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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/an-educational-rtl-to-gdsii-flow-for-a-non-pipelined-8-bit-accumulator-based-cpu-using-open-source-tools/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-educational-rtl-to-gdsii-flow-for-a-non-pipelined-8-bit-accumulator-based-cpu-using-open-source-tools/]]></link>
			<title>An Educational RTL-to-GDSII Flow for a Non-Pipelined 8-bit Accumulator-Based CPU Using Open-Source Tools</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:52:34 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/bulaq-an-intelligent-mobile-queue-framework-with-dynamic-service-allocation-and-ml-driven-wait-time-prediction/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/bulaq-an-intelligent-mobile-queue-framework-with-dynamic-service-allocation-and-ml-driven-wait-time-prediction/]]></link>
			<title>BulaQ: An intelligent mobile Queue Framework with dynamic service allocation and ML-driven wait time prediction</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:44:02 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/valelink-design-development-and-evaluation-of-a-digital-property-management-platform-for-fijis-residential-rental-sector/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/valelink-design-development-and-evaluation-of-a-digital-property-management-platform-for-fijis-residential-rental-sector/]]></link>
			<title>ValeLink: Design, Development, and Evaluation of a Digital Property Management Platform for Fiji’s Residential Rental Sector</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:42:32 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/graph-based-clustering-and-explainable-graph-neural-networks-for-crime-hotspot-prediction-in-bangladesh-2020-2025/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/graph-based-clustering-and-explainable-graph-neural-networks-for-crime-hotspot-prediction-in-bangladesh-2020-2025/]]></link>
			<title>Graph-Based Clustering and Explainable Graph Neural Networks for Crime Hotspot Prediction in Bangladesh (2020–2025)</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:37:59 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/q-learning-based-degradation-aware-bess-management-for-agricultural-microgrids/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/q-learning-based-degradation-aware-bess-management-for-agricultural-microgrids/]]></link>
			<title>Q-Learning-Based Degradation-Aware BESS Management for Agricultural Microgrids</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:22:23 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/endostack-xai-a-hybrid-and-explainable-machine-learning-framework-for-endometriosis-prediction/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/endostack-xai-a-hybrid-and-explainable-machine-learning-framework-for-endometriosis-prediction/]]></link>
			<title>EndoStack-XAI: A Hybrid and Explainable Machine Learning Framework for Endometriosis Prediction</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 06:21:20 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sector-level-emission-intensity-profiling-of-supply-chains-a-leakage-free-machine-learning-approach-using-structurally-independent-predictors-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/sector-level-emission-intensity-profiling-of-supply-chains-a-leakage-free-machine-learning-approach-using-structurally-independent-predictors-2/]]></link>
			<title>Sector-Level Emission Intensity Profiling of Supply Chains: A Leakage-Free Machine Learning Approach Using Structurally Independent Predictors</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:51:53 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/from-first-come-first-served-to-eevdf-an-empirical-survey-of-cpu-scheduling-using-google-borg-cluster-traces/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/from-first-come-first-served-to-eevdf-an-empirical-survey-of-cpu-scheduling-using-google-borg-cluster-traces/]]></link>
			<title>From First-Come-First-Served to EEVDF: An Empirical Survey of CPU Scheduling Using Google Borg Cluster Traces</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:50:34 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lauc-risknet-leakage-aware-and-interpretable-learning-for-rule-driven-mental-health-labels/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lauc-risknet-leakage-aware-and-interpretable-learning-for-rule-driven-mental-health-labels/]]></link>
			<title>LAUC-RiskNet: Leakage-Aware and Interpretable Learning for Rule-Driven Mental-Health Labels</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:49:07 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/wind-turbine-blade-structural-health-monitoring-using-piezoelectric-sensors-and-machine-learning-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/wind-turbine-blade-structural-health-monitoring-using-piezoelectric-sensors-and-machine-learning-2/]]></link>
