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Littérature scientifique sur le sujet « Low-distortion embedding »

Auteur : Grafiati
Publié le 25 mai 2024

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Articles de revues sur le sujet "Low-distortion embedding"

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Castermans, Thom, Kevin Verbeek, Bettina Speckmann, et al. "SolarView: Low Distortion Radial Embedding with a Focus." IEEE Transactions on Visualization and Computer Graphics 25, no. 10 (2019): 2969–82. http://dx.doi.org/10.1109/tvcg.2018.2865361.

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Shih, Frank Y., and Xin Zhong. "Intelligent Watermarking for High-Capacity Low-Distortion Data Embedding." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 05 (2016): 1654003. http://dx.doi.org/10.1142/s0218001416540033.

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Image watermarking intends to hide secret data for the purposes of copyright protection, image authentication, data privacy, and broadcast monitoring. The ultimate goal is to achieve highest embedding capacity and lowest image distortion. In this paper, we present an intelligent watermarking scheme which can automatically analyze an image content to extract significant regions of interest (ROIs). A ROI is an area involving crucial information, and will be kept intact. The remaining regions of non-interest (RONIs) are collated for embedding watermarks, and will be ranked according to their entropy fuzzy memberships into a degree of importance. They are embedded by different amounts of bits to achieve optimal watermarking. The watermark is compressed and embedded in the frequency domain of the image. Experimental results show that the proposed technique has accomplished high capacity, high robustness, and high PSNR (peak signal-to-noise ratio) watermarking.
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Li, Wan Qi, Heng Wang, Che Nian, Huang Wei, and Hong Yao You. "Minimizing the Embedding Impact Using Network Flow Algorithms." Advanced Materials Research 341-342 (September 2011): 478–83. http://dx.doi.org/10.4028/www.scientific.net/amr.341-342.478.

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A novel method of minimizing the embedding impact is proposed in this paper. Optimal embedding is achieved using network flow algorithms by considering the modifications on the cover image as flows of pixels among different states. This method is not an independent steganographic scheme, but rather it minimizes the embedding impact after the embedding process and it’s compatible with the majority of embedding techniques. Due to its dependence on the embedding process, many optimization problems, such as the minimization of a globally interactive distortion function, that are intractable during the embedding process can be solved with relatively low computational cost by rectifying the modifications on the cover image after the embedding process. A distortion function based on Kullback-Leibler divergence is provided as a concrete example to illustrate the basic idea of this method.
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Nguyen, Dinh-Chien, Thai-Son Nguyen, Chin-Chen Chang, Huan-Sheng Hsueh, and Fang-Rong Hsu. "High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift." Security and Communication Networks 2018 (August 1, 2018): 1–11. http://dx.doi.org/10.1155/2018/2029869.

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Data hiding is a technique that allows secret data to be delivered securely by embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high embedding capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of I frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the embedding group and the averting group. The embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced embedding capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.
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Hu, Yongjin, Xiyan Li, and Jun Ma. "A Novel LSB Matching Algorithm Based on Information Pre-Processing." Mathematics 10, no. 1 (2021): 8. http://dx.doi.org/10.3390/math10010008.

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This paper analyzes random bits and scanned documents, two forms of secret data. The secret data were pre-processed by halftone, quadtree, and S-Box transformations, and the size of the scanned document was reduced by 8.11 times. A novel LSB matching algorithm with low distortion was proposed for the embedding step. The golden ratio was firstly applied to find the optimal embedding position and was used to design the matching function. Both theory and experiment have demonstrated that our study presented a good trade-off between high capacity and low distortion and is superior to other related schemes.
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Wang, Ruosong, та David P. Woodruff. "Tight Bounds for ℓ 1 Oblivious Subspace Embeddings". ACM Transactions on Algorithms 18, № 1 (2022): 1–32. http://dx.doi.org/10.1145/3477537.

