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		<title>NPS Australia Submission System</title>
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			<title>A Machine Learning-Based Framework for Detection and Classification of Spam and Malicious Textual Content on X Using Large-Scale Social Media Data</title>
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			<title>NPS Australia Submission System</title>
			<pubDate><![CDATA[Thu, 27 Aug 2026 11:09:48 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/exploring-possible-adoption-factors-of-mhealth-applications-among-women-in-bangladesh/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/exploring-possible-adoption-factors-of-mhealth-applications-among-women-in-bangladesh/]]></link>
			<title>EXPLORING POSSIBLE ADOPTION FACTORS OF mHealth APPLICATIONS AMONG WOMEN IN BANGLADESH</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 20:36:37 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/evaluating-synthetic-oversampling-strategies-for-imbalanced-thyroid-disease-classification-with-shap-based-explainability-a-comparative-study-using-ensemble-classifiers/]]></guid>
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			<title>Evaluating Synthetic Oversampling Strategies for Imbalanced Thyroid Disease Classification with SHAP-Based Explainability: A Comparative Study Using Ensemble Classifiers.</title>
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			<title>Optimization of operational parameters of incline plate planter via Response surface methodology</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 16:51:29 +0000]]></pubDate>
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			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-empirical-study-on-the-impact-of-authorship-on-the-bug-proneness-of-code-clones/]]></link>
			<title>An Empirical Study on the Impact of Authorship on the Bug-proneness of Code Clones</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 16:03:50 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/comparative-analysis-and-shunt-reactor-mitigation-of-the-ferranti-effect-in-132-kv-overhead-and-underground-transmission-lines-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/comparative-analysis-and-shunt-reactor-mitigation-of-the-ferranti-effect-in-132-kv-overhead-and-underground-transmission-lines-2/]]></link>
			<title>Comparative Analysis and Shunt-Reactor Mitigation of the Ferranti Effect in 132-kV Overhead and Underground Transmission Lines</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 15:52:49 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/omnicortex-a-hybrid-framework-for-explainable-multimodal-brain-tumor-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/omnicortex-a-hybrid-framework-for-explainable-multimodal-brain-tumor-classification/]]></link>
			<title>OmniCortex: A Hybrid Framework for Explainable Multimodal Brain Tumor Classification</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 15:51:05 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-quality-control-in-textiles-a-computer-vision-blended-approach-to-fabric-defect-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-quality-control-in-textiles-a-computer-vision-blended-approach-to-fabric-defect-detection/]]></link>
			<title>Automated Quality Control in Textiles: A Computer Vision Blended Approach to Fabric Defect Detection</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 15:35:44 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multi-class-mri-brain-tumor-classification-using-a-hybrid-efficientnet-attention-architecture/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multi-class-mri-brain-tumor-classification-using-a-hybrid-efficientnet-attention-architecture/]]></link>
			<title>Multi-Class MRI Brain Tumor Classification Using a Hybrid EfficientNet-Attention Architecture</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 15:32:03 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/scopeguard-mitigating-goal-drift-and-confused-deputy-attacks-in-mcp-agent-pipelines/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/scopeguard-mitigating-goal-drift-and-confused-deputy-attacks-in-mcp-agent-pipelines/]]></link>
			<title>ScopeGuard: Mitigating Goal Drift and Confused Deputy Attacks in MCP Agent Pipelines</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 14:56:22 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/traffic-demand-regulation-by-an-intelligent-management-system-in-dhaka-city/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/traffic-demand-regulation-by-an-intelligent-management-system-in-dhaka-city/]]></link>
			<title>Traffic Demand Regulation by an Intelligent Management System in Dhaka City</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 14:02:04 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/benchmarking-deep-learning-models-for-iomt-intrusion-detection-with-mcnemar-testing-and-explainable-artificial-intelligence/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/benchmarking-deep-learning-models-for-iomt-intrusion-detection-with-mcnemar-testing-and-explainable-artificial-intelligence/]]></link>
			<title>Benchmarking Deep Learning Models for IoMT Intrusion Detection with McNemar Testing and  Explainable Artificial Intelligence</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 13:34:13 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/assessment-of-near-field-and-far-field-electromagnetic-exposure-in-daily-use-wireless-devices/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/assessment-of-near-field-and-far-field-electromagnetic-exposure-in-daily-use-wireless-devices/]]></link>
			<title>Assessment of Near-Field and Far-Field Electromagnetic Exposure in Daily-Use Wireless Devices</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 13:30:33 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-iot-enabled-smart-cold-storage-system-for-real-time-environmental-monitoring-and-automated-control-of-perishable-commodities/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-iot-enabled-smart-cold-storage-system-for-real-time-environmental-monitoring-and-automated-control-of-perishable-commodities/]]></link>
