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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/when-technostress-drains-and-autonomy-protects-how-organizational-support-sustains-employee-well-being-in-hybrid-work-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/when-technostress-drains-and-autonomy-protects-how-organizational-support-sustains-employee-well-being-in-hybrid-work-2/]]></link>
			<title>When Technostress Drains and Autonomy Protects: How Organizational Support Sustains Employee Well-Being in Hybrid Work</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 20:40:35 +0000]]></pubDate>
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			<title>Packages</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 19:52:53 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/machine-learning-assisted-confinement-loss-prediction-for-a-highly-sensitive-pcf-spr-sensor/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/machine-learning-assisted-confinement-loss-prediction-for-a-highly-sensitive-pcf-spr-sensor/]]></link>
			<title>Machine Learning-Assisted Confinement Loss Prediction for a Highly Sensitive PCF-SPR Sensor</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:54:53 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/beyond-whole-slice-comparing-encoder-families-and-patch-based-pipelines-for-pancreas-segmentation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/beyond-whole-slice-comparing-encoder-families-and-patch-based-pipelines-for-pancreas-segmentation/]]></link>
			<title>Beyond Whole-Slice: Comparing Encoder Families and Patch-Based Pipelines for Pancreas Segmentation</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:49:55 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-domain-invariant-multi-scale-graph-temporal-learning-for-cross-environment-wi-fi-deauthentication-detection-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-domain-invariant-multi-scale-graph-temporal-learning-for-cross-environment-wi-fi-deauthentication-detection-2/]]></link>
			<title>A Domain-Invariant Multi-Scale Graph Temporal Learning for Cross-Environment  Wi-Fi Deauthentication Detection</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 07:41:54 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pathways-to-environmental-sustainability-how-green-ambidexterity-and-green-hrm-flexibility-shape-the-leather-goods-and-footwear-sector-in-bangladesh/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pathways-to-environmental-sustainability-how-green-ambidexterity-and-green-hrm-flexibility-shape-the-leather-goods-and-footwear-sector-in-bangladesh/]]></link>
			<title>Pathways to Environmental Sustainability: How Green Ambidexterity and Green HRM Flexibility Shape the Leather Goods and Footwear Sector in Bangladesh</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:32:50 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/on-device-plant-disease-detection-with-cnn-and-random-forest-ensembles/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/on-device-plant-disease-detection-with-cnn-and-random-forest-ensembles/]]></link>
			<title>On-Device Plant Disease Detection with  CNN and Random Forest Ensembles</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 07:40:26 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-lightweight-hybrid-cnn-transformer-architecture-for-interpretable-evil-twin-attack-detection-in-wi-fi-networks-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-lightweight-hybrid-cnn-transformer-architecture-for-interpretable-evil-twin-attack-detection-in-wi-fi-networks-2/]]></link>
			<title>A Lightweight Hybrid CNN-Transformer Architecture for Interpretable Evil Twin Attack Detection in Wi-Fi Networks</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 07:39:01 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-large-scale-performance-evaluation-of-ml-based-and-deep-neural-models-in-evil-twin-attack-identification-using-a-hybrid-ieee-802-11-dataset/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-large-scale-performance-evaluation-of-ml-based-and-deep-neural-models-in-evil-twin-attack-identification-using-a-hybrid-ieee-802-11-dataset/]]></link>
			<title>A Large-Scale Performance Evaluation of ML-Based and Deep-Neural Models in Evil Twin Attack Identification Using a Hybrid IEEE 802.11 Dataset</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 07:34:08 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sustainable-consumption-and-e-waste-reduction-an-analysis-of-the-jargon-barrier-in-consumer-electronics-readability-for-right-to-repair-practices/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sustainable-consumption-and-e-waste-reduction-an-analysis-of-the-jargon-barrier-in-consumer-electronics-readability-for-right-to-repair-practices/]]></link>
			<title>Sustainable Consumption and E-Waste Reduction: An Analysis of the Jargon Barrier in Consumer Electronics Readability for Right-to-Repair Practices</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 06:34:56 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/environmental-sustainability-and-energy-awareness-among-university-students-in-bangladesh-an-empirical-study/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/environmental-sustainability-and-energy-awareness-among-university-students-in-bangladesh-an-empirical-study/]]></link>
			<title>Environmental Sustainability and Energy Awareness among University Students in Bangladesh: An Empirical Study</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 06:32:15 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/tcnlightgbm-a-hybrid-deep-learning-gradient-boosting-architecture-for-interpretable-short-term-electricity-demand-forecasting-in-bangladesh/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/tcnlightgbm-a-hybrid-deep-learning-gradient-boosting-architecture-for-interpretable-short-term-electricity-demand-forecasting-in-bangladesh/]]></link>
			<title>TCN+LightGBM: A Hybrid Deep Learning–Gradient Boosting Architecture for Interpretable Short-Term Electricity Demand Forecasting in Bangladesh</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 05:22:12 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-lightweight-deep-learning-for-plant-leaf-disease-detection-using-mobilenet-and-grad-cam/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-lightweight-deep-learning-for-plant-leaf-disease-detection-using-mobilenet-and-grad-cam/]]></link>
