Privacy-utility tradeoff method using multi-variable source coding by Yong-hao GU, Jiu-chuan LIN

“…In the age of big data,data providers need to ensure their privacy,while data analysts need to mine the value of data.So,how to find the privacy-utility tradeoff has become a research hotspot.Current works mostly focus on privacy preserving methods,ignoring the data utility.Based on the current research of privacy utility equilibrium methods,a privacy-utility tradeoff method using multi-variable source coding was proposed to solve the problem that different public datasets in the same database have different privacy requirements.Two results are obtained by simulations.The first result is that the greater the association degree between the private information and public information,the increase of the distortion degree of public information will significantly improve the effect of privacy preservation.The second result is that public information with larger variance should be less distorted to ensure more utility.…”
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Enhanced Distributed Computation for Machine Learning: Coded Strategies and Multidisciplinary Impact by Tian Xiaolin

“…It discusses two primary concepts: coded multiplication and data shuffling, along with a non-linear core to Random Access Memory (RAM) approach, presenting new avenues for future research. …”
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The Uses Of Code Mixing On Facebook By The Students In English Language Education Department by Ida Bagus Putu Arjun Adinata, Dewa Putu Ramendra, Gede Mahendrayana

“… This study intended to analyze types of code-mixing and determine the motive of code-mixing used by the seventh-semester students of English Language Education on Facebook. …”
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BEHAVE - facilitating behaviour coding from videos with AI-detected animals by Reinoud Elhorst, Martyna Syposz, Katarzyna Wojczulanis-Jakubas

“…Due to these advantages, the behaviour coding process can be significantly accelerated, resulting in well-organised and readily exportable/importable data.…”
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An Adaptive Opportunistic Network Coding Mechanism in Wireless Multimedia Sensor Networks by Hang Shen, Guangwei Bai, Lu Zhao, Zhenmin Tang

“…However, some special characteristics of existing wireless network coding mechanisms degrade the performance of video data delivery. …”
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Improved information hiding algorithm based on twice positioning in coding channel by Li-quan CHEN, Miao LU, Ai-qun HU, Xiao-yan SUN

“…Based on analysis of existing information hiding algorithms and capacities in coding channel,the defects of those existing algorithms were pointed out,and an improved information hiding algorithm with capacity upper limit analysis and based on twice positioning was proposed.the proposed algorithm,the information hiding capacity upper limit is firstly computed before embedding,and used for comparison with the size of hiding secret data.Then,twice posi-tioning scheme and cyclic shift mechanism for choosing the embedding position were used in the proposed algorithm.Simulation results show that,compared with those existing algorithms,the proposed algorithm is able to avoid the risk of exposure of the secret channel caused by capacity exceeding of hiding data.It can not only improve the randomness of the embedding position,but also avoid the risk of overlap among different secret data.The hiding performances of the coding channel information hiding system are improved.…”
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Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy by Yasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, Hirokazu Fukidome, Hideitsu Hino, Masato Okada

“…Additionally, our sparse coding method learns an optimal dictionary tailored for nanostructure extraction, fine-tuning the SR process to the unique characteristics of the data, even with noise and limited samples. …”
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Mathematical model of hidden, noiseproof information transfer provided in the modular code by Jurii Evgenevich Ryabinin, Oleg Anatolievich Finko

“…This task solving method is excessive modular coding of data built in steganographic containers of different file formats (jpeg, mp3, avi, mpeg4, etc.) and of different potential capacity (by choosing modules sizes). …”
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Convolutional sparse coding network for sparse seismic time-frequency representation by Qiansheng Wei, Zishuai Li, Haonan Feng, Yueying Jiang, Yang Yang, Zhiguo Wang

“…Seismic time-frequency (TF) transforms are essential tools in reservoir interpretation and signal processing, particularly for characterizing frequency variations in non-stationary seismic data. Recently, sparse TF transforms, which leverage sparse coding (SC), have gained significant attention in the geosciences due to their ability to achieve high TF resolution. …”
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Constraints in code-switching: a case study from Basque and Spanish by Arrate Isasi-Isasmendi, Irantzu Epelde

“… In the present study we analyze two features in Basque-Spanish code-switching data: (1) phonological mixing in intraword position involving phoneme /θ/ and (2) switches between pronouns and verbs. …”
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THE PHENOMENON OF CODE-MIXING ON YOUTUBE CASTER OF CLARA MONGSTAR AND RANGER EMAS by Alif Rahmadhani, Desi Arintawati, Fiona Puspitasari Mulyadi, Ginarsiwi Mayangseto, Ratini Setyowati