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An \ell _p oblivious subspace embedding is a distribution over r \times n matrices \Pi such that for any fixed n \times d matrix A , \[ \Pr _{\Pi }[\textrm {for all }x, \ \Vert Ax\Vert _p \le \Vert \Pi Ax\Vert _p \le \kappa \Vert Ax\Vert _p] \ge 9/10, \] where r is the dimension of the embedding, \kappa is the distortion of the embedding, and for an n -dimensional vector y , \Vert y\Vert _p = (\sum _{i=1}^n |y_i|^p)^{1/p} is the \ell _p -norm. Another important property is the sparsity of \Pi , that is, the maximum number of non-zero entries per column, as this determines the running time of computing \Pi A . While for p = 2 there are nearly optimal tradeoffs in terms of the dimension, distortion, and sparsity, for the important case of 1 \le p \lt 2 , much less was known. In this article, we obtain nearly optimal tradeoffs for \ell _1 oblivious subspace embeddings, as well as new tradeoffs for 1 \lt p \lt 2 . Our main results are as follows: (1) We show for every 1 \le p \lt 2 , any oblivious subspace embedding with dimension r has distortion \[ \kappa = \Omega \left(\frac{1}{\left(\frac{1}{d}\right)^{1 / p} \log ^{2 / p}r + \left(\frac{r}{n}\right)^{1 / p - 1 / 2}}\right). \] When r = {\operatorname{poly}}(d) \ll n in applications, this gives a \kappa = \Omega (d^{1/p}\log ^{-2/p} d) lower bound, and shows the oblivious subspace embedding of Sohler and Woodruff (STOC, 2011) for p = 1 is optimal up to {\operatorname{poly}}(\log (d)) factors. (2) We give sparse oblivious subspace embeddings for every 1 \le p \lt 2 . Importantly, for p = 1 , we achieve r = O(d \log d) , \kappa = O(d \log d) and s = O(\log d) non-zero entries per column. The best previous construction with s \le {\operatorname{poly}}(\log d) is due to Woodruff and Zhang (COLT, 2013), giving \kappa = \Omega (d^2 {\operatorname{poly}}(\log d)) or \kappa = \Omega (d^{3/2} \sqrt {\log n} \cdot {\operatorname{poly}}(\log d)) and r \ge d \cdot {\operatorname{poly}}(\log d) ; in contrast our r = O(d \log d) and \kappa = O(d \log d) are optimal up to {\operatorname{poly}}(\log (d)) factors even for dense matrices. We also give (1) \ell _p oblivious subspace embeddings with an expected 1+\varepsilon number of non-zero entries per column for arbitrarily small \varepsilon \gt 0 , and (2) the first oblivious subspace embeddings for 1 \le p \lt 2 with O(1) -distortion and dimension independent of n . Oblivious subspace embeddings are crucial for distributed and streaming environments, as well as entrywise \ell _p low-rank approximation. Our results give improved algorithms for these applications.
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Zhang, Shun, Liang Yang, Xihao Xu, and Tiegang Gao. "Secure Steganography in JPEG Images Based on Histogram Modification and Hyper Chaotic System." International Journal of Digital Crime and Forensics 10, no. 1 (2018): 40–53. http://dx.doi.org/10.4018/ijdcf.2018010104.

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Security always plays an important role in the communication. Steganography, which conceals the process of communication, is another efficient way to achieve secure communication besides encryption. This paper proposes a secure steganography scheme in JPEG images with high embedding capacity and low distortion to the cover image. It embeds the additional information by modifying the DCT coefficients in JPEG images. Considering the size of the additional information, some DCT coefficients are adaptively selected in the embedding process. Two chaotic encryption strategies are designed based on the hyper-chaotic system to encrypt the additional information before the embedding to enhance the security. Extensive experiments have demonstrated the validity and efficiency of this proposed scheme. Compared with some existing schemes, it offers larger embedding rate and lower distortion with stronger security.
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Yang, Yuhang, Xuyu Xiang, Jiaohua Qin, Yun Tan, Zhangdong Wang, and Yajie Liu. "High-Embedded Low-Distortion Multihistogram Shift Video Reversible Data Hiding Based on DCT Coefficient." Electronics 12, no. 7 (2023): 1652. http://dx.doi.org/10.3390/electronics12071652.

