Machine learning and artificial intelligence for energy solutions.

Subject Terms: Artificial intelligence -- Industrial applications., Machine learning -- Industrial applications., Renewable energy sources.

Online Access: https://purl.fdlp.gov/GPO/gpo194657
https://www.nrel.gov/docs/fy20osti/77525.pdf

A comparative study of unsupervised machine learning methods for anomaly detection in flight data : case studies from real-world flight operations

Authors: Jasra, Sameer Kumar, Valentino, Gianluca, Muscat, Alan, Camilleri, Robert

Subject Terms: Flight recorders -- Data processing, Machine learning -- Industrial applications, Anomaly detection (Computer security), Aircraft accidents -- Prevention, Aeronautics -- Safety measures

Relation: https://www.um.edu.mt/library/oar/handle/123456789/137334

Availability: https://www.um.edu.mt/library/oar/handle/123456789/137334
https://doi.org/10.3390/aerospace12020151

R3sNet: optimized residual neural network architecture for the classification of urban solid waste via images

Authors: Castro Bello, Mirna, Romero Juárez, Victor M., Fuentes Pacheco, Jorge, Morales Morales, Cornelio, Marmolejo Vega, Carlos Virgilio, Zagal Barrera, Sergio R., Gutierrez Valencia, Diego Esteban, Marmolejo Duarte, Carlos Ramiro

Contributors: Universitat Politècnica de Catalunya. Departament de Tecnologia de l'Arquitectura, Universitat Politècnica de Catalunya. QURBIS - Quality of Urban Life: Innovation, Sustainability and Social Engagement

Subject Terms: Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Política i gestió ambiental::Gestió de residus, Recycling (Waste, etc.) -- Computer software -- Design and construction, Automatic classification -- Mathematical models -- Industrial applications, Deep learning (Machine learning) -- Industrial applications, Deep learning, Waste classification, Convolution neuronal network, Optimized architecture, Residual networks, Reciclatge (Residus, etc.) -- Programari -- Disseny i construcció, Classificació automàtica -- Models matemàtics -- Aplicacions industrials, Aprenentatge profund -- Aplicacions industrials

File Description: application/pdf

Relation: https://www.mdpi.com/2071-1050/17/8/3502; Castro, M. [et al.]. R3sNet: optimized residual neural network architecture for the classification of urban solid waste via images. "Sustainability (Basel)", 14 Abril 2025, vol. 17, núm. 8, article 3502.; https://hdl.handle.net/2117/429447

Availability: https://hdl.handle.net/2117/429447
https://doi.org/10.3390/su17083502

Convolutional neural network models in municipal solid waste classification: towards sustainable management

Authors: Castro Bello, Mirna, Roman Padilla, Dominic Brian, Morales Morales, Cornelio, Campos Francisco, Wilfrido, Marmolejo Vega, Carlos Virgilio, Marmolejo Duarte, Carlos Ramiro, Evangelista Alcocer, Yanet, Gutierrez Valencia, Diego Esteban

Contributors: Universitat Politècnica de Catalunya. Departament de Tecnologia de l'Arquitectura, Universitat Politècnica de Catalunya. QURBIS - Quality of Urban Life: Innovation, Sustainability and Social Engagement

Subject Terms: Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Política i gestió ambiental::Gestió de residus, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria, Recycling (Waste, etc.) -- Computer software -- Design and construction, Automatic classification -- Mathematical models -- Evaluation, Deep learning (Machine learning) -- Industrial applications, Robot vision -- Mathematical models -- Software, Object detection, Waste, Convolutional neural networks, Raspberry Pi, Embedded system, Sustainable development, Management, Reciclatge (Residus, etc.) -- Programari -- Disseny i construcció, Classificació automàtica -- Models matemàtics -- Avaluació, Aprenentatge profund -- Aplicacions industrials, Visió artificial (Robòtica) -- Models matemàtics -- Programari

File Description: application/pdf

Relation: https://www.mdpi.com/2071-1050/17/8/3523; Castro, M. [et al.]. Convolutional neural network models in municipal solid waste classification: towards sustainable management. "Sustainability (Basel)", 14 Abril 2025, vol. 17, núm. 8, article 3523.; https://hdl.handle.net/2117/429453

Availability: https://hdl.handle.net/2117/429453
https://doi.org/10.3390/su17083523

A novel automated autism spectrum disorder detection system

Authors: Oh, Shu Lih, Jahmunah, V., Arunkumar, N., Abdulhay, Enas W., Gururajan, Raj, Kadri, Nahrizul, Ciaccio, Edward J., Cheong, Kang Hao, Acharya, U. Rajendra

Source: Complex & Intelligent Systems. 7:2399-2413

Subject Terms: Autism--Diagnosis, Support vector machines, Tenfold cross-validation, Autism, Autism diagnosis index, Autism spectrum disorders, 3. Good health, Nonlinear features, 03 medical and health sciences, 0302 clinical medicine, SVM polynomial, Machine learning, Machine learning--Industrial applications, Marginal fsher analysis

Access URL: https://link.springer.com/content/pdf/10.1007/s40747-021-00408-8.pdf

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Authors: Nam, Yoonhee, Koo, Harim, Yang, Yingxi, Shin, Sang, Zhu, Zhihan, Kim, Donggeon, Cho, Hee J., Mu, Quanhua, Choi, Seung W., Sa, Jason K., Seo, Yun J., Kim, Yejin, Lee, Kyoungmin, Oh, Jeong-Woo, Kwon, Yong-Jun, Park, Woong-Yang, Kong, Doo-Sik, Seol, Ho J., Lee, Jung-Il, Park, Chul-Kee, Lee, Hye W., Yoon, Yeup, Wang, Jiguang

