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		<title>NPS Australia Submission System</title>
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		<description><![CDATA[NPS Australia Submission System]]></description>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/segmentation-guided-attention-transfer-learning-for-breast-cancer-classification-in-digital-mammography/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/segmentation-guided-attention-transfer-learning-for-breast-cancer-classification-in-digital-mammography/]]></link>
			<title>Segmentation-Guided Attention Transfer Learning for Breast Cancer Classification in Digital Mammography</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:34:35 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-optimizing-mac-protocol-for-wbans-managing-multi-class-and-multi-load-in-ieee-802-15-6-superframes-using-hysteretic-q-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-optimizing-mac-protocol-for-wbans-managing-multi-class-and-multi-load-in-ieee-802-15-6-superframes-using-hysteretic-q-learning/]]></link>
			<title>An Optimizing MAC Protocol for WBANs Managing Multi-class and Multi-load in IEEE 802.15.6 Superframes Using Hysteretic Q-learning</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:29:13 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-intelligent-railway-level-crossing-system-with-multi-zone-train-monitoring-and-predictive-safety/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-intelligent-railway-level-crossing-system-with-multi-zone-train-monitoring-and-predictive-safety/]]></link>
			<title>An Intelligent Railway Level Crossing System with Multi-Zone Train Monitoring and Predictive Safety</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:18:58 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-deep-learning-approach-for-multi-class-lung-disease-classification-from-chest-x-rays-with-fused-gradcam-localization/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-deep-learning-approach-for-multi-class-lung-disease-classification-from-chest-x-rays-with-fused-gradcam-localization/]]></link>
			<title>A Benchmark of Fake Review Detection Using Machine Learning in E-Commerce</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:14:59 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/machine-learning-for-literacy-rate-prediction-in-bangladesh-leveraging-engineered-socio-economic-features-and-explainable-ai/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/machine-learning-for-literacy-rate-prediction-in-bangladesh-leveraging-engineered-socio-economic-features-and-explainable-ai/]]></link>
			<title>Machine Learning for Literacy Rate Prediction in Bangladesh: Leveraging Engineered Socio-Economic Features and Explainable AI</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:06:11 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/water-quality-and-environment-suitability-feedback-system-for-local-fish-farming-a-fuzzy-logic-based-approach/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/water-quality-and-environment-suitability-feedback-system-for-local-fish-farming-a-fuzzy-logic-based-approach/]]></link>
			<title>Water Quality and Environment Suitability Feedback System for Local Fish Farming: A Fuzzy Logic-Based Approach</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 14:03:00 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/token-smuggling-and-log-injection-in-open-source-ai-coding-assistants-a-case-study/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/token-smuggling-and-log-injection-in-open-source-ai-coding-assistants-a-case-study/]]></link>
			<title>Token Smuggling and Log Injection in Open-Source AI Coding Assistants: A Case Study</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:52:09 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pan-nanofiber-mat-incorporated-with-graphene-oxide-and-cellulose-nanocrystals-for-potential-food-packaging-applications/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pan-nanofiber-mat-incorporated-with-graphene-oxide-and-cellulose-nanocrystals-for-potential-food-packaging-applications/]]></link>
			<title>PAN Nanofiber Mat Incorporated with Graphene Oxide and Cellulose Nanocrystals for Potential Food Packaging Applications</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:50:21 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/domain-aware-hybrid-quantum-learning-via-correlation-guided-circuit-design-for-crime-pattern-analytics/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/domain-aware-hybrid-quantum-learning-via-correlation-guided-circuit-design-for-crime-pattern-analytics/]]></link>
			<title>Domain-Aware Hybrid Quantum Learning via Correlation-Guided Circuit Design for Crime Pattern Analytics</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:32:00 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/latent-space-counterfactual-explanations-for-cervical-cytology-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/latent-space-counterfactual-explanations-for-cervical-cytology-classification/]]></link>
			<title>Latent-Space Counterfactual Explanations for Cervical Cytology Classification</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:24:03 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/tca-net-a-tri-stage-cross-attention-network-with-explainability-consistency-and-boundary-aware-learning-for-generalizable-medical-image-segmentation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/tca-net-a-tri-stage-cross-attention-network-with-explainability-consistency-and-boundary-aware-learning-for-generalizable-medical-image-segmentation/]]></link>
			<title>TCA-Net: A Tri-Stage Cross-Attention Network with Explainability-Consistency and Boundary-Aware Learning for Generalizable Medical Image Segmentation</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:16:23 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fed-oct-iot-cbam-augmented-efficientnet-with-federated-learning-and-explainable-ai-for-retinal-oct-diagnosis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fed-oct-iot-cbam-augmented-efficientnet-with-federated-learning-and-explainable-ai-for-retinal-oct-diagnosis/]]></link>