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Video reversible data hiding technology can be applied to copyright protection, medical images, the military, and other fields, but it cannot guarantee high visual quality with an effective embedded capacity. In this paper, a high-embedding and low-distortion reversible data hiding scheme based on a discrete cosine transform (DCT) coefficients method is proposed. The scheme first decodes the original video stream with entropy, obtains all the DCT blocks, and selects the embeddable DCT blocks according to the capacity of the zero factor. Then, it divides the coefficients in the DCT blocks into the shift and embedding coefficients. The shift coefficients directly generate a one-dimensional histogram; the embedding coefficients generate a two-dimensional histogram according to paired strategies. Finally, the secret data can be successfully embedded according to the proposed two-dimensional histogram shift reversible data hiding scheme. This scheme performed more effectively than existing schemes in terms of the embedded capacity, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM).
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Tsai, Yuan-Yu, Yao-Hsien Huang, Ruo-Jhu Lin, and Chi-Shiang Chan. "An Adjustable Interpolation-based Data Hiding Algorithm Based on LSB Substitution and Histogram Shifting." International Journal of Digital Crime and Forensics 8, no. 2 (2016): 48–61. http://dx.doi.org/10.4018/ijdcf.2016040105.

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Data hiding can be regarded as a type of image processing techniques. Other image processing operations are usually integrated to increase the embedding capacity or decrease the visual distortion. Interpolation is an example of this type of operation. However, previous interpolation-based data hiding algorithms suffered from low and fixed embedding capacity and high visual distortion. This study proposes a more effective two-stage data hiding algorithm based on interpolation, LSB substitution, and histogram shifting. First, the authors modify the formula for embedding capacity calculation and make some adjustments on the sample pixels determination. A threshold is used to obtain the block complexity and each embeddable pixel has a different amount of message embedded. Second, an LSB substitution method and an optimal pixel adjustment process are adopted to raise the image quality. Finally, the authors' proposed algorithm can support adjustable embedding capacity. Compared to the previous algorithm, the experimental results demonstrate the feasibility of the proposed method.
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Wu, Nan-I., Kuo-Chen Wu, and Chung-Ming Wang. "Exploring pixel-value differencing and base decomposition for low distortion data embedding." Applied Soft Computing 12, no. 2 (2012): 942–60. http://dx.doi.org/10.1016/j.asoc.2011.09.002.

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Thèses sur le sujet "Low-distortion embedding"

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Carpenter, Timothy E. "Algorithms For Low-Distortion Embeddings Into Geometrically Restricted Spaces." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555337435997622.

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Sidiropoulos, Anastasios. "Approximation algorithms for low-distortion embeddings into low-dimensional spaces." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34126.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Includes bibliographical references (p. 33-35).<br>We present several approximation algorithms for the problem of embedding metric spaces into a line, and into the two-dimensional plane. We give an O([square root] n)-approximation algorithm for the problem of finding a line embedding of a metric induced by a given unweighted graph, that minimizes the (standard) multiplicative distortion. For the same problem, we give an exact algorithm, with running-time exponential in the distortion. We complement these results by showing that the problem is NP-hard to [alpha]-approximate, for some constant [alpha] > 1. For the two-dimensional case, we show a O([square root] n) upper bound for the distortion required to embed an n-point subset of the two-dimensional sphere, into the plane. We prove that this bound is asymptotically tight, by exhibiting n-point subsets such that any embedding into the plane has distortion [omega]([square root] n). These techniques yield a O(1)-approximation algorithm for the problem of embedding an n-point subset of the sphere into the plane.<br>by Anastasios Sidiropoulos.<br>S.M.
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Yan, Yiqing. "Scalable and accurate algorithms for computational genomics and dna-based digital storage." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS078.

