Relevant bibliographies by topics / MFCC

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'MFCC'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "MFCC"

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Lankala, Srinija, and Dr M. Ramana Reddy. "Design and Implementation of Energy-Efficient Floating Point MFCC Extraction Architecture for Speech Recognition Systems." International Journal for Research in Applied Science and Engineering Technology 10, no. 9 (2022): 1217–25. http://dx.doi.org/10.22214/ijraset.2022.46807.

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Abstract: This brief presents an energy-efficient architecture to extract mel-frequency cepstrum coefficients (MFCCs) for realtime speech recognition systems. Based on the algorithmic property of MFCC feature extraction, the architecture is designed with floating-point arithmetic units to cover a wide dynamic range with a small bit-width. Moreover, various operations required in the MFCC extraction are examined to optimize operational bit-width and lookup tables needed to compute nonlinear functions, such as trigonometric and logarithmic functions. In addition, the dataflow of MFCC extraction
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ANCA, DUMITRU, DINU AURELIA, IURESCU IOANA C., and TOADER STEFAN. "Investigation of polypyrrole/TiO2 and poypyrrole/WO3 nanocomposites as anode modifier in salt bridge microbial fuel cell using municipal wastewater." Romanian Reports in Physics 76, no. 1 (2024): 502. http://dx.doi.org/10.59277/romrepphys.2024.76.502.

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Developing nanocomposite materials based on conducting polymers (CPs) and metal-oxide nanoparticles, which combine redox electrochemistry of CPs with intrinsic properties of nano-scale semiconducting materials, may offer improved microbial fuel cells (MFCs) performances. Polypyrrole (PPY) based nanocomposites were synthesized by chemical oxidative polymerization method and were further used as an anode modifier in salt bridge MFCs. The PPY-based nanocomposites were characterized by X-ray diffraction, Fourier-Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy (SEM). The ma
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Chu, Yun Yun, Wei Hua Xiong, Wei Wei Shi, and Yu Liu. "The Extraction of Differential MFCC Based on EMD." Applied Mechanics and Materials 313-314 (March 2013): 1167–70. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.1167.

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Feature extraction is the key to the object recognition. How to obtain effective, reliable characteristic parameters from the limited measured data is a question of great importance in feature extraction. This paper presents a method based on Empirical Mode Decomposition (EMD) for the extraction of Mel Frequency Cepstrum Coefficients (MFCCs) and its first order difference from original speech signals that contain four kinds of emotions such as anger, happiness, surprise and natural for emotion recognition. And the experiments compare the recognition rate of MFCC, differential MFCC (Both of the
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Mohammed, Duraid Y., Khamis Al-Karawi, and Ahmed Aljuboori. "Robust speaker verification by combining MFCC and entrocy in noisy conditions." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): 2310–19. http://dx.doi.org/10.11591/eei.v10i4.2957.

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Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, wit
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Duraid, Y. Mohammed, Al-Karawi Khamis, and Aljuboori Ahmed. "Robust speaker verification by combining MFCC and entrocy in noisy conditions." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): pp. 2310~2319. https://doi.org/10.11591/eei.v10i4.2957.

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Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, wit
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Eskidere, Ömer, and Ahmet Gürhanlı. "Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features." Computational and Mathematical Methods in Medicine 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/956249.

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The Mel Frequency Cepstral Coefficients (MFCCs) are widely used in order to extract essential information from a voice signal and became a popular feature extractor used in audio processing. However, MFCC features are usually calculated from a single window (taper) characterized by large variance. This study shows investigations on reducing variance for the classification of two different voice qualities (normal voice and disordered voice) using multitaper MFCC features. We also compare their performance by newly proposed windowing techniques and conventional single-taper technique. The result
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Abdul, Zrar Khalid. "Kurdish Spoken Letter Recognition based on k-NN and SVM Model." Journal of University of Raparin 7, no. 4 (2020): 1–12. http://dx.doi.org/10.26750/vol(7).no(4).paper1.

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Automatic recognition of spoken letters is one of the most challenging tasks in the area of speech recognition system. In this paper, different machine learning approaches are used to classify the Kurdish alphabets such as SVM and k-NN where both approaches are fed by two different features, Linear Predictive Coding (LPC) and Mel Frequency Cepstral Coefficients (MFCCs). Moreover, the features are combined together to learn the classifiers. The experiments are evaluated on the dataset that are collected by the authors as there as not standard Kurdish dataset. The dataset consists of 2720 sample
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N., H. Mohd Johari, Abdul Malik Noreha, and A. Sidek K. "Distinctive features for normal and crackles respiratory sounds using cepstral coefficients." Bulletin of Electrical Engineering and Informatics 8, no. 3 (2019): 875–81. https://doi.org/10.11591/eei.v8i3.1517.