			<title>Fed-OCT-IoT: CBAM-Augmented EfficientNet with Federated Learning and Explainable AI for Retinal OCT Diagnosis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:05:49 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/the-miou-headline-flatters-ssl-a-label-efficient-head-to-head-of-four-self-supervised-pretraining-families-on-lung-tumor-ct/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/the-miou-headline-flatters-ssl-a-label-efficient-head-to-head-of-four-self-supervised-pretraining-families-on-lung-tumor-ct/]]></link>
			<title>The mIoU Headline Flatters SSL: A Label-Efficient Head-to-Head of Four Self-Supervised\\ Pretraining Families on Lung-Tumor CT</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:03:34 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lexicon-context-divergence-for-reliability-aware-hate-speech-detection-in-low-resource-bangla-memes-a-banglabert-hybrid-with-calibration-and-selective-prediction-analysis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lexicon-context-divergence-for-reliability-aware-hate-speech-detection-in-low-resource-bangla-memes-a-banglabert-hybrid-with-calibration-and-selective-prediction-analysis/]]></link>
			<title>Lexicon–Context Divergence for Reliability-Aware Hate Speech Detection in Low-Resource Bangla Memes: A BanglaBERT Hybrid with Calibration and Selective Prediction Analysis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 13:01:00 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-ensemble-vision-transformer-approach-for-automated-detection-of-hepatocellular-carcinoma/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-ensemble-vision-transformer-approach-for-automated-detection-of-hepatocellular-carcinoma/]]></link>
			<title>An Ensemble Vision Transformer Approach for Automated Detection of Hepatocellular Carcinoma</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 12:49:21 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ai-based-framework-for-cardiovascular-disease-detection-and-risk-prediction-using-machine-learning-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ai-based-framework-for-cardiovascular-disease-detection-and-risk-prediction-using-machine-learning-2/]]></link>
			<title>An Explainable AI-Based Framework for Cardiovascular Disease Detection and Risk Prediction Using Machine Learning</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 12:37:33 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/climate-variability-and-rice-production-extreme-temperature-index-modeling-seasonal-yield-response-assessment/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/climate-variability-and-rice-production-extreme-temperature-index-modeling-seasonal-yield-response-assessment/]]></link>
			<title>Climate Variability and Rice Production: Extreme Temperature Index Modeling: Seasonal Yield Response Assessment</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 12:30:11 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-efficient-protocol-for-private-face-recognition-using-post-quantum-secure-encryption/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-efficient-protocol-for-private-face-recognition-using-post-quantum-secure-encryption/]]></link>
			<title>An Efficient Protocol for Private Face Recognition Using Post-Quantum Secure Encryption</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:53:20 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-low-cost-embedded-data-acquisition-system-for-concrete-rcp-test/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-low-cost-embedded-data-acquisition-system-for-concrete-rcp-test/]]></link>
			<title>A Low-Cost Embedded Data Acquisition System For Concrete RCP Test</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:33:38 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-deep-learning-approach-for-anemia-detection-using-peripheral-blood-smear-images/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-deep-learning-approach-for-anemia-detection-using-peripheral-blood-smear-images/]]></link>
			<title>A Deep learning approach for anemia detection using peripheral blood smear images</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:30:30 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/exploiting-federated-learning-approach-for-efficient-bandwidth-utilization-in-iot-based-surveillance-system/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/exploiting-federated-learning-approach-for-efficient-bandwidth-utilization-in-iot-based-surveillance-system/]]></link>
			<title>Exploiting Federated Learning Approach for Efficient Bandwidth Utilization in IoT-Based Surveillance System</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:16:34 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/dual-flow-knowledge-distillation-with-category-adaptive-inference-for-unsupervised-industrial-anomaly-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/dual-flow-knowledge-distillation-with-category-adaptive-inference-for-unsupervised-industrial-anomaly-detection/]]></link>
			<title>Dual-Flow Knowledge Distillation with Category-Adaptive Inference for Unsupervised Industrial Anomaly Detection</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:08:37 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fine-tuned-efficientnetb0-for-pneumonia-detection-from-chest-x-rays-independent-evaluation-and-grad-cam-based-explainability/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fine-tuned-efficientnetb0-for-pneumonia-detection-from-chest-x-rays-independent-evaluation-and-grad-cam-based-explainability/]]></link>