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La réduction des coûts et l'amélioration du débit de la technologie de séquençage ont entraîné de nouvelles avancées dans des applications telles que la médecine de précision et le stockage basé sur l'ADN. Cependant, le résultat séquencé contient des erreurs. Pour mesurer la similitude entre le résultat séquencé et la référence, la distance d'édition est préférée en pratique à la distance de Hamming en raison des indels. Le calcul de la distance d'édition est complexe quadratique. Par conséquent, l'analyse de similarité de séquence nécessite beaucoup de calculs. Dans cette thèse, nous introduisons deux algorithmes d'analyse de similarité de séquence précis et évolutifs, i) Accel-Align, un mappeur et un aligneur de séquence rapide basé sur la méthodologie seed–embed–extend, et ii) Motif-Search, une structure-efficace algorithme conscient pour récupérer les informations codées par les motifs composites à partir de l'archive ADN. Ensuite, nous utilisons Accel-Align comme un outil efficace pour étudier la conception d'accès aléatoire dans le stockage basé sur l'ADN<br>Cost reduction and throughput improvement in sequencing technology have resulted in new advances in applications such as precision medicine and DNA-based storage. However, the sequenced result contains errors. To measure the similarity between the sequenced result and reference, edit distance is preferred in practice over Hamming distance due to the indels. The primitive edit distance calculation is quadratic complex. Therefore, sequence similarity analysis is computationally intensive. In this thesis, we introduce two accurate and scalable sequence similarity analysis algorithms, i) Accel-Align, a fast sequence mapper and aligner based on the seed–embed–extend methodology, and ii) Motif-Search, an efficient structure-aware algorithm to recover the information encoded by the composite motifs from the DNA archive. Then, we use Accel-Align as an efficient tool to study the random access design in DNA-based storage
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Ke, Yen-Ching, and 柯衍慶. "A Study of Low Distortion or Distortion-free Data Embedding Algorithms for High Dynamic Range Images." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/11542322514894594244.

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碩士<br>國立中興大學<br>資訊網路多媒體研究所<br>100<br>In this paper, we investigate data embedding algorithms for high dynamic range images encoded by the RGBE image format. We present four algorithms that have the distortion-free feature and one algorithm that demonstrates the feature of very low distortion. Our first algorithm belongs to the distortion-free manner. In this algorithm, we make use of all statuses produced by the pixel variation and employ triplet coding technology to increase the embedding capacity. Comparing with the previous work, our algorithm can improve the embedding capacity in the range between 5.52% and 5.79%. No image distortion is encountered when tone mapping the high dynamic range embedded images to produce the low dynamic range embedded image. The second algorithm we introduce belongs to the distortion-free manner. In this algorithm, we take advantages of the “null” pixel, a new pixel category produced by the E channel, where we embed messages into these pixels to expand the embedding capacity. Experimental results show that comparing to our counterparts, our algorithm can offer an average of 48.37% embedding capacity without causing any image distortion. The third algorithm we develop belongs to the very low distortion manner. We adopt an optimization computation mechanism for the R, G, B channels to generate a number of potential pixels, referred to as “promising” and “feasible” pixels. These pixels cause the least image distortion when operating the message embedding. Comparing to our counterparts, the algorithm can largely increase the amount of embedding capacity with the magnitude between 2.77 and 3.02. The tone mapped image presents high PSNR values (76.60~84.44 dB) showing no perceivable visual difference. The final algorithm we propose is with the distortion-free manner. We take advantage of homogeneous pixel representation and combine a group of M pixels (M>=2) as a pixel cluster to generate sufficient statuses for message embedding. This approach allows us to adopt the triplet coding technique to increase the embedding capacity without incurring any image distortion. We compare our scheme of using 2 pixels as a cluster with previous results of using a single pixel. The comparison indicates that our algorithm can provide larger payloads in the range of 317~2397 bits. We adopt the tone mapping scheme to produce low dynamic range images to quantize the image difference, and we employ the HDR-VDP technique to inspect the visual difference between the cover and stego images. The image difference quantization results show that no distortion is encountered. The probability map produced by HDR-VDP inspection is in grey color indicating that the detection probability of visual difference is null. In conclusion, our work offers the following four contributions: we exploit the triplet coding technology and increase the capacity for non-distortion algorithm; we make use of a new pixels to convey messages, raising the embedding capacity; we develop the optimization computation mechanism fully using pixels not available in our counterpart to further increase the embedding capacity; we adopt the pixel cluster scheme allowing the increase of concealed messages without causing image distortion. The four algorithms developed are adequate for applications of image annotation and image steganography.
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JHANG, YONG, and 張顒. "A Study of Data Hiding Algorithm with High Embedding Capacity and Low Distortion." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/08892940439139247182.

