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Bartan, Burak, Pilanci, Mert.  2019.  Distributed Black-Box optimization via Error Correcting Codes. 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). :246—252.
We introduce a novel distributed derivative-free optimization framework that is resilient to stragglers. The proposed method employs coded search directions at which the objective function is evaluated, and a decoding step to find the next iterate. Our framework can be seen as an extension of evolution strategies and structured exploration methods where structured search directions were utilized. As an application, we consider black-box adversarial attacks on deep convolutional neural networks. Our numerical experiments demonstrate a significant improvement in the computation times.
Selvi J., Anitha Gnana, kalavathy G., Maria.  2019.  Probing Image and Video Steganography Based On Discrete Wavelet and Discrete Cosine Transform. 2019 Fifth International Conference on Science Technology Engineering and Mathematics (ICONSTEM). 1:21–24.

Now-a-days, video steganography has developed for a secured communication among various users. The two important factor of steganography method are embedding potency and embedding payload. Here, a Multiple Object Tracking (MOT) algorithmic programs used to detect motion object, also shows foreground mask. Discrete wavelet Transform (DWT) and Discrete Cosine Transform (DCT) are used for message embedding and extraction stage. In existing system Least significant bit method was proposed. This technique of hiding data may lose some data after some file transformation. The suggested Multiple object tracking algorithm increases embedding and extraction speed, also protects secret message against various attackers.

F. Hassan, J. L. Magalini, V. de Campos Pentea, R. A. Santos.  2015.  "A project-based multi-disciplinary elective on digital data processing techniques". 2015 IEEE Frontiers in Education Conference (FIE). :1-7.

Todays' era of internet-of-things, cloud computing and big data centers calls for more fresh graduates with expertise in digital data processing techniques such as compression, encryption and error correcting codes. This paper describes a project-based elective that covers these three main digital data processing techniques and can be offered to three different undergraduate majors electrical and computer engineering and computer science. The course has been offered successfully for three years. Registration statistics show equal interest from the three different majors. Assessment data show that students have successfully completed the different course outcomes. Students' feedback show that students appreciate the knowledge they attain from this elective and suggest that the workload for this course in relation to other courses of equal credit is as expected.