Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter by Abadjiev, D., Adams, T., Adzic, P., Ahmad, M., Amendola, C., Andrews, M. B., Arcidiacono, R., Argiro, S., Askew, A., Auffray, E., Azzolini, V., Bailleux, D., Band, R., Barney, D., Barria, P., Bartosik, N., Basile, C., Bastos, D., Bell, K. W., Besancon, M., Bianco, R., Biino, C., Blinov, V., Borca, C., Bornheim, A., Brown, R. M., Campana, M., Castells, S., Cavallari, F., Cetorelli, F., Chatterjee, R. M., Chatterjee, S., Chaudhary, G., Chen, J. A., Chernyavskaya, N., Chung, H., Cipriani, M., Cokic, L., Cooke, C., Cossio, F., Couderc, F., Cristoforetti, D., Cucciati, G., Cunqueiro Mendez, L., Da Silva Di Calafiori, D., Dafinei, I., Cockerill, D. J. A., Dejardin, M., Re, D. Del, Ricca, G. Della, Depasse, P., Dervan, J., Marco, E. Di, Diemoz, M., Dimova, T., Dissertori, G., Dittmar, M., Dolgopolov, A., Donegà, M., Dordevic, M., Mamouni, H. El, Errico, F., Espinosa, F., Faure, J. L., Fay, J., Menendez, J. Fernandez, Ferri, F., Finco, L., Fiori, F., Frahm, E., Funk, W., Gadek, T., Gajownik, J., Galli, M., Ganjour, S., Gascon, S., Ghezzi, A., Ghose, P., Gninenko, S., Goadhouse, S., Godinovic, N., Golubev, N., Govoni, P., Gras, P., Hakala, J., de Monchenault, G. Hamel, Harilal, A., Härringer, N., Hashmi, R., Heath, H. F., Hirosky, R., Ho, K. W., Hou, X., Ingram, Q., Jain, Sh., Javaid, T., Jessop, C., Jimènez, R., Joshi, B. M., Jourd‘hui, E., Kaadze, K., Kao, Y.-W., Kardapoltsev, L., Khurana, R., King, J., Kirilovas, A., Konstantinov, D., Kovac, M., Krishna, A., Kuo, C. M., Lambrecht, L., Lavizzari, G., Lecoq, P., Ledovskoy, A., Legger, F., Lelas, D., Li, Y. y., Liang, Z., Lin, W., Longo, E., Loukas, N., Lu, R. -S., Lustermann, W., Lutton, L., Lyon, A. -M., Maeshima, K., Malcles, J., Mandrik, P., Manzoni, R. A., Marchese, L., Marinelli, N., Marini, A. C., Martin, L., Marzocchi, B., Mascellani, A., Massironi, A., Matveev, V., Mazza, G., Meridiani, P., Mijic, M., Mijuskovic, J., Milenovic, P., Milosevic, J., Monteno, M., Monti, F., Moortgat, F., Mousa, J., Mudholkar, T., Nessi-Tedaldi, F., Nicolaou, C., Nigamova, A., Obertino, M. M., Organtini, G., Orimoto, T., Orlandi, F., Ovtin, I., Paganis, E., Papagiannis, D., Pandolfi, F., Paramatti, R., Park, K., Pastrone, N., Paulini, M., Pauss, F., Petkovic, , A., Petraityte, E., Pettinacci, V., Petyt, D., Pigazzini, S., Pinolini, B. S., Prova, P. R., Quaranta, C., Ragazzi, S., Rahatlou, S., Rasteiro Da Silva, J. C., Razis, P. A., Teles, P. Rebello, Reis, T., Riti, F., Rogan, C., Romanteau, T., Rosowsky, A., Rovelli, C., Rovere, M., Rusack, R., Salvi, G., Sancar, O., Sanchez, A., Sandever, C., Santanastasio, F., Saradhy, R., Sarkar, U., Schneider, M., Schroeder, N., Sculac, A., Sculac, T., Shahzad, M. A., Shepherd-Themistocleous, C. H., Simkina, P., Singla, A., Singovsky, A., Skovpen, Y., Smith, V. J., Soffi, L., Stachon, K., Steen, A., Steggemann, J., Succar, M., Tao, J., Tishelman-Charny, A., Tiwari, P. C., Tornago, M., Tramontano, R., Tsai, L. -S., Usai, E., Valsecchi, D., Vagnerini, A., Varela, J., Venditti, R., Verma, P., Vlassov, E., Wachirapusitanand, V., Wamorkar, T., Wang, C., Wang, J., Wadud, M. A., Yu, S. S., Zabi, A., Zghiche, A., Zhang, L., Zhu, R. Y., Zygal, L.