Subject Terms: Glioblastoma multiforme, Brain--Cancer--Chemotherapy, Drug resistance in cancer cells, Machine learning--Industrial applications, Cancer--Genetic aspects

Availability: https://doi.org/10.7916/mqt4-pw13

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Authors: Yoonhee Nam, Harim Koo, Yingxi Yang, Sang Shin, Zhihan Zhu, Donggeon Kim, Hee Jin Cho, Quanhua Mu, Seung Won Choi, Jason K. Sa, Yun Jee Seo, Yejin Kim, Kyoungmin Lee, Jeong-Woo Oh, Yong-Jun Kwon, Woong-Yang Park, Doo-Sik Kong, Ho Jun Seol, Jung-Il Lee, Chul-Kee Park, Hye Won Lee, Yeup Yoon, Jiguang Wang

Source: Genome Med
Genome Medicine, Vol 15, Iss 1, Pp 1-15 (2023)

Subject Terms: Brain Neoplasms, Research, Glioma, QH426-470, Glioblastoma multiforme, Brain--Cancer--Chemotherapy, 3. Good health, Cancer--Genetic aspects, Pharmacogenetics, Drug Resistance, Neoplasm, Machine learning--Industrial applications, Machine learning, Early Growth Response Transcription Factors, Cancer genomics, Genetics, Temozolomide, Intra-tumoral heterogeneity, Medicine, Humans, Drug resistance in cancer cells, Pharmacogenomics, Glioblastoma

Access URL: https://pubmed.ncbi.nlm.nih.gov/36915208
https://doaj.org/article/99fc4d15a41f4a889cba3961ed437928

Computer vision in aquaculture : a case study of juvenile fish counting

Authors: Babu, Krishna Moorthy

Source: Journal of the Royal Society of New Zealand, Feb 2023; v.53 n.1:p.52-68

Access URL: http://www.tandfonline.com/doi/pdf/10.1080/03036758.2022.2101484
https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=FL86067279

GA and AI : a new age
Geographic atrophy and artificial intelligence : a new age

Authors: Yap, Aaron, Sheck, Leo

Source: New Zealand optics, Mar 2023; p.14-16

Welcome to the fourth agricultural revolution

Authors: Lee, Anne

Source: New Zealand dairy exporter (1988), Jul/Aug 2023; v.98 n.10:p.57-58
Dairy exporter

Access URL: https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE87889732

New approach to predict growth of forestry tree species

Source: Scion connections, Feb 2023; n.42:p.54-55

Access URL: https://www.scionresearch.com/__data/assets/pdf_file/0003/86961/Scion-Connections-Issue42.pdf
https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE86217399

Learning Mobile Manipulation

Authors: Watkins, David Joseph

Source: CoRR.

Subject Terms: FOS: Computer and information sciences, Computer Science - Robotics, Machine learning--Industrial applications, Robotics, Mobile robots--Design and construction, Computer science, Robotics (cs.RO)

Access URL: http://arxiv.org/abs/2206.03448

Analysis of the impact of machine learning automation on NZ supermarkets

Authors: Batra, Charu, Talukder, Dayal

Source: ICL journal (Auckland, N.Z.), Oct 2022; v.5 n.2:p.29-43

Access URL: https://www.icl.ac.nz/wp-content/uploads/2023/01/ICL-Journal-2022-vol-5-issue-2-1.pdf
https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE85387194

A brand new world : navigating a changing media landscape

Authors: Miller, Ayla

Source: Marketing magazine, Jun/Jul 2022; p.48-52

A novel automated autism spectrum disorder detection system

Authors: Oh, Shu L., Jahmunah, V., Arunkumar, N., Abdulhay, Enas W., Gururajan, Raj, Adib, Nahrizul, Ciaccio, Edward J., Cheong, Kang H., Acharya, U. R.

Subject Terms: Autism spectrum disorders, Machine learning--Industrial applications, Autism--Diagnosis, Support vector machines

Availability: https://doi.org/10.7916/yjw0-fa93

Towards longitudinal mapping of transportation infrastructure with spatio-temporal generative modeling

Authors: Singla, Ayush, Mitchell, John, Ng, Andrew

Subject Terms: Transportation--Planning, Climate change mitigation, Artificial intelligence--Industrial applications, Super-Resolution, Remote-sensing images, 11. Sustainability, Machine learning--Industrial applications, Generative Adversarial Networks (GANs)

Learning Non-Euclidean Representations for Solid Mechanics

Authors: Xiao, Mian

Subject Terms: Civil engineering, Machine learning--Industrial applications, Artificial intelligence--Industrial applications, Anisotropy, Geometry, Non-Euclidean, Strains and stresses--Analysis

Availability: https://doi.org/10.7916/37qe-6t56

Identifying pōhutukawa for myrtle rust response

Source: Scion connections, Mar 2020; n.35:p.4-5

Access URL: https://www.scionresearch.com/__data/assets/pdf_file/0004/68674/Scion-Connections-Issue35.pdf
https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE52809751

Surveying seedlings for precision forestry

Source: Scion connections, Mar 2020; n.35:p.6

Access URL: https://www.scionresearch.com/__data/assets/pdf_file/0004/68674/Scion-Connections-Issue35.pdf
https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE52809751

Machine Learning Applications : From Computer Vision to Robotics

Authors: Indranath Chatterjee, Sheetal Zalte

Resource Type: eBook.

Subjects: Machine learning--Scientific applications, Machine learning--Industrial applications, Deep learning (Machine learning)--Scientific applications, Deep learning (Machine learning)--Industrial applications

Categories: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, TECHNOLOGY & ENGINEERING / Mobile & Wireless Communications