Biometrics. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0983-7.ch061.

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Abstract:
Advances in technologies facilitate the end users to carry out unauthorized manipulation and duplication of multimedia data with less effort. Because of these advancements, the two most commonly encountered problems are (1) copyright protection and (2) unauthorized manipulation of multimedia data. Thus a scheme is required to protect multimedia data from those two above said problems. Digital Watermarking is considered as one of the security mechanisms to protect copyrights of multimedia data. The literature review reveals that the calculation of scaling and embedding parameters are not completely automated. In order to automate the procedure of calculating scaling and embedding parameters the computational intelligence need to be incorporated in the watermarking algorithm. Moreover the quality of the watermarked images could also be preserved by combining computational intelligence concepts. Thus watermarking schemes utilizing computational intelligence concepts could be called as intelligence based watermarking schemes and it is presented in this chapter in detail.
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4

Bhajantri, Lokesh B., and Tabassum N. Mujawar. "A Comprehensive Review of Access Control Mechanism Based on Attribute Based Encryption Scheme for Cloud Computing." In Research Anthology on Artificial Intelligence Applications in Security. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7705-9.ch042.

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Cloud computing is the most prevailing paradigm, which provides computing resources and services over the Internet. Due to immense development in services provided by cloud computing, the trend to share large-scale and confidential data on cloud has been increased. Though cloud computing provides many benefits, ensuring security of the data stored in cloud is the biggest challenge. The security concern about the data becomes main barrier for adoption of cloud. One of the important security aspects is fine grained access control mechanism. The most widely used and efficient access control scheme for cloud computing is Attribute Based Encryption (ABE). The Attribute Based Encryption (ABE) scheme provides a new technique for embedding access policies cryptographically into encryption process. The article presents an overview of various existing attribute-based encryption schemes and traditional access control models. Also, the comparison of existing ABE schemes for cloud computing, on basis of various criteria is presented in the article.
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Bhajantri, Lokesh B., and Tabassum N. Mujawar. "A Comprehensive Review of Access Control Mechanism Based on Attribute Based Encryption Scheme for Cloud Computing." In Research Anthology on Artificial Intelligence Applications in Security. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7705-9.ch042.

Full text
Abstract:
Cloud computing is the most prevailing paradigm, which provides computing resources and services over the Internet. Due to immense development in services provided by cloud computing, the trend to share large-scale and confidential data on cloud has been increased. Though cloud computing provides many benefits, ensuring security of the data stored in cloud is the biggest challenge. The security concern about the data becomes main barrier for adoption of cloud. One of the important security aspects is fine grained access control mechanism. The most widely used and efficient access control scheme for cloud computing is Attribute Based Encryption (ABE). The Attribute Based Encryption (ABE) scheme provides a new technique for embedding access policies cryptographically into encryption process. The article presents an overview of various existing attribute-based encryption schemes and traditional access control models. Also, the comparison of existing ABE schemes for cloud computing, on basis of various criteria is presented in the article.
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Conference papers on the topic "Scheins embedding mechanisms"

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Wang, Zihan, Zhaochun Ren, Chunyu He, Peng Zhang, and Yue Hu. "Robust Embedding with Multi-Level Structures for Link Prediction." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/728.

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Knowledge Graph (KG) embedding has become crucial for the task of link prediction. Recent work applies encoder-decoder models to tackle this problem, where an encoder is formulated as a graph neural network (GNN) and a decoder is represented by an embedding method. These approaches enforce embedding techniques with structure information. Unfortunately, existing GNN-based frameworks still confront 3 severe problems: low representational power, stacking in a flat way, and poor robustness to noise. In this work, we propose a novel multi-level graph neural network (M-GNN) to address the above chal
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