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碩士<br>稻江科技暨管理學院<br>數位內容設計與管理學系研究所<br>102<br>In this thesis, a novel data hiding method, designed base on human visual perception and capable of offering high invisibility, is proposed to enable the user to conceal large amounts of secret data into edge areas of still images. In order to achieve a higher payload and to obtain a better stego image quality, the principle of payload allotment is to hide more data into edge areas than smooth areas, thus serving the ultimate purpose of maintaining human imperceptibility to the distortion in the image caused by the embedding of the secret message. In our new scheme, we utilize the pixel-value differencing to determine the payload of a pixel pair. The higher difference values the areas are, the large the messages are hidden, and vice versa. In the embedding algorithm, the binary secret data is transferred into non-decimal number system and then hid into each pixel pair using modulus function. Since the characteristics of the pixel pairs remain the same after the secret data is hidden, the proposed scheme qualifies as a so-called "blind" scheme, meaning that the presence of the original image is not required in the extraction procedure. The experiments we conducted have demonstrated that the proposed scheme is indeed capable of hiding more data while keeping down the stego-image distortion and remaining the imperceptibility. The performance of the proposed scheme, compared with those of the existing techniques, proving that our scheme is not only feasible but better.
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Chapitres de livres sur le sujet "Low-distortion embedding"

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Faragó, András. "Low Distortion Metric Embedding into Constant Dimension." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20877-5_12.

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Sarkar, Rik. "Low Distortion Delaunay Embedding of Trees in Hyperbolic Plane." In Graph Drawing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25878-7_34.

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Babilon, Robert, Jiří Matoušek, Jana Maxová, and Pavel Valtr. "Low-Distortion Embeddings of Trees." In Graph Drawing. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45848-4_27.

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Bhattacharya, Arnab, Purushottam Kar, and Manjish Pal. "On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03573-9_13.

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Wu, Hanzhou. "Graph Models in Information Hiding." In Graph Theory [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98592.

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Information hiding allows us to hide secret information into digital objects such as images without significantly distorting the objects. The object containing hidden information will be transmitted to a data receiver via a probably insecure channel. To securely transmit the object carrying hidden information, the distortion caused by data embedding should be as low as possible, which is referred to as the rate-distortion optimization problem. Many conventional methods optimize the data embedding procedure by a heuristic fashion, which may be not optimal in terms of the rate-distortion performance. In this chapter, we introduce novel approaches that use graph theory for information hiding. These graph models are general and can be used for improving the rate-distortion performance of information hiding systems. In addition to rate-distortion optimization, recent graph models used for system design of information hiding will be also reviewed. This chapter is intended as a tutorial introducing advanced graph models applied to information hiding.
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Babilon, Robert, Jiří Matoušek, Jana Maxová, and Pavel Valtr. "Low-Distortion Embeddings of Trees." In Graph Algorithms and Applications 4. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773296_0018.

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Diwaker, Ritesh, and Deepak Asrani. "Multimedia Security in Audio Signal." In Artificial intelligence and Multimedia Data Engineering. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815196443123010008.