			<title>An IoT-Enabled Smart Cold Storage System for Real-Time Environmental Monitoring and Automated Control of Perishable Commodities</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 13:29:27 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/leukemiacellnet-a-patient-aware-multi-scale-cnn-transformer-framework-with-attention-based-aggregation-for-leakage-free-aml-cytomorphology-classification-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/leukemiacellnet-a-patient-aware-multi-scale-cnn-transformer-framework-with-attention-based-aggregation-for-leakage-free-aml-cytomorphology-classification-2/]]></link>
			<title>LeukemiaCellNet: A Patient-Aware Multi-Scale CNN–Transformer Framework with Attention-Based Aggregation for Leakage-Free AML Cytomorphology Classification</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 13:27:29 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-dual-band-rectenna-with-high-rf-to-dc-conversion-efficiency-for-ambient-wireless-power-harvesting/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-dual-band-rectenna-with-high-rf-to-dc-conversion-efficiency-for-ambient-wireless-power-harvesting/]]></link>
			<title>A Dual-Band Rectenna with High RF-to-DC Conversion Efficiency for Ambient Wireless Power Harvesting</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 07:07:07 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/impedance-based-stability-boundary-for-two-stage-solid-state-transformer-ev-fast-chargers/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/impedance-based-stability-boundary-for-two-stage-solid-state-transformer-ev-fast-chargers/]]></link>
			<title>Impedance-Based Stability Boundary for Two-Stage Solid-State-Transformer EV Fast Chargers</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 06:42:04 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-hybrid-statistical-and-machine-learning-approach-for-optimizing-critical-quality-a-hybrid-statistical-and-machine-learning-approach-for-optimizing-critical-quality/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-hybrid-statistical-and-machine-learning-approach-for-optimizing-critical-quality-a-hybrid-statistical-and-machine-learning-approach-for-optimizing-critical-quality/]]></link>
			<title>A Hybrid Statistical and Machine Learning Approach for Optimizing Critical Quality A Hybrid Statistical and Machine Learning Approach for Optimizing Critical Quality</title>
			<pubDate><![CDATA[Sat, 29 Aug 2026 02:37:10 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-code-smell-detection-for-software-quality-assurance-using-a-web-based-machine-learning-framework/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-code-smell-detection-for-software-quality-assurance-using-a-web-based-machine-learning-framework/]]></link>
			<title>Automated Code Smell Detection for Software Quality Assurance Using a Web-Based Machine Learning Framework</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 21:53:35 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/scenario-based-synthetic-road-accident-risk-prediction-using-explainable-ensemble-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/scenario-based-synthetic-road-accident-risk-prediction-using-explainable-ensemble-learning/]]></link>
			<title>Scenario Based Synthetic Road Accident Risk Prediction using Explainable Ensemble Learning</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 21:52:20 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sga-wqi-shap-guided-adaptive-water-quality-index-for-deep-learning-based-water-quality-prediction-using-tabnet-and-transformer-models/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sga-wqi-shap-guided-adaptive-water-quality-index-for-deep-learning-based-water-quality-prediction-using-tabnet-and-transformer-models/]]></link>
			<title>SGA-WQI: SHAP-Guided Adaptive Water Quality Index for Deep Learning-Based Water Quality Prediction Using TabNet and Transformer Models</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 21:47:45 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/soft-voting-ensemble-with-explainable-ai-for-sustainable-crop-recommendation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/soft-voting-ensemble-with-explainable-ai-for-sustainable-crop-recommendation/]]></link>
			<title>Soft Voting Ensemble with Explainable AI for Sustainable Crop Recommendation</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 21:46:50 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-comparative-analysis-of-machine-learning-models-for-crop-recommendation-using-explainable-ai/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-comparative-analysis-of-machine-learning-models-for-crop-recommendation-using-explainable-ai/]]></link>
			<title>A Comparative Analysis of Machine Learning Models for Crop Recommendation using Explainable AI</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 21:45:41 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/x-stream-ids-an-explainable-streaming-aware-deep-learning-based-intrusion-detection-system-for-iot/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/x-stream-ids-an-explainable-streaming-aware-deep-learning-based-intrusion-detection-system-for-iot/]]></link>
			<title>X-STREAM-IDS: An Explainable Streaming-Aware Deep Learning based Intrusion Detection System for IoT</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 19:38:49 +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[Fri, 28 Aug 2026 16:27:39 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multi-granularity-self-consistency-entropy-for-large-language-model-hallucination-detection-informative-insights-across-fabrication-prone-and-refusal-prone-model-regimes/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multi-granularity-self-consistency-entropy-for-large-language-model-hallucination-detection-informative-insights-across-fabrication-prone-and-refusal-prone-model-regimes/]]></link>