Get full text

ADC architectures for low power analog machine learning by David Bose, Christin

“…First, a 1-bit ADC (current comparator) is designed for application in a novel ELM based conditional branch prediction system designed for pipelined processors. …”
Get full text

EEG based mind controlled car by Li, Yue

“…This project describes the process to design and implementation of real time application for Extreme Learning Machine on Brain-Computer interface area. The ELM was proposed by Dr. Huang GB in NTU, which is Single-hidden layer feed forward network can be applied as a reliable and efficiency classifier in many different area. …”
Get full text

Extreme learning machine based fast object recognition by Xu, Jiantao, Zhou, Hongming, Huang, Guang-Bin

“…Extreme Learning Machine (ELM) as a type of generalized single-hidden layer feed-forward networks (SLFNs) has demonstrated its good generalization performance with extreme fast learning speed in many benchmark and real applications. …”
Get full text
Get full text
Get full text

Emotional states classification from brain signals by Lee, Vinson Bing Jun.

“…Results from the experimental data have indicated that Kernel ELM is the best option as opposed to other SVM variants. …”
Get full text

Inferno XVI: from the circling sodomites to Geryon’s cord by Gilson, S

“…Questa lectura analizza le principali sezioni del canto XVI dell’Inferno con particolare attenzione al dialogo fra Dante personaggio e i tre dannati fiorentini, al trattamento della sodomia nella cultura medievale e ai suoi contesti teologici, e al ruolo della profezia in tale canto. …”

Estimation of diaphragm wall deflections for deep braced excavation in anisotropic clays using ensemble learning by Zhang, Runhong, Wu, Chongzhi, Goh, Anthony Teck Chee, Böhlke, Thomas, Zhang, Wengang

“…Surrogate models were developed via ensemble learning methods (ELMs), including the eXtreme Gradient Boosting (XGBoost), and Random Forest Regression (RFR) to predict the maximum lateral wall deformation (δhmax). …”
Get full text

India's comprehensive economic engagement with east and southeast Asia. by Suvi Dogra.

Get full text

Microfinance and poverty alleviation : experience in Bangladesh and Cambodia by Ek Sopheara

Get full text

Low-power processors for implantable epileptic seizure detection system by Baihaqi, Muhammad Rayhan

“…Extreme Learning Machine (ELM) has gained some attentions recently, due to the fact that learning speed of ELM is really fast compared to the traditional learning algorithm. …”
Get full text

SCHOOL OF THIEVES / by Sabrina Ismail, author 655830, Naadhira Zahari, editor 655828

“…What will happen to Amra’s poor family? And will she ever get her revenge?…”

Structured sparse representations for supervised and unsupervised learning by Zeng, Yijie

“…This thesis also explores the use of unsupervised ELM (US-ELM) on top of the learned graph to learn a flexible and discriminative data embedding that is beneficial for clustering. …”
Get full text

Automatic knee segmentation from multi-contrast MR images by Zhang, Kunlei

“…The choice of the classifier can be some powerful classification models such as SVM and ELM. The advantages of the developed scheme are achieved via effective incorporation of both a useful feature set and the ELM (or SVM) classification with spatial dependencies between neighboring voxels via a DRF framework. …”
Get full text

Electromagnetic (EM) propagation through iron (III) oxide-based building materials embedded with electrically small antennas at microwave frequencies (part 1) by Sheng, Lin

“…Moreover, it was also found that embedding ESA inside concrete will result in the increase of resonant frequency over time as the concrete cures.…”
Get full text

Geometry guided supervised representation learning for classification by Li, Yue

“…Additionally, the extreme learning machine (ELM) was recently extended to representation learning based on the structure of AE. …”
Get full text

A collaborative model in persuasive web design: multiple case study of Lazada and Shopee by Loh, Yin Xia, Choon Sen Seah, Choon Sen Seah, Muhammad Arif, Ezatul Emilia, Jalaludin, Farah Waheeda, Chin, Wai Yin, Abdul Hamid, Nor Aziati

“…This study examined online persuasion through website design by using the Elaboration Likelihood Model (ELM) and Persuasive System Design (PSD). This study investigates the phenomenon of the success of Lazada and Shopee to provide guidelines for website designers and local sellers to enhance the e-commerce website’s persuasiveness. …”
Get full text

Mitigation study and approach for safe drone operations in low-altitude environments by Sidharth, R Sai

“…The average accuracy and macro-averaged F1 scores for the OS-Fuzzy- ELM fault diagnosis model are 80.2% and 78.0%.…”
Get full text

Intraperitoneal administration of mRNA encoding interleukin-12 for immunotherapy in peritoneal carcinomatosis by Arrizabalaga, L, Di Trani, CA, Fernández-Sendin, M, Bella, Á, Russo-Cabrera, JS, Gomar, C, Ardaiz, N, Belsue, V, González-Gomariz, J, Zalba, S, Gil-Korilis, A, Garrido, MJ, Melero, I, Aranda, F, Berraondo, P

Why is income inequality necessary for economic growth? If income equality is achieved, will economic growth stagnate? by Tan, Melisa Mei Jin

Get full text

Investigation of flow over textured surfaces by Koh, Ti Kiat

“…The chemicals used were Hydrochloric Acid (HCL), Sodium Hydroxide (NaOH) and Ethanol with Stearic Acid (ESA). HCL and NaOH were used to alter the surface of AA 6061 while ESA was used to lower the surface energy of the samples. …”
Get full text