			<title>Wind Turbine Blade Structural Health Monitoring Using Piezoelectric Sensors and Machine Learning</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:42:28 +0000]]></pubDate>
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			<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[Wed, 30 Sep 2026 05:34:04 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/regime-aware-temporal-convolutional-gated-recurrent-forecasting-of-hydrogen-production-in-wave-driven-pem-electrolysis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/regime-aware-temporal-convolutional-gated-recurrent-forecasting-of-hydrogen-production-in-wave-driven-pem-electrolysis/]]></link>
			<title>Regime-Aware Temporal Convolutional–Gated Recurrent Forecasting of Hydrogen Production in Wave-Driven PEM Electrolysis</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:33:30 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/drifterase-har-ledger-anchored-federated-unlearning-for-multimodal-human-activity-recognition-under-asynchronous-sensor-drift/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/drifterase-har-ledger-anchored-federated-unlearning-for-multimodal-human-activity-recognition-under-asynchronous-sensor-drift/]]></link>
			<title>DriftErase-HAR: Ledger-Anchored Federated Unlearning for Multimodal Human Activity Recognition under Asynchronous Sensor Drift</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:29:00 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/provable-moving-target-defense-for-cyber-physical-networks-from-the-security-performance-frontier-to-no-regret-defense/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/provable-moving-target-defense-for-cyber-physical-networks-from-the-security-performance-frontier-to-no-regret-defense/]]></link>
			<title>Provable Moving-Target Defense for Cyber-Physical Networks: From the Security–Performance Frontier to No-Regret Defense</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:21:35 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/revisiting-behavioral-android-malware-classification-a-leakage-controlled-benchmark-of-tree-ensemble-methods-and-hybrid-attention-networks/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/revisiting-behavioral-android-malware-classification-a-leakage-controlled-benchmark-of-tree-ensemble-methods-and-hybrid-attention-networks/]]></link>
			<title>Revisiting Behavioral Android Malware Classification: A Leakage-Controlled Benchmark of Tree Ensemble Methods and Hybrid Attention Networks</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:20:34 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-bangla-speech-dataset-for-sentence-type-and-emotion-classification-using-traditional-machine-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-bangla-speech-dataset-for-sentence-type-and-emotion-classification-using-traditional-machine-learning/]]></link>
			<title>A Bangla Speech Dataset for Sentence Type and Emotion Classification Using Traditional Machine Learning</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 05:16:05 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/embedded-fail-safe-and-real-time-communication-framework-for-http-based-wireless-mobile-robot-teleoperation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/embedded-fail-safe-and-real-time-communication-framework-for-http-based-wireless-mobile-robot-teleoperation/]]></link>
			<title>Embedded Fail-Safe and Real-Time Communication Framework for HTTP-Based Wireless Mobile Robot Teleoperation</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 04:56:58 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/curvature-regularized-graph-tractography-for-reproducible-multi-site-diffusion-mri-connectomes/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/curvature-regularized-graph-tractography-for-reproducible-multi-site-diffusion-mri-connectomes/]]></link>
			<title>Curvature-Regularized Graph Tractography for Reproducible Multi-Site Diffusion MRI Connectomes</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 04:42:08 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ensemble-machine-learning-framework-for-predicting-icu-mortality-in-critically-ill-patients/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-ensemble-machine-learning-framework-for-predicting-icu-mortality-in-critically-ill-patients/]]></link>
			<title>An Explainable Ensemble Machine-Learning Framework for Predicting ICU Mortality in Critically Ill Patients</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 04:31:20 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/evaluation-of-avr-performance-using-pid-anfis-and-ann-based-controllers-under-time-domain-analysis/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/evaluation-of-avr-performance-using-pid-anfis-and-ann-based-controllers-under-time-domain-analysis/]]></link>