			<title>Fine-Tuned EfficientNetB0 for Pneumonia Detection from Chest X-Rays: Independent Evaluation and Grad-CAM-Based Explainability</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:07:44 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-comprehensive-study-of-classical-machine-learning-and-deep-learning-in-subject-independent-bci-using-adaptive-snr-weighted-dwt-artifact-elimination/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-comprehensive-study-of-classical-machine-learning-and-deep-learning-in-subject-independent-bci-using-adaptive-snr-weighted-dwt-artifact-elimination/]]></link>
			<title>A Comprehensive Study of Classical Machine Learning and Deep Learning in Subject-Independent BCI Using Adaptive SNR-Weighted DWT Artifact Elimination</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:05:12 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-hybrid-relieff-wrapper-feature-optimization-framework-with-stacking-ensembles-for-explainable-breast-cancer-diagnosis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-hybrid-relieff-wrapper-feature-optimization-framework-with-stacking-ensembles-for-explainable-breast-cancer-diagnosis/]]></link>
			<title>A Hybrid ReliefF-Wrapper Feature Optimization Framework with Stacking Ensembles for Explainable Breast Cancer Diagnosis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 11:02:09 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-vision-transformer-based-culturally-contextualized-bangla-image-captioning-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-vision-transformer-based-culturally-contextualized-bangla-image-captioning-2/]]></link>
			<title>A Vision Transformer-Based Culturally Contextualized Bangla Image Captioning</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 10:58:12 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/esp32-based-smart-fire-and-gas-hazard-detection-with-multi-channel-alert-mechanisms-for-high-risk-urban-buildings/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/esp32-based-smart-fire-and-gas-hazard-detection-with-multi-channel-alert-mechanisms-for-high-risk-urban-buildings/]]></link>
			<title>ESP32-Based Smart Fire and Gas Hazard Detection with Multi-Channel Alert Mechanisms for High-Risk Urban Buildings</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 10:33:24 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/policy-driven-deep-learning-framework-for-facial-age-verification-in-senior-citizen-welfare-programs/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/policy-driven-deep-learning-framework-for-facial-age-verification-in-senior-citizen-welfare-programs/]]></link>
			<title>Policy-Driven Deep Learning Framework for Facial Age Verification in Senior Citizen Welfare Programs</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 10:22:13 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/myth-model-and-reality-nli-framework-for-hallucination-mitigation-in-slm-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/myth-model-and-reality-nli-framework-for-hallucination-mitigation-in-slm-2/]]></link>
			<title>Myth, Model and Reality NLI Framework for Hallucination Mitigation in SLM</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 10:13:14 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/handwritten-prescription-recognition-through-transfer-learning-models-evaluation-under-multiple-dataset-partitions-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/handwritten-prescription-recognition-through-transfer-learning-models-evaluation-under-multiple-dataset-partitions-2/]]></link>
			<title>Handwritten Prescription Recognition Through Transfer Learning Models Evaluation Under Multiple Dataset Partitions</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 09:34:17 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/towards-edge-artificial-intelligence-for-predicting-antimicrobial-resistance-in-mycobacterium-tuberculosis-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/towards-edge-artificial-intelligence-for-predicting-antimicrobial-resistance-in-mycobacterium-tuberculosis-2/]]></link>
			<title>Towards Edge Artificial Intelligence for Predicting Antimicrobial Resistance in Mycobacterium tuberculosis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 09:22:39 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/robust-ransomware-detection-through-cross-family-evaluation-and-behavioral-feature-analysis-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/robust-ransomware-detection-through-cross-family-evaluation-and-behavioral-feature-analysis-2/]]></link>
			<title>Robust Ransomware Detection Through Cross-Family  Evaluation and Behavioral Feature Analysis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 09:07:40 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/deep-sense-deep-learning-for-early-staging-the-onset-of-diabetes-and-optimizing-insulin-dosages-emanating-recognition-of-activity-patterns/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/deep-sense-deep-learning-for-early-staging-the-onset-of-diabetes-and-optimizing-insulin-dosages-emanating-recognition-of-activity-patterns/]]></link>
			<title>Deep Sense: Deep Learning for Early Staging the Onset of Diabetes and Optimizing Insulin Dosages Emanating Recognition of Activity Patterns</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 08:38:33 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/reliability-and-conflict-aware-closed-loop-multimodal-edge-framework-for-landslide-early-warning-a-simulation-based-algorithmic-evaluation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/reliability-and-conflict-aware-closed-loop-multimodal-edge-framework-for-landslide-early-warning-a-simulation-based-algorithmic-evaluation/]]></link>
			<title>Reliability and Conflict-Aware Closed-Loop Multimodal Edge Framework for Landslide Early Warning: A Simulation-Based Algorithmic Evaluation</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:52:28 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/attention-augmented-deep-learning-and-decision-threshold-tuning-for-primary-bone-tumor-classification-in-radiographs/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/attention-augmented-deep-learning-and-decision-threshold-tuning-for-primary-bone-tumor-classification-in-radiographs/]]></link>