			<title>Multi-Granularity Self-Consistency Entropy for Large Language Model Hallucination Detection: Informative Insights Across Fabrication-Prone and Refusal-Prone Model Regimes</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 15:03:46 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-dual-branch-framework-for-livestock-disease-screening-using-multi-repository-visual-datasets-and-symptom-based-intelligence/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-dual-branch-framework-for-livestock-disease-screening-using-multi-repository-visual-datasets-and-symptom-based-intelligence/]]></link>
			<title>A Dual-Branch Framework for Livestock Disease Screening Using Multi-Repository Visual Datasets and Symptom-Based Intelligence</title>
			<pubDate><![CDATA[Thu, 27 Aug 2026 15:16:40 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ml-framework-for-five-customs-fraud-type-predictions-using-xgboost-and-smote-based-class-balancing/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ml-framework-for-five-customs-fraud-type-predictions-using-xgboost-and-smote-based-class-balancing/]]></link>
			<title>An Explainable ML Framework for Five Customs Fraud Type Predictions Using XGBoost and SMOTE-Based Class Balancing</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 12:14:48 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-feature-integrated-machine-learning-framework-for-lysine-ptm-site-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-feature-integrated-machine-learning-framework-for-lysine-ptm-site-classification/]]></link>
			<title>A FEATURE-INTEGRATED MACHINE LEARNING FRAMEWORK FOR LYSINE PTM SITE CLASSIFICATION</title>
			<pubDate><![CDATA[Thu, 27 Aug 2026 14:20:16 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote-3/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote-3/]]></link>
			<title>ASD-Predict: A Multi-class Explainable Autism Disorder Severity Prediction Using LightGBM and SMOTE</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 12:06:28 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote-2/]]></link>
			<title>A new era begins</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 12:04:56 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/predicting-solar-pv-power-under-real-world-conditions-a-comparative-evaluation-of-interpretable-machine-learning-models/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/predicting-solar-pv-power-under-real-world-conditions-a-comparative-evaluation-of-interpretable-machine-learning-models/]]></link>
			<title>Predicting Solar PV Power Under Real-World Conditions: A Comparative Evaluation of Interpretable Machine Learning Models</title>
			<pubDate><![CDATA[Thu, 27 Aug 2026 14:14:48 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/asd-predict-a-multi-class-explainable-autism-disorder-severity-prediction-using-lightgbm-and-smote/]]></link>
			<title>ASD a new era begins</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 11:25:19 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-ai-enhanced-four-class-stacking-ensemble-framework-for-explainable-income-tax-fraud-detection-using-calibrated-nbr-it-10b-structure/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-ai-enhanced-four-class-stacking-ensemble-framework-for-explainable-income-tax-fraud-detection-using-calibrated-nbr-it-10b-structure/]]></link>
			<title>An AI-Enhanced Four-Class Stacking Ensemble Framework for Explainable Income Tax Fraud Detection Using Calibrated NBR IT-10B Structure</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 10:33:27 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/water-pixel-dilution-bias-a-systematic-measurement-error-in-riverine-spatial-feature-engineering/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/water-pixel-dilution-bias-a-systematic-measurement-error-in-riverine-spatial-feature-engineering/]]></link>
			<title>Water Pixel Dilution Bias: A Systematic Measurement Error in Riverine Spatial Feature Engineering</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 10:25:24 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/url-only-phishing-detection-based-on-structural-and-character-level-lexical-fusion-using-tf-idf-and-lightgbm/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/url-only-phishing-detection-based-on-structural-and-character-level-lexical-fusion-using-tf-idf-and-lightgbm/]]></link>
			<title>URL-Only Phishing Detection Based on Structural and Character-Level Lexical Fusion Using TF-IDF and LightGBM</title>
			<pubDate><![CDATA[Fri, 28 Aug 2026 09:50:46 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/complexity-aware-explainable-deep-learning-for-skin-cancer-classification-a-dynamic-explanation-selector-for-adaptive-xai-on-dermoscopic-images/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/complexity-aware-explainable-deep-learning-for-skin-cancer-classification-a-dynamic-explanation-selector-for-adaptive-xai-on-dermoscopic-images/]]></link>
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			<pubDate><![CDATA[Fri, 28 Aug 2026 04:57:56 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-lightweight-knowledge-distilled-cnn-for-real-time-waste-classification-on-edge-devices/]]></guid>
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			<pubDate><![CDATA[Thu, 27 Aug 2026 19:32:28 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/real-time-bangladeshi-vehicle-type-recognition-using-yolov9-variants/]]></guid>
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			<pubDate><![CDATA[Thu, 27 Aug 2026 17:47:18 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-district-level-regional-planning-framework-for-ccus-deployment-in-bangladesh-spatial-decision-support-approach/]]></guid>
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			<pubDate><![CDATA[Thu, 27 Aug 2026 17:21:12 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/fedpdm-privacy-preserving-federated-learning-for-remaining-useful-life-prediction-across-heterogeneous-industrial-systems/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/web-based-explainable-deep-learning-framework-for-skin-disease-detection/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/iot-driven-refreshable-braille-architecture-utilizing-vision-based-ocr-and-cloud-storage/]]></guid>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/global-ai-governance-without-the-giants-market-access-as-middle-power-leverage/]]></guid>
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