			<title>Evaluation of AVR Performance Using PID, ANFIS, and ANN-Based Controllers Under Time-Domain Analysis</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 04:16:13 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-intelligent-wearable-framework-for-real-time-harassment-detection-using-machine-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-intelligent-wearable-framework-for-real-time-harassment-detection-using-machine-learning/]]></link>
			<title>An Intelligent Wearable Framework for Real-Time Harassment Detection Using Machine Learning</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 04:07:44 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-rice-leaf-disease-detection-using-deep-feature-extraction-and-machine-learning-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/automated-rice-leaf-disease-detection-using-deep-feature-extraction-and-machine-learning-classification/]]></link>
			<title>Automated Rice Leaf Disease Detection Using  Deep Feature Extraction and Machine Learning  Classification</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 03:54:51 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/real-time-object-classification-in-autonomous-driving-a-lightweight-residual-cnn-approach-on-unified-bdd100k-coco-data/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/real-time-object-classification-in-autonomous-driving-a-lightweight-residual-cnn-approach-on-unified-bdd100k-coco-data/]]></link>
			<title>Real-Time Object Classification in Autonomous Driving: A Lightweight Residual CNN Approach on Unified BDD100K–COCO Data</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 03:09:41 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-adaptive-fusion-based-ensemble-deep-learning-framework-for-cross-subject-eeg-emotion-recognition-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-adaptive-fusion-based-ensemble-deep-learning-framework-for-cross-subject-eeg-emotion-recognition-2/]]></link>
			<title>An Adaptive Fusion-Based Ensemble Deep Learning Framework for Cross-Subject EEG Emotion Recognition</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 02:46:19 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-and-generalizable-deepfake-detection-for-vishing-attack-recognition/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-and-generalizable-deepfake-detection-for-vishing-attack-recognition/]]></link>
			<title>Explainable and Generalizable Deepfake Detection for Vishing Attack Recognition</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 02:11:40 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/design-simulation-and-sizing-assessment-of-an-off-grid-solar-pv-pem-green-hydrogen-generation-and-compressed-storage-system-for-bangladesh-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/design-simulation-and-sizing-assessment-of-an-off-grid-solar-pv-pem-green-hydrogen-generation-and-compressed-storage-system-for-bangladesh-2/]]></link>
			<title>Design, Simulation, and Sizing Assessment of an Off-Grid Solar PV–PEM Green Hydrogen Generation and Compressed Storage System for Bangladesh</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 02:01:05 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/]]></link>
			<title>NPS Australia Submission System</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 02:00:04 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/serial-rag-engine-for-memory-efficient-offline-math-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/serial-rag-engine-for-memory-efficient-offline-math-learning/]]></link>
			<title>Serial RAG Engine for Memory-Efficient Offline Math Learning</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 00:28:09 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/30-day-ahead-load-forecasting-for-the-rajshahi-zone-of-the-bangladesh-power-system-a-linear-base-boosted-bilstm-approach/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/30-day-ahead-load-forecasting-for-the-rajshahi-zone-of-the-bangladesh-power-system-a-linear-base-boosted-bilstm-approach/]]></link>
			<title>30-Day-Ahead Load Forecasting for the Rajshahi Zone of the Bangladesh Power System: A Linear-Base Boosted BiLSTM Approach</title>
			<pubDate><![CDATA[Wed, 30 Sep 2026 00:18:52 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/cross-lingual-and-cross-domain-transfer-learning-for-digital-arrest-scam-detection-via-transformer-warm-starting-with-coercion-stage-explainability/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/cross-lingual-and-cross-domain-transfer-learning-for-digital-arrest-scam-detection-via-transformer-warm-starting-with-coercion-stage-explainability/]]></link>
			<title>Cross-Lingual and Cross-Domain Transfer Learning for Digital-Arrest Scam Detection via Transformer Warm-Starting with Coercion-Stage Explainability</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 23:47:38 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/above-chance-below-the-baseline-a-majority-anchored-case-grouped-ablation-for-thyroid-ultrasound-segmentation-and-report-derived-suspicion-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/above-chance-below-the-baseline-a-majority-anchored-case-grouped-ablation-for-thyroid-ultrasound-segmentation-and-report-derived-suspicion-classification/]]></link>
