LEADER 02189nam 22004693 450 001 9911046658803321 005 20230829185221.0 010 $a9781761062636 010 $a1761062638 035 $a(CKB)4900000000551885 035 $a(MiAaPQ)EBC6704969 035 $a(Au-PeEL)EBL6704969 035 $a(OCoLC)1264472933 035 $a(EXLCZ)994900000000551885 100 $a20230823d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Battle for Shaggy Ridge $eThe Extraordinary Story of the Australian Campaign Against the Japanese in New Guinea's Finisterre Mountains In 1943-44 205 $a1st ed. 210 1$aSydney :$cAllen & Unwin,$d2022. 210 4$dİ2021. 215 $a1 online resource (345 pages) 311 08$a9781760878672 311 08$a1760878677 327 $aCover -- Also by the author -- Title Page -- Copyright -- Dedication -- CONTENTS -- LIST OF MAPS -- Chapter 1: KAIAPIT -- Chapter 2: TO THE END OF THE EARTH -- Chapter 3: 'HOP IN FOR YOUR BLOODY CHOP' -- Chapter 4: 'DO OR DIE' -- Chapter 5: 'WE'D OUTFOUGHT THEM THERE' -- Chapter 6: 'THE BRIG WANTS THAT HILL TONIGHT, MAC' -- Chapter 7: ONTO SHAGGY RIDGE -- Chapter 8: KESAWAI -- Chapter 9: MISSING -- Chapter 10: THE ONE-MAN FRONT -- Chapter 11: THE PIMPLE -- Chapter 12: 18TH BRIGADE -- Chapter 13: PROTHERO -- Chapter 14: LIFE AND DEATH ON SHAGGY RIDGE -- Chapter 15: 'YOU'LL NEVER FORGET SHAGGY RIDGE' -- Chapter 16: TO KANKIRYO -- EPILOGUE -- PICTURE SECTION -- ACKNOWLEDGEMENTS -- NOTES -- BIBLIOGRAPHY -- INDEX. 330 $aAn enlightening re-examination of an important campaign following the experiences of the men from both sides. 606 $aMilitary campaigns 606 $aWorld War, 1939-1945$vPersonal narratives, Australian 615 0$aMilitary campaigns. 615 0$aWorld War, 1939-1945 676 $a940.542653 700 $aBradley$b Phillip$01603668 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911046658803321 996 $aThe Battle for Shaggy Ridge$94468536 997 $aUNINA LEADER 05793nam 22006855 450 001 9911011652903321 005 20250624130250.0 010 $a981-9670-33-0 024 7 $a10.1007/978-981-96-7033-8 035 $a(MiAaPQ)EBC32175414 035 $a(Au-PeEL)EBL32175414 035 $a(CKB)39445505100041 035 $a(OCoLC)1525621614 035 $a(DE-He213)978-981-96-7033-8 035 $a(EXLCZ)9939445505100041 100 $a20250624d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2?6, 2024, Proceedings, Part XV /$fedited by Mufti Mahmud, Maryam Doborjeh, Kevin Wong, Andrew Chi Sing Leung, Zohreh Doborjeh, M. Tanveer 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (639 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v2296 311 08$a981-9670-32-2 327 $aUtilizing Deep Learning to address Temporal and Spatial Dependencies in Weather Forecasting -- Imagined Digits Recognition Based on Masked Electroencephalography Modeling -- THGCN:Temporal Hypergraph Convolutional Network for Subject Independent EEG Emotion Recognition -- ANN-Based Pollution Forecasting Through Short-Term Spatio-Temporal Analysis: A North Island, New Zealand Case Study -- Detection of Animal Movement from Weather Radar using Self-Supervised Learning -- From Concrete to Abstract: A Multimodal Generative Approach to Abstract Concept Learning -- Analysis on Artificial Representations of a Trained AlexNet Model Using the CIFAR-10 Dataset -- Modelling the influence of temperature and rainfall on the spread of African swine fever in Australia -- An EEG-based Spatial-Temporal Hybrid Architecture for Cognitive Load Detection -- Decoding Psychological Stress during Laparoscopic Surgery Training: Insights from EEG -- A Comparison between baseline models and a transformer network for SOC prediction of lithium-ion batteries -- Insights into Long-term Electrical Load Forecasting: Explainable AI approach on Multivariate LSTM -- Artificial Intelligence and Climate Change: A Review of Causes and Opportunities -- Towards a machine learning model to predict cognitive ability using EEG data and virtual spatial navigation task scores in intellectually disabled adults -- HyPeFL: Tackling Data Heterogeneity via Hypernetwork in Personalized Federated Learning -- NeuroGeMS: An open-source GUI software for multimodal modelling in biomedical research and applications -- Multimodal Multiview Graph Convolution Network for the Diagnosis of Alzheimer?s Disease -- DNA-PRIME: Advanced DNA Sequence Compression through Enhanced Feature Fusion and Weight Hashing -- SnE-VNet: A Deep Learning Model with Squeeze and Excitation for Improved 3D Stroke Lesion Segmentation -- Morphology-Guided 3D Skull Gender Identification with Point-BERT -- Cuffless Blood Pressure Measurement From Photoplethysmography through High and low Frequency Information Fusion Attention Mechanism -- Hybrid EEG-fNIRS decoding for fine joint motor imagery of Unilateral Upper Limb with Two-Stage Hybrid Training -- A Neural Network-Augmented Case-Based Reasoning Framework for Weather Risk Modeling using Remote Sensing Data -- Autonomous Design of Floor Plan Based on Architectural Drawings Example without Neighbour Relation -- Using ensemble learning algorithms to integrate multisource remote sensing data for mapping regional forest canopy height -- MTDS: Meta-Path Context Enhanced Drug Combination Synergy Prediction -- A Federated Learning Approach for Genomic Selection in Pigs -- TOP-EEG: a robust software to predict the outcomes of therapies for depression using EEG signals in DGMD domain -- Neural Network as Surrogate Model for Sleep EEG Trajectories and Insomnia Disorder Classification. 330 $aThe sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v2296 606 $aPattern recognition systems 606 $aData mining 606 $aMachine learning 606 $aSocial sciences$xData processing 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aComputer Application in Social and Behavioral Sciences 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aMachine learning. 615 0$aSocial sciences$xData processing. 615 14$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a006.4 700 $aMahmud$b Mufti$01361230 701 $aDoborjeh$b Maryam$01827591 701 $aHuang$b Dejiang$01884775 701 $aLeung$b Andrew Chi Sing$01827593 701 $aDoborjeh$b Zohreh$01827594 701 $aTanveer$b M$01827595 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911011652903321 996 $aNeural Information Processing$94519337 997 $aUNINA