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Classification of respiratory sounds between normal and abnormal is very crucial for screening and diagnosis purposes. Lung associated diseases can be detected through this technique. With the advancement of computerized auscultation technology, the adventitious sounds such as crackles can be detected and therefore diagnostic test can be performed earlier. In this paper, Linear Predictive Cepstral Coefficient (LPCC) and Mel-frequency Cepstral Coefficient (MFCC) are used to extract features from normal and crackles respiratory sounds. By using statistical computation such as mean and standard d
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Raychaudhuri, Aryama, Rudra Narayan Sahoo, and Manaswini Behera. "Application of clayware ceramic separator modified with silica in microbial fuel cell for bioelectricity generation during rice mill wastewater treatment." Water Science and Technology 84, no. 1 (2021): 66–76. http://dx.doi.org/10.2166/wst.2021.213.

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Abstract Ceramic separators have recently been investigated as low-cost, robust, and sustainable separators for application in microbial fuel cells (MFC). In the present study, an attempt was made to develop a low-cost MFC employing a clayware ceramic separator modified with silica. The properties of separators with varying silica content (10%–40% w/w) were evaluated in terms of oxygen and proton diffusion. The membrane containing 30% silica exhibited improved performance compared to the unmodified membrane. Two identical MFCs, fabricated using ceramic separators with 30% silica content (MFCS-
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A. Hassan, Tariq, and Salam A. Hussein. "Modulation and Energy Components for Speaker Recognition System." International Journal of Advances in Scientific Research and Engineering 10, no. 08 (2024): 18–26. http://dx.doi.org/10.31695/ijasre.2024.8.3.

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This paper presents a model use the modulation and energy components for speaker recognition application, that is mainly follows theshort-term scenario in speech signal processing, and also introduce a parameter combination that includes the instantaneous components and the energy parameters. This will describe the importance of short-term speech analysis in estimating the modulation parameters and the role of the instantaneous energy in estimating the speaker-dependent parameters. Simply, the short-term scenario is used to, first; avoid the silent and background noise speech portions that pre
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Dissertations / Theses on the topic "MFCC"

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Mukherjee, Rishiraj. "Speaker Recognition Using Shifted MFCC." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4136.

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Speaker Recognition is the art of recognizing a speaker from a given database using speech as the only input. In this thesis we will be discussing a novel approach to detect speakers. Here we will introduce the concept of shifted MFCC to add improvement over the performance from previous work which has shown quite a decent amount of accuracy of about 95% at best. We will be talking about adding different parameters which also contributed in improving the efficiency of speaker recognition. Also we will be testing our algorithm on Text dependent speech data and Text Independent speech data. Our
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Tolunay, Atahan. "Text-Dependent Speaker Verification Implemented in Matlab Using MFCC and DTW." Thesis, Linköpings universitet, Informationskodning, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-60992.

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Even though speaker verification is a broad subject, the commercial and personal use implementations are rare. There are several problems that need to be solved before speaker verification can become more useful. The amount of pattern matching and feature extraction techniques is large and the decision on which ones to use is debatable. One of the main problems of speaker verification in general is the impact of noise. The very popular feature extraction technique MFCC is inherently sensitive to mismatch between training and verification conditions. MFCC is used in many speech recognition appl
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Krotký, Jan. "Dekodér pro systém detekce klíčových slov." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218176.

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The essay presents the basic characteristics of human speech recognition, describes systems for the detection of key words and further deals with the proposal of each decoder blocks divided into three chapters. The first one describes the operations that are performed before the signal distribution of the framework and the segmentation. The second chapter describes the calculation of short-term energy, the number of zero passes and self-correlative, prediction and Mel-frequency cepstral coefficients. The third chapter, which describes the design of the block decoder, describes the method of dy
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Mubarak, Omer Mohsin Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Speech and music discrimination using short-time features." Awarded by:University of New South Wales. Electrical Engineering & Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/31954.

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This thesis addresses the problem of classifying an audio stream as either speech or music, an issue which is beginning to receive increasing attention due to its wide range of applications. Various techniques have been presented in last decade to discriminate between speech and music. However, their accuracy is still not sufficient since music can refer to a very broad class of signals due to the large number of musical instruments found in audio data. Performance can also be further compromised in noisy conditions, which are unavoidable in some practical situations. This thesis presents an a
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Pan, Linlin. "Research and simulation on speech recognition by Matlab." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-16950.