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The security of Digital media has been varying continuously due to advanced malware attacks. Multimedia security has become one of the major concerns since new technologies are introduced. The proposed paper applied the watermarking technique in digital audio signals in which unique data is inserted in one-dimensional data in such a way that it must not affect the major information of the audio signal. The hybrid decomposition scheme has been applied to the audio data in order to extract features in terms of energy bands. The data is kept hidden in a low significant energy band that contains less information. This watermarking technique ensures the ownership of the multimedia data. Only authorized authors can be able to claim ownership of the audio data. The correct authorization of audio data can be proven by the extraction method in which the hidden watermark data has been extracted back to its original form without leaving any distortion in audio data. The proposed work introduces a hybrid approach to watermarking 2D data into an audio file. A hybrid audio decomposition technique was introduced by the proposed scheme in which a dual form of audio decomposition method has been applied containing Fast Fourier transform (FFT) and Cordic QR scheme. The correct location from the energy band has been found to embed the watermark data. Before the embedding procedure, the watermarking data has been selected. The proposed method selects an image containing information as a watermark that is first encrypted before initiating the embedding process. Watermark Encryption has been done using a cyclic coding algorithm and Arnold’s cat map. The disintegration of the audio file will finally result in Q and R matrices. Both such matrices are of orthogonal type. Then, the encrypted watermark data has been implanted in a random fashion in the R component of decomposed audio data during the embedding process. The inverse procedure has been applied for the watermark extraction and decryption process.
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Indyk, Piotr, and Ji_í Matou_ek. "Low-Distortion Embeddings of Finite Metric Spaces." In Handbook of Discrete and Computational Geometry, Second Edition. Chapman and Hall/CRC, 2004. http://dx.doi.org/10.1201/9781420035315.ch8.

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"Low-Distortion Embeddings of Finite Metric Spaces." In Handbook of Discrete and Computational Geometry, Second Edition. Chapman and Hall/CRC, 2004. http://dx.doi.org/10.1201/9781420035315-8.

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Actes de conférences sur le sujet "Low-distortion embedding"

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Koranne, S. "Analysis of very large resistive networks using low distortion embedding." In 2013 14th International Symposium on Quality Electronic Design (ISQED 2013). IEEE, 2013. http://dx.doi.org/10.1109/isqed.2013.6523659.

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Ostrovsky, Rafail, and Yuval Rabani. "Low distortion embeddings for edit distance." In the thirty-seventh annual ACM symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1060590.1060623.

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Braunsmann, Juliane, Marko Rajkovic, Martin Rumpf, and Benedikt Wirth. "Learning low bending and low distortion manifold embeddings." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2021. http://dx.doi.org/10.1109/cvprw53098.2021.00498.

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Indyk, P. "Algorithmic applications of low-distortion geometric embeddings." In Proceedings 42nd IEEE Symposium on Foundations of Computer Science. IEEE, 2001. http://dx.doi.org/10.1109/sfcs.2001.959878.

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Rousselot, S., D. Truffi, G. Doulgeris, S. Mistry, V. Pachidis, and P. Pilidis. "Generation of a Quasi 3-D Map of a Half-Embedded Ultra High Bypass Ratio Turbofan Intake on the Wing of a Broad Delta Wing Airframe." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51008.

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The need for low fuel consumption, emissions and noise drives future propulsion systems towards ultra high bypass ratio turbofan configurations. One of the arising challenges is the installation of such an engine, due to its high diameter. An alternative to under-the-wing podded installation is half embedding it into a thick wing. An ideal airframe has been found to be the Broad Delta (BD) wing, featuring high wing-root thickness. Two conventional nacelles have been integrated into each wing of a four-engine BD body. The performance of a half embedded turbofan intake has been studied, with the use of 3-D Computational Fluid Dynamics. This qualitative analysis comprises of full scale aircraft simulation with special focus on the flow-field upstream and inside the novel installation. The study required the creation of a detailed map of the intake for cruise and take-off flight conditions. The map comprises of radial pressure recovery profiles in various circumferential positions for enhanced representation of fan-inlet total pressure distortion. It is produced using a decoupled zooming process, where ‘matching’ between a 0-D gas turbine performance code and 3-D CFD is achieved for each operating point.
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Bǎdoiu, Mihai, Julia Chuzhoy, Piotr Indyk, and Anastasios Sidiropoulos. "Low-distortion embeddings of general metrics into the line." In the thirty-seventh annual ACM symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1060590.1060624.

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Fawzi, Omar, Patrick Hayden, and Pranab Sen. "From low-distortion norm embeddings to explicit uncertainty relations and efficient information locking." In the 43rd annual ACM symposium. ACM Press, 2011. http://dx.doi.org/10.1145/1993636.1993738.

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Meng, Xiangrui, and Michael W. Mahoney. "Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression." In the 45th annual ACM symposium. ACM Press, 2013. http://dx.doi.org/10.1145/2488608.2488621.

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