			<title>Above Chance, Below the Baseline: A Majority-Anchored, Case-Grouped Ablation for Thyroid Ultrasound Segmentation and Report-Derived Suspicion Classification</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 23:46:47 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/aqua-monitor-a-decoupled-lora-to-cloud-iot-architecture-for-low-cost-multi-pond-water-quality-monitoring-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/aqua-monitor-a-decoupled-lora-to-cloud-iot-architecture-for-low-cost-multi-pond-water-quality-monitoring-2/]]></link>
			<title>Aqua Monitor: A Decoupled LoRa-to-Cloud IoT Architecture for Low-Cost Multi-Pond Water Quality Monitoring</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 23:37:08 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/conservation-residual-augmented-learning-for-telemetry-integrity-monitoring-of-rooftop-solar-storage-systems/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/conservation-residual-augmented-learning-for-telemetry-integrity-monitoring-of-rooftop-solar-storage-systems/]]></link>
			<title>Conservation-Residual Augmented Learning for Telemetry Integrity Monitoring of Rooftop Solar-Storage Systems</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 23:33:07 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-calibrated-hierarchical-xlm-r-for-bilingual-phq-9-depression-severity-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-calibrated-hierarchical-xlm-r-for-bilingual-phq-9-depression-severity-classification/]]></link>
			<title>Explainable Calibrated Hierarchical XLM-R for Bilingual PHQ-9 Depression Severity Classification</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 21:28:37 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/physics-and-communication-aware-remote-terminal-unit-cyberattacks-detection-and-classification-for-smart-energy-grids/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/physics-and-communication-aware-remote-terminal-unit-cyberattacks-detection-and-classification-for-smart-energy-grids/]]></link>
			<title>Physics and Communication-Aware Remote Terminal Unit Cyberattacks Detection and Classification for Smart Energy Grids</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 21:25:43 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/rice-leaf-disease-classification-using-fine-tuned-resnet152v2-benchmarking-cnn-models/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/rice-leaf-disease-classification-using-fine-tuned-resnet152v2-benchmarking-cnn-models/]]></link>
			<title>Rice Leaf Disease Classification Using Fine-Tuned ResNet152V2: Benchmarking CNN Models</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 21:19:59 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-machine-learning-for-regional-load-shedding-severity-classification-using-supply-side-constraints-in-bangladesh/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/explainable-machine-learning-for-regional-load-shedding-severity-classification-using-supply-side-constraints-in-bangladesh/]]></link>
			<title>Explainable Machine Learning for Regional Load-Shedding Severity Classification Using Supply-Side Constraints in Bangladesh</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:58:22 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multimodal-autonomous-drone-surveillance-for-campus-security-yolo11-based-person-and-id-card-detection-with-acoustic-threat-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/multimodal-autonomous-drone-surveillance-for-campus-security-yolo11-based-person-and-id-card-detection-with-acoustic-threat-classification/]]></link>
			<title>Multimodal Autonomous Drone Surveillance for Campus Security: YOLO11-Based Person and ID-Card Detection with Acoustic Threat Classification</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:48:23 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-multi-factor-smart-motorcycle-ignition-interlock-with-face-recognition-helmet-verification-and-alcohol-screening/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-multi-factor-smart-motorcycle-ignition-interlock-with-face-recognition-helmet-verification-and-alcohol-screening/]]></link>
			<title>A Multi-Factor Smart Motorcycle Ignition Interlock with Face Recognition, Helmet Verification, and Alcohol Screening</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:32:19 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pp-gbd-privacy-preserving-graph-neural-botnet-detection-in-encrypted-traffic/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/pp-gbd-privacy-preserving-graph-neural-botnet-detection-in-encrypted-traffic/]]></link>
			<title>PP-GBD: Privacy-Preserving Graph Neural Botnet Detection in Encrypted Traffic</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:29:54 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/spearxai-org-target-context-aware-benchmark-and-explainable-hybrid-reference-framework-for-llm-assisted-spear-phishing-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/spearxai-org-target-context-aware-benchmark-and-explainable-hybrid-reference-framework-for-llm-assisted-spear-phishing-detection/]]></link>