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With the development of multimedia technology, speech recognition technology has increasingly become a hotspot of research in recent years. It has a wide range of applications, which deals with recognizing the identity of the speakers that can be classified into speech identification and speech verification according to decision modes.The main work of this thesis is to study and research the techniques, algorithms of speech recognition, thus to create a feasible system to simulate the speech recognition. The research work and achievements are as following: First: The author has done a lot of i
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SIQUEIRA, JAN KRUEGER. "CONTINUOUS SPEECH RECOGNITION WITH MFCC, SSCH AND PNCC FEATURES, WAVELET DENOISING AND NEURAL NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19143@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Um dos maiores desafios na área de reconhecimento de voz contínua é desenvolver sistemas robustos ao ruído aditivo. Para isso, este trabalho analisa e testa três técnicas. A primeira delas é a extração de atributos do sinal de voz usando os métodos MFCC, SSCH e PNCC. A segunda é a remoção de ruído do sinal de voz via wavelet denoising. A terceira e última é uma proposta original batizada de feature denoising, que busca melhorar os atributos extraídos usando um conjunto de redes neurais. Embora algumas dessas técnicas já sejam con
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Dobrovolskis, Martynas. "Šnekos atpažinimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050614_154005-58155.

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Voice recognition technologies appeared in the period of general device miniaturization, when all technologies were commonly integrated into one lust. There is no space for buttons and displays anymore. To have a good system of Lithuanian language recognition, a number of throughout researches must be implemented. Only after selecting the most efficient speech recognition scheme, we can proceed to the development of software adapted to the contemporary time. The aim of this paper is to determine, how efficient speech recognition is possible using neuron networks. MFCC and LPC coefficients were
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Julien, Eric. "Alignement du chant par rapport à une référence audio en temps réel." Mémoire, Université de Sherbrooke, 2013. http://hdl.handle.net/11143/6184.

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Dans l'optique de créer un système de karaoké qui modifie une interprétation chantée à capella en temps réel, il est nécessaire de pouvoir localiser l'interprète par rapport à une référence afin de pouvoir déterminer quelle serait la cible d'un algorithme de modification de la voix. Pour qu'un tel système fonctionne bien, il est nécessaire que l'algorithme d'alignement exploite au maximum les spécificités de la voix, qu'il utilise l'information liée au texte prononcé plutôt qu'aux aspects artistiques du chant, qu'il soit à temps réel et qu'il offr la plus faible latence possible. Afin d'attein
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Martins, Ana Caroline Vasconcelos. "GluA2 - Glutamatergic Receptor Study: A Molecular Approach." reponame:Repositório Institucional da UFC, 2017. http://www.repositorio.ufc.br/handle/riufc/28258.

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Submitted by José Orlando Soares de Oliveira (orlando.soares@bol.com.br) on 2017-11-30T12:23:47Z No. of bitstreams: 1 2017_tese_acvmartins.pdf: 10270409 bytes, checksum: f2b0eb40db54875e0e40a6d040ce7336 (MD5)<br>Rejected by Weslayne Nunes de Sales (weslaynesales@ufc.br), reason: A aluna optou por publicar apenas os elementos pré-textuais. on 2017-12-01T12:36:51Z (GMT)<br>Submitted by José Orlando Soares de Oliveira (orlando.soares@bol.com.br) on 2017-12-01T13:50:35Z No. of bitstreams: 1 Tese corrigida - elementos pretextuais.pdf: 159585 bytes, checksum: 9531b29bc8c5a46f5ed5753442df383f (M
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Vrba, Václav. "Robustní detekce klíčových slov v řečovém signálu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220670.

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The master thesis is divided into two parts theoretical and practical. The theoretical part is focused on methods of analysis and detection of speech signals. In the practical part the system for isolated word recognition was created in Matlab. The system is speaker independent separately for men and women. Also two speech databases were created for further use in the aircraft cockpit. Tests and evaluations were performed even with added noise.
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Books on the topic "MFCC"

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Crockett, Frank. MFC Developer's workshop. Microsoft Press, 1997.

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E, Robichaux Paul, ed. Using MFC and ATL. QUE, 1997.

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Japan. Keizai Sangyōshō. Sangyō Gijutsu Kankyōkyoku. Kankyō Chōwa Sangyō Suishinshitsu. Materiaru furō kosuto kaikei (MFCA) dōnyū jireishū. Keizai Sangyōshō Sangyō Gijutsu Kankyōkyoku Kankyō Seisakuka Kankyō Chōwa Sangyō Suishinshitsu, 2008.