“…The data from this research is the YouTube video of Clara Mongstar and the Gold Ranger in 2020. …”
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Detect Windows Code Injection by Cross-validating Stack and VAD Information by ZHAI Jiqiang, HAN Xu, WANG Jiaqian, SUN Haixu, YANG Hailu

“…Then the data is combined with the process VAD structure to detect the function return address and match the file name to locate the injected code. …”
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Systematic librarian-led zip code analysis to target underserved communities by Rachel Roberts, Kelsey L. Grabeel

“…Researchers gathered the health information service’s 2022 data, which was de-identified. Data analyzed included zip code and customer topics, which were coded according to the hospital’s business line, which was defined as why a patient was hospitalized or used the ED.  …”
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Malicious code within model detection method based on model similarity by Degang WANG, Yi SUN, Chuanxin ZHOU, Qi GAO, Fan YANG

“…The privacy of user data in federated learning is mainly protected by exchanging model parameters instead of source data.However, federated learning still encounters many security challenges.Extensive research has been conducted to enhance model privacy and detect malicious model attacks.Nevertheless, the issue of risk-spreading through malicious code propagation during the frequent exchange of model data in the federated learning process has received limited attention.To address this issue, a method for detecting malicious code within models, based on model similarity, was proposed.By analyzing the iterative process of local and global models in federated learning, a model distance calculation method was introduced to quantify the similarity between models.Subsequently, the presence of a model carrying malicious code is detected based on the similarity between client models.Experimental results demonstrate the effectiveness of the proposed detection method.For a 178MB model containing 0.375MB embedded malicious code in a training set that is independent and identically distributed, the detection method achieves a true rate of 82.9% and a false positive rate of 1.8%.With 0.75MB of malicious code embedded in the model, the detection method achieves a true rate of 96.6% and a false positive rate of 0.38%.In the case of a non-independent and non-identically distributed training set, the accuracy of the detection method improves as the rate of malicious code embedding and the number of federated learning training rounds increase.Even when the malicious code is encrypted, the accuracy of the proposed detection method still achieves over 90%.In a multi-attacker scenario, the detection method maintains an accuracy of approximately 90% regardless of whether the number of attackers is known or unknown.…”
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Characterization of human pseudogene-derived non-coding RNAs for functional potential. by Xingyi Guo, Mingyan Lin, Shira Rockowitz, Herbert M Lachman, Deyou Zheng

“…To explore these issues systematically, we first developed a computational pipeline to identify transcribed pseudogenes from RNA-Seq data. Applying the pipeline to datasets from 16 distinct normal human tissues identified ∼ 3,000 pseudogenes that could produce non-coding RNAs in a manner of low abundance but high tissue specificity under normal physiological conditions. …”
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Unveiling the Need of Synonym in Code Mixing in the Movie ‘Yowis Ben Finale’ by Dwi Putri Fatmawati, Dyah ‘Ainun Rohimah, Efazetta Fazafaza, Jaizah Nasywa, Teguh Sarosa

“…Using a descriptive qualitative approach, this research method systematically analyzes factual information to accurately interpret the integration of Indonesian and Javanese in the film. Primary data were collected by observing the movie video and taking notes on the scripts containing code-mixing. …”
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Deep learning techniques for sentiment analysis in code-switched Hausa-English tweets by Yusuf Aliyu, Aliza Sarlan, Kamaluddeen Usman Danyaro, Abdullahi Sani abd Rahman, Aminu Aminu Muazu, Mustapha Yusuf Abubakar

“…Prior research has predominantly concentrated on sentiment analysis within single-language data rather than code-switched data. This paper proposes an efficient hyperparameter tuning framework and a novel stemming algorithm for the Hausa language. …”
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Code-switching Habits in Group Discussions by Students of English as Foreign Language by Rahmawansyah Sahib, Andi Miftahul Maulidil Mursyid, Wira Kafryawan, Najiba Nawing

“…The data analysis showed that students used five code-switching types, namely situational code-switching, metaphorical code-switching, intra-sentential code-switching, inter-sentential code-switching, and tag switching. …”
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Effects of Robotic Coding on Computational Thinking Skills of Secondary School Students by Serhat Altıok, Memet Üçgül

“…Data were collected before and after the robotic coding activities using the Self-Efficacy Perception Scale for Computational Thinking Skills (SEPSCTS) instrument, comprising 36 items categorized into five factors. …”
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Allelic expression of deleterious protein-coding variants across human tissues. by Kimberly R Kukurba, Rui Zhang, Xin Li, Kevin S Smith, David A Knowles, Meng How Tan, Robert Piskol, Monkol Lek, Michael Snyder, Daniel G Macarthur, Jin Billy Li, Stephen B Montgomery

“…This study demonstrates the potential importance of transcriptome data to the interpretation of pathogenic protein-coding variants.…”
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