			<title>SpearXAI-Org: Target-Context-Aware Benchmark and Explainable Hybrid Reference Framework for LLM-Assisted Spear-Phishing Detection</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:27:30 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/medinetlite-a-resource-efficient-ultra-lightweight-cnn-for-medicinal-leaf-recognition-in-bangladeshi-weed-infested-area/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/medinetlite-a-resource-efficient-ultra-lightweight-cnn-for-medicinal-leaf-recognition-in-bangladeshi-weed-infested-area/]]></link>
			<title>MediNetLite: A Resource Efficient Ultra Lightweight CNN for Medicinal Leaf Recognition in Bangladeshi Weed-Infested Area</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:21:17 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/conflict-aware-trust-based-aggregation-for-poisoning-resistant-federated-medical-image-classification/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/conflict-aware-trust-based-aggregation-for-poisoning-resistant-federated-medical-image-classification/]]></link>
			<title>Conflict Aware Trust-Based Aggregation for Poisoning Resistant Federated Medical Image Classification</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 20:04:27 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/unipedformer-a-unified-single-stage-vision-transformer-for-joint-pedestrian-detection-and-trajectory-prediction/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/unipedformer-a-unified-single-stage-vision-transformer-for-joint-pedestrian-detection-and-trajectory-prediction/]]></link>
			<title>UniPedFormer: A Unified Single-Stage Vision Transformer for Joint Pedestrian Detection and Trajectory Prediction</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:50:33 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/twenty-five-years-of-air-quality-in-bangladesh-trends-seasonality-and-spatial-pollution-regimes/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/twenty-five-years-of-air-quality-in-bangladesh-trends-seasonality-and-spatial-pollution-regimes/]]></link>
			<title>Twenty-Five Years of Air Quality in Bangladesh: Trends, Seasonality, and Spatial Pollution Regimes</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:32:36 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/wide-deep-fahn-a-fuzzy-attention-hybrid-network-for-e-commerce-purchase-prediction-with-sequence-and-statistical-feature-fusion/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/wide-deep-fahn-a-fuzzy-attention-hybrid-network-for-e-commerce-purchase-prediction-with-sequence-and-statistical-feature-fusion/]]></link>
			<title>Wide &amp; Deep FAHN: A Fuzzy Attention Hybrid Network for E-Commerce Purchase Prediction with Sequence and Statistical Feature Fusion</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:21:00 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/recurrent-graph-reinforcement-learning-framework-for-task-offloading-in-internet-of-vehicles/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/recurrent-graph-reinforcement-learning-framework-for-task-offloading-in-internet-of-vehicles/]]></link>
			<title>Recurrent Graph Reinforcement Learning Framework for Task Offloading in Internet of Vehicles</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:16:49 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/notebridge-a-framework-for-real-time-multimodal-lecture-note-taking-with-evolving-knowledge-state/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/notebridge-a-framework-for-real-time-multimodal-lecture-note-taking-with-evolving-knowledge-state/]]></link>
			<title>NOTEBRIDGE: A Framework for Real-Time Multimodal Lecture Note-Taking with Evolving Knowledge State</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:08:03 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/yolo-hvconv-a-horizontally-vertically-aware-yolo-for-road-damage-detection/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/yolo-hvconv-a-horizontally-vertically-aware-yolo-for-road-damage-detection/]]></link>
			<title>YOLO-HVConv: A Horizontally-Vertically Aware YOLO for Road Damage Detection</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 19:00:50 +0000]]></pubDate>
		</item>
					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/what-actually-drives-profit-in-telecom-churn-retention-profit-aligned-targeting-versus-accuracy-and-calibration/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/what-actually-drives-profit-in-telecom-churn-retention-profit-aligned-targeting-versus-accuracy-and-calibration/]]></link>
			<title>What Actually Drives Profit in Telecom Churn Retention: Profit-Aligned Targeting versus Accuracy and Calibration</title>
			<pubDate><![CDATA[Tue, 29 Sep 2026 18:53:26 +0000]]></pubDate>
		</item>
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