Intra-Sentential and Intra-Lexical Code Mixing in Nessie Judge’s YouTube Video Entitled “Lagu Populer + Pesan Iblis Tersembunyi”

As a linguistic phenomenon, code mixing is common to be identified in language users. Furthermore, YouTube as one of the online platforms has become an environment rich with the use of code mixing. Considering that YouTube might influence the language use in its audience, the following study aimed to identify the use of code-mixing presented by Indonesian content creator named Nessie Judge. Following the qualitative analysis research from Miles, Huberman, & Saldana (2014), the recent study identified the types of code mixing as presented by Hoffman namely, Intra-sentential code-mixing and Intra-lexical code-mixing. The present study identified the use of code mixing type intra-sentential and -lexical uttered by the speaker. From 114 utterances made by Nessie Judge in her video, code-mixing was identified in 86 utterances, where 53 utterances belong to intra-sentential code mixing and 13 utterances belonged to intra-lexical code mixing. The analysis revealed that the use of code mixing might be rooted in the speakers’ inability to find the equivalent words while discussing the video content. By looking at the number of the data percentage, intra-sentential code-mixing had more data than intra-lexical code-mixing meaning that the use of intra-sentential code-mixing was more common rather than intra-lexical code-mixing. It can be concluded because the speaker in the video inserts English words at the end of sentences or in the middle of sentences most of the time. The speaker on the video was clearly seen mixed Indonesian words with English words without changing the structure or context of the sentences.

Abnormality detection method for transmission lines based on video code stream analysis

As the demand for electricity continues to grow, the coverage of transmission lines is getting larger. Despite the continuous improvement of the grid system, transmission lines are still vulnerable to various natural disasters. At the same time, many transmission lines are installed in areas with harsh environments and other places that are difficult for operation and maintenance personnel to reach, which brings huge challenges to the operation and maintenance of transmission lines. Therefore, how to effectively detect the status of the transmission line and ensure the normal operation of the power grid has become an important research topic in the power system. The existing video surveillance-based methods need to decode the video, which has poor real-time performance. Therefore, this paper proposes a transmission line abnormality monitoring method based on video stream analysis. Using the extracted parameters for judgment before decoding the video stream can effectively improve the real-time performance of online monitoring of the transmission line and greatly shorten the time required for abnormal alarms.

A Semantic Watermarking Technique for Authenticating Video of H.264

A novel watermarking technique to authenticate video of H.264 is presented in this paper, using Uniform Content Locator (UCL) to semantically indexing video content and dual watermarks to preserve and enhance video content integrity and authentication. UCL index information is firstly extracted from video content and is formatted as semantic watermark to be embedded in video content. The UCL watermark is regarded as robust watermark and is then embedded into medium frequencies of DCT-coefficients of H.264 video I-frames in order to protect video attributes property (e.g., video author, copyright, content category). Features information obtained from the previously watermarked DCT-coefficients are treated as fragile watermark and are embedded into the motion vectors of H.264 video P-frames in order to ensure video secrecies (e.g., video integrity, authentication). Experiments demonstrate that this proposed technique can fulfill the requirements of H.264 video authentication and has negligible effects on video code rate change and content distortion.