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Schildt, Herbert. MFC programming from the ground up. 2nd ed. Osborne/McGraw-Hill, 1998.

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Mike, Blaszczak, ed. Professional MFC with Visual C++5. Wrox Press, 1997.

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Broquard, Victor E. Programming with MFC for Windows 95. Prentice Hall PTR, 1996.

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Blaszczak, Mike. Professional MFC with Visual C++ 6. 4th ed. Wrox Press, 2000.

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Nishant, Sivakumar, ed. Extending MFC applications with the .NET framework. Addison-Wesley, 2003.

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M, Jones Richard. Introduction to MFC programming with Visual C++. Prentice Hall PTR, 2000.

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Kenn, Scribner, and White K. David, eds. MFC programming with Visual C++ 6 unleashed. SAMS Pub., 1999.

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Book chapters on the topic "MFCC"

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Yan, Qin, Zhengjuan Zhou, and Shan Li. "Chinese Accents Identification with Modified MFCC." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27334-6_77.

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Liu, Jinfeng, Tong Zhu, Xiao He, and John Z. H. Zhang. "MFCC-Based Fragmentation Methods for Biomolecules." In Fragmentation. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch11.

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Gonzalez, Ruben. "Better Than MFCC Audio Classification Features." In The Era of Interactive Media. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3501-3_24.

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Gulhane, Sushen R., D. Shirbahadurkar Suresh, and S. Badhe Sanjay. "Identification of Musical Instruments Using MFCC Features." In New Trends in Computational Vision and Bio-inspired Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41862-5_97.

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Sethi, Nandini, and Dinesh Kumar Prajapati. "Text-Independent Voice Authentication System Using MFCC Features." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5113-0_45.

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Singh, Vrijendra, and Narendra Meena. "Engine Fault Diagnosis using DTW, MFCC and FFT." In Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer India, 2009. http://dx.doi.org/10.1007/978-81-8489-203-1_6.

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Umarani, S. D., R. S. D. Wahidabanu, and P. Raviram. "Isolated Word Recognition Using Enhanced MFCC and IIFs." In Advances in Intelligent Systems and Computing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35314-7_32.

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Jothieswari, J., T. Manicka Sundara Valli, and S. Suguna. "Enhancing Dysarthria Detection: Harnessing Ensemble Models and MFCC." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1329-5_11.

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Li, Fuhai, Jinwen Ma, and Dezhi Huang. "MFCC and SVM Based Recognition of Chinese Vowels." In Computational Intelligence and Security. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_118.

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Ding, Kai, Shoujun Zheng, Xiaogang Qi, Shan Huang, and Haoting Liu. "Acoustic Target Recognition Based on MFCC and SVM." In Man-Machine-Environment System Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4786-5_58.

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Conference papers on the topic "MFCC"

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Jongman, Kabo Benedict, Girum Ayalneh, and Getachew Dagnew. "Clay-Based Microbial Fuel Cell System for Petroleum Contaminated Wastewater Treatment and Green Energy Generation." In Africa International Conference on Clean Energy and Energy Storage. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-8lbnv6.

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The increasing demand for energy and the growing concern for environment pollution have led to the exploration of sustainable and efficient methods for wastewater treatment coupled with energy recovery. This study was focusing on the application of clay based (MFC) microbial fuel cell as a novel approach to treat petroleum wastewater while simultaneously generating electrical energy by using microorganisms extracted from diesel oil-contaminated soil collected from old garage. In this study, microbial fuel cells (MFCs) were constructed using low cost ceramic cylindrical pot (900ml) as an ion ex
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Raviteja, Budidi, Nadikuda Adithi, Patharla Sai Jashwanth, and Lingam Sunitha. "Affective Speech Processing Using MFCC." In 2025 International Conference on New Trends in Computing Sciences (ICTCS). IEEE, 2025. https://doi.org/10.1109/ictcs65341.2025.10989400.

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Bansal, Priyanka, Syed Akhtar Imam, and Roma Bharti. "Expression of Concern for: Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy." In 2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI). IEEE, 2015. http://dx.doi.org/10.1109/icscti35875.2015.10699465.

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Alagundi, Dayanand, Anchal Patil, Varadesh Haridas, Satish Chikkamath, Nirmala S. R, and Suneeta Budihal. "Infant Cry Classification using CNN-MFCC Fusion." In 2024 IEEE International Conference on Contemporary Computing and Communications (InC4). IEEE, 2024. http://dx.doi.org/10.1109/inc460750.2024.10649119.