			<title>Attention-Augmented Deep Learning and Decision-Threshold Tuning for Primary Bone Tumor Classification in Radiographs</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:51:26 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/hybrid-deep-learning-framework-for-bone-tumor-classification-from-x-ray-images-using-efficientnet-densenet-and-ensemble-voting/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/hybrid-deep-learning-framework-for-bone-tumor-classification-from-x-ray-images-using-efficientnet-densenet-and-ensemble-voting/]]></link>
			<title>Hybrid Deep Learning Framework for Bone Tumor Classification from X-Ray Images Using EfficientNet, DenseNet, and Ensemble Voting</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:49:42 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sustainable-edge-vision-an-energy-efficient-deep-learning-for-crop-disease-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sustainable-edge-vision-an-energy-efficient-deep-learning-for-crop-disease-detection/]]></link>
			<title>Sustainable Edge Vision: An Energy-efficient Deep Learning for Crop Disease Detection</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:28:43 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-machine-learning-framework-for-antibiotic-resistance-prediction-in-e-coli-utis-clinical-insights-for-bangladesh/]]></guid>
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			<title>Explainable Machine Learning framework for Antibiotic Resistance Prediction in E. coli UTIs: Clinical Insights for Bangladesh</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:24:20 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-webcam-based-gaze-aware-human-computer-interaction-framework-for-hands-free-digital-reading-and-context-aware-llm-assisted-text-understanding-3/]]></guid>
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			<title>A Webcam-Based Gaze-Aware Human–Computer Interaction Framework for Hands-Free Digital Reading and Context-Aware LLM-Assisted Text Understanding</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:21:50 +0000]]></pubDate>
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			<title>IoT-Enabled Pneumatic Piston Load-Cell Water-Level Sensing and LoRa Mesh Networking for Automated Alternate Wetting and Drying (AWD) Irrigation Management in Rice Cultivation</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:21:04 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sustainability-in-higher-education-institutions-heis-two-step-assessment-approach-for-least-developed-countries/]]></guid>
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			<title>Sustainability in Higher Education Institutions (HEIs): Two-Step Assessment Approach for Least Developed Countries</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 07:02:16 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/concept-drift-detection-in-streaming-bangla-text-using-an-ensemble-statistical-framework-2/]]></guid>
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			<title>Concept Drift Detection in Streaming Bangla Text Using an Ensemble Statistical Framework</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 06:25:06 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/do-digital-transformations-ensure-sustainable-education-in-the-heis-a-conceptual-framework-based-on-toe-and-rbv/]]></guid>
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			<title>Do Digital Transformations Ensure Sustainable Education in the HEIs? A Conceptual Framework Based on TOE and RBV</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 06:17:45 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/]]></guid>
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			<title>NPS Australia Submission System</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 06:04:52 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/hemastack-harnessing-heterogeneous-stacking-with-neural-meta-learning-and-dual-explainability-for-cost-effective-dengue-diagnosis/]]></guid>
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			<title>HemaStack: Harnessing Heterogeneous Stacking with Neural Meta-Learning and Dual Explainability for Cost-Effective Dengue Diagnosis</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 05:52:35 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/the-impact-of-gpt-and-large-language-models-llms-on-students-academic-performance/]]></guid>
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			<title>The Impact of Generative Pre-trained Transformer and Large Language Models on Students’ Academic Performance</title>
			<pubDate><![CDATA[Sat, 10 Oct 2026 05:24:30 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fairmoe-surv-a-fairness-gated-neuro-symbolic-mixture-of-experts-for-equitable-clinical-risk-prediction-with-cross-cohort-validation/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/triyield-xai-an-explainable-ensemble-model-for-weather-and-geospatial-driven-aman-aus-and-boro-yield-prediction-in-bangladesh/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/device-optimization-and-defect-analysis-of-sr3bicl3-based-perovskite-solar-cells-by-scaps-1d/]]></guid>
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			<title>Device Optimization and Defect Analysis of Sr3BiCl3-Based Perovskite Solar Cells by SCAPS-1D</title>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/cmsa-net-cross-modal-sparse-attention-and-generative-representation-repair-for-multimodal-classification-under-missing-inputs/]]></guid>
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			<pubDate><![CDATA[Sat, 10 Oct 2026 04:10:19 +0000]]></pubDate>
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