			<title>Explainable Lightweight Deep Learning for Plant Leaf Disease Detection Using MobileNet and Grad-CAM</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 04:17:04 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/who-did-the-thinking-a-cognitive-control-conceptual-framework-for-student-genai-interaction-in-assessed-ict-tasks/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/who-did-the-thinking-a-cognitive-control-conceptual-framework-for-student-genai-interaction-in-assessed-ict-tasks/]]></link>
			<title>Who did the Thinking? A cognitive-control conceptual framework for student-GenAI interaction in assessed ICT tasks</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:53:15 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-forecast-guided-battery-energy-management-strategy-for-peak-load-shaving-in-renewable-community-microgrids/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-forecast-guided-battery-energy-management-strategy-for-peak-load-shaving-in-renewable-community-microgrids/]]></link>
			<title>A Forecast-Guided Battery Energy Management Strategy for Peak Load Shaving in Renewable Community Microgrids</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 04:02:57 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/novel-attacks-arrive-diffuse-rethinking-few-shot-open-set-enrollment-for-ros-intrusion-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/novel-attacks-arrive-diffuse-rethinking-few-shot-open-set-enrollment-for-ros-intrusion-detection/]]></link>
			<title>Novel Attacks Arrive Diffuse: Rethinking Few-Shot Open-Set Enrollment for ROS Intrusion Detection</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 02:22:51 +0000]]></pubDate>
		</item>
					<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[Wed, 30 Sep 2026 18:11:52 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/adaptive-extended-kalman-filtering-with-lstm-based-signal-quality-assessment-for-gnss-precise-point-positioning-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/adaptive-extended-kalman-filtering-with-lstm-based-signal-quality-assessment-for-gnss-precise-point-positioning-2/]]></link>
			<title>Adaptive Extended Kalman Filtering with LSTM-Based Signal Quality Assessment for GNSS Precise Point Positioning</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:11:44 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-terms-conditions/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-terms-conditions/]]></link>
			<title>NPS Terms Conditions</title>
			<pubDate><![CDATA[Thu, 01 Oct 2026 03:25:46 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-eeg-based-schizophrenia-detection-by-a-feature-extraction-and-machine-learning-algorithm-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-eeg-based-schizophrenia-detection-by-a-feature-extraction-and-machine-learning-algorithm-2/]]></link>
			<title>Automated EEG-Based Schizophrenia Detection by a Feature Extraction and Machine Learning Algorithm</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:11:02 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/road-surface-defects-and-utilities-detection-using-yolo26-with-explainable-ai/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/road-surface-defects-and-utilities-detection-using-yolo26-with-explainable-ai/]]></link>
			<title>Road Surface Defects and Utilities Detection using YOLO26 with Explainable AI</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:10:44 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-simulation-based-machine-learning-framework-for-quantum-noise-channel-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-simulation-based-machine-learning-framework-for-quantum-noise-channel-classification/]]></link>
			<title>A Simulation-Based Machine Learning Framework for Quantum Noise-Channel Classification</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:08:24 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/degradation-aware-v2g-coordination-of-ev-fleets-for-renewable-smart-distribution-networks-a-bangladesh-calibrated-ieee-33-bus-study/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/degradation-aware-v2g-coordination-of-ev-fleets-for-renewable-smart-distribution-networks-a-bangladesh-calibrated-ieee-33-bus-study/]]></link>
			<title>Medprice-XAI-BD: A Kind of Explainable &amp; Uncertainty Mindful Machine Learning Framework, for Medicine Price Prediction in Bangladesh</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:05:05 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/predictive-ceilings-in-generative-ai-learning-analytics-a-six-model-benchmark-of-burnout-risk-grade-change-and-skill-retention-across-50000-student-records/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/predictive-ceilings-in-generative-ai-learning-analytics-a-six-model-benchmark-of-burnout-risk-grade-change-and-skill-retention-across-50000-student-records/]]></link>
			<title>Predictive Ceilings in Generative-AI Learning Analytics: A Six-Model Benchmark of Burnout Risk, Grade Change, and Skill Retention Across 50000 Student Records</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:03:26 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/does-cross-encoder-reranking-close-the-multi-hop-performance-gap-between-knowledge-graph-retrieval-and-vector-rag-in-renewable-energy-domain-qa/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/does-cross-encoder-reranking-close-the-multi-hop-performance-gap-between-knowledge-graph-retrieval-and-vector-rag-in-renewable-energy-domain-qa/]]></link>
			<title>Does Cross-Encoder Reranking Close the Multi-Hop Performance Gap Between Knowledge Graph Retrieval and Vector RAG in Renewable Energy Domain QA?</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:03:11 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/degradation-aware-v2g-coordination-of-ev-fleets-for-renewable-smart-distribution-networks-a-bangladesh-calibrated-ieee-33-bus-study-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/degradation-aware-v2g-coordination-of-ev-fleets-for-renewable-smart-distribution-networks-a-bangladesh-calibrated-ieee-33-bus-study-2/]]></link>