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Bhargavi, Kilaru Devi, V. Deepa, and I. Harshitha. "Audio Classification through MFCC features using RNN algorithm." In 2024 4th Asian Conference on Innovation in Technology (ASIANCON). IEEE, 2024. https://doi.org/10.1109/asiancon62057.2024.10838024.

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M, Sivaramakrishnan, Aaryan Rajput, and Saravanan M. "Classification of Deep Fake Audio Using MFCC Technique." In 2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS). IEEE, 2024. http://dx.doi.org/10.1109/iciteics61368.2024.10625305.

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Esti Anggraini, Ratih Nur, Farzana Afifah Razak, and Dwi Sunaryono. "Phonics Recognition Using Machine Learning with MFCC Extraction." In 2024 7th International Conference on Information and Communications Technology (ICOIACT). IEEE, 2024. https://doi.org/10.1109/icoiact64819.2024.10913214.

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Bansal, Priyanka, Syed Akhtar Imam, and Roma Bharti. "Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy." In 2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI). IEEE, 2015. http://dx.doi.org/10.1109/icscti.2015.7489535.

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Paseddula, Chandrasekhar, and Suryakanth V. Gangashetty. "DNN based Acoustic Scene Classification using Score Fusion of MFCC and Inverse MFCC." In 2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2018. http://dx.doi.org/10.1109/iciinfs.2018.8721379.

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Nagawade, Monica S., and Varsha R. Ratnaparkhe. "Musical instrument identification using MFCC." In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2017. http://dx.doi.org/10.1109/rteict.2017.8256990.

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Reports on the topic "MFCC"

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Jones, Robert, Molly Creagar, Michael Musty, Randall Reynolds, Scott Slone та Robyn Barbato. A 𝘬-means analysis of the voltage response of a soil-based microbial fuel cell to an injected military-relevant compound (urea). Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45940.

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Biotechnology offers new ways to use biological processes as environmental sensors. For example, in soil microbial fuel cells (MFCs), soil electro-genic microorganisms are recruited to electrodes embedded in soil and produce electricity (measured by voltage) through the breakdown of substrate. Because the voltage produced by the electrogenic microbes is a function of their environment, we hypothesize that the voltage may change in a characteristic manner given environmental disturbances, such as the contamination by exogenous material, in a way that can be modelled and serve as a diagnostic. I
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Rossi, Ruggero, David Jones, Jaewook Myung, et al. Evaluating a multi-panel air cathode through electrochemical and biotic tests. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46320.

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To scale up microbial fuel cells (MFCs), larger cathodes need to be developed that can use air directly, rather than dissolved oxygen, and have good electrochemical performance. A new type of cathode design was examined here that uses a “window-pane” approach with fifteen smaller cathodes welded to a single conductive metal sheet to maintain good electrical conductivity across the cathode with an increase in total area. Abiotic electrochemical tests were conducted to evaluate the impact of the cathode size (exposed areas of 7 cm², 33 cm², and 6200 cm²) on performance for all cathodes having th
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Michael Cannon, Terry Barney, Gary Cook, et al. MFC Communications Infrastructure Study. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1035903.

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Aydogdu, Ali. Design of the glider assimilation experiments. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.2_v2.

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Aydogdu, Ali, Jaime Hernandez-Lasheras, Carolina Amadio, Baptiste Mourre, Gianpiero Cossarini, and Jenny Pistola. Design of the glider assimilation experiments. EuroSea, 2021. http://dx.doi.org/10.3289/eurosea_d4.2.

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Medam, Anudeep, Michael Stadler, Abhishek Banerjee, et al. Summary Report for the Microgrid Fast Charging Station (MFCS) Design Platform Project. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1813548.

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Mickelsen, Zand. Project Closeout Report for the MFC Firewater Replacement Project. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1466677.

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Kerry L. Nisson. Permanent Closure of MFC Biodiesel Underground Storage Tank 99ANL00013. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1060996.

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Guan, Haiying, Andrew Delgado, Yooyoung Lee, et al. User Guide for NIST Media Forensic Challenge (MFC) Datasets. National Institute of Standards and Technology, 2021. http://dx.doi.org/10.6028/nist.ir.8377.

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Steele, William F. Conceptual Design Report for the Materials and Fuels Complex (MFC) Research Collaboration Building (RCB). Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1485427.

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