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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-explainable-efficientnetb0-based-framework-for-multi-class-retinal-disease-classification-using-fundus-images-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-efficientnetb0-based-framework-for-multi-class-retinal-disease-classification-using-fundus-images-2/]]></link>
			<title>An Explainable EfficientNetB0-Based Framework for Multi-Class Retinal Disease Classification Using Fundus Images</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 15:43:14 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lightskinnet-protocol-aware-skin-lesion-classification-with-segmentation-guided-networks/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/lightskinnet-protocol-aware-skin-lesion-classification-with-segmentation-guided-networks/]]></link>
			<title>LightSkinNet: Protocol-Aware Skin Lesion Classification with Segmentation-Guided Networks</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 14:44:27 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-and-class-balanced-gradient-boosting-framework-for-heart-disease-prediction-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-and-class-balanced-gradient-boosting-framework-for-heart-disease-prediction-2/]]></link>
			<title>An Explainable and Class-Balanced Gradient Boosting Framework for Heart Disease Prediction</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 14:30:12 +0000]]></pubDate>
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			<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 Optimized MAC Protocol for WBANs Managing Multi-class and Multi-load in IEEE 802.15.6 Superframes Using Hysteretic Q-learning</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 13:57:03 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/design-and-implementation-of-a-resilient-multi-branch-wan-for-sonali-bank-plc-eigrp-routing-dual-isp-redundancy-and-hierarchical-ip-addressing/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/design-and-implementation-of-a-resilient-multi-branch-wan-for-sonali-bank-plc-eigrp-routing-dual-isp-redundancy-and-hierarchical-ip-addressing/]]></link>
			<title>Design and Implementation of a Resilient Multi-Branch WAN for Sonali Bank PLC: EIGRP Routing, Dual-ISP Redundancy, and Hierarchical IP Addressing</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 13:36:30 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/development-of-a-piezoresistive-e-textile-sock-for-in-situ-dynamic-plantar-pressure-assessment-3/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/development-of-a-piezoresistive-e-textile-sock-for-in-situ-dynamic-plantar-pressure-assessment-3/]]></link>
			<title>Development of a Piezoresistive E-Textile Sock for In Situ Dynamic Plantar Pressure Assessment</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 13:20:53 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ai-enhanced-digital-twin-with-hardware-in-the-loop-deployment-for-real-time-lithium-ion-battery-state-of-health-estimation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/ai-enhanced-digital-twin-with-hardware-in-the-loop-deployment-for-real-time-lithium-ion-battery-state-of-health-estimation/]]></link>
			<title>AI-Enhanced Digital Twin with Hardware-in-the-Loop Deployment for Real-Time Lithium-Ion Battery State-of-Health Estimation</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 13:15:27 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-context-aware-xgboost-framework-for-vulnerability-remediation-recommendation-using-github-security