			<title>The &#8220;Aakash Deep&#8221; Hub: A Sustainable and AI- Driven Li-Fi Framework for the Consumer Market in Bangladesh</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 18:03:02 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-difficulty-and-algorithmic-tag-prediction-for-competitive-programming-problems-using-natural-language-processing/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-difficulty-and-algorithmic-tag-prediction-for-competitive-programming-problems-using-natural-language-processing/]]></link>
			<title>Automated Difficulty and Algorithmic Tag Prediction for Competitive Programming Problems Using Natural Language Processing</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:54:34 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/user-interface-evolution-of-youtube-2005-2026-a-longitudinal-analysis-from-hci-perspective/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/user-interface-evolution-of-youtube-2005-2026-a-longitudinal-analysis-from-hci-perspective/]]></link>
			<title>User Interface Evolution of YouTube (2005-2026): A Longitudinal Analysis from HCI Perspective</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:54:33 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multilabel-emotion-recognition-using-a-label-query-dynamic-dependency-network/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multilabel-emotion-recognition-using-a-label-query-dynamic-dependency-network/]]></link>
			<title>Multilabel Emotion Recognition Using a Label-Query Dynamic Dependency Network</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:53:11 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-physics-grounded-explainable-ai-framework-for-false-data-injection-attack-detection-in-smart-grids/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-physics-grounded-explainable-ai-framework-for-false-data-injection-attack-detection-in-smart-grids/]]></link>
			<title>A Physics-Grounded Explainable AI Framework for False Data Injection Attack Detection in Smart Grids</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:46:15 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ensemble-based-detection-of-global-climate-anomalies-using-surface-temperature-and-co₂-emission-indicators-a-majority-voting-unsupervised-framework-with-shap-interpretability/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ensemble-based-detection-of-global-climate-anomalies-using-surface-temperature-and-co₂-emission-indicators-a-majority-voting-unsupervised-framework-with-shap-interpretability/]]></link>
			<title>Ensemble-Based Detection of Global Climate Anomalies Using Surface Temperature and CO₂ Emission Indicators: A Majority-Voting Unsupervised Framework with SHAP Interpretability</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:31:38 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-deep-learning-based-breast-cancer-classification-using-histopathological-images-a-comparative-study-of-cnn-and-vision-transformer-architectures/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-deep-learning-based-breast-cancer-classification-using-histopathological-images-a-comparative-study-of-cnn-and-vision-transformer-architectures/]]></link>
			<title>Explainable Deep Learning-Based Breast Cancer Classification Using Histopathological Images: A Comparative Study of CNN and Vision Transformer Architectures</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:25:13 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/swinmlp-xai-an-explainable-swin-transformer-based-framework-for-automated-detection-of-tuberculosis-in-chest-radiographs/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/swinmlp-xai-an-explainable-swin-transformer-based-framework-for-automated-detection-of-tuberculosis-in-chest-radiographs/]]></link>
			<title>SwinMLP-XAI: An Explainable Swin Transformer-Based Framework for Automated Detection of Tuberculosis in Chest Radiographs</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:24:54 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ompact-multi-scale-attention-cnn-for-brain-mri-tumour-detection-under-a-duplicate-aware-evaluation-protocol/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ompact-multi-scale-attention-cnn-for-brain-mri-tumour-detection-under-a-duplicate-aware-evaluation-protocol/]]></link>
			<title>A Compact Multi Scale Attention CNN for Brain MRI Tumour Detection Under a Duplicate Aware Evaluation Protocol</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:21:38 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/quantifying-social-bias-in-llms-for-bangla-a-likelihood-based-comparative-analysis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/quantifying-social-bias-in-llms-for-bangla-a-likelihood-based-comparative-analysis/]]></link>
			<title>Quantifying Social Bias in LLMs for Bangla: A Likelihood-Based Comparative Analysis</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:19:46 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/brain-tumor-mri-classification-using-hybrid-model/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/brain-tumor-mri-classification-using-hybrid-model/]]></link>
			<title>Brain Tumor MRI Classification Using Hybrid Model</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 17:18:47 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/segswin-net-a-segmentation-guided-vision-transformer-for-improved-leukemia-detection-and-classification/]]></guid>
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			<pubDate><![CDATA[Wed, 30 Sep 2026 17:15:21 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/post-training-int8-quantization-of-mobilenetv3-for-efficient-chest-x-ray-classification-on-edge-devices-2/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/beyond-soh-a-composite-degradation-index-with-uncertainty-aware-soc-estimation-for-ev-batteries/]]></guid>
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			<pubDate><![CDATA[Wed, 30 Sep 2026 17:09:16 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/when-fine-tuning-does-not-help-a-two-stage-efficientnet-b0-evaluation-for-four-class-lung-ct-classification-on-a-small-cohort/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-robust-integrity-verification-and-recovery-framework-for-coarse-to-fine-text-semantic-communication-against-model-tampering-attacks-2/]]></guid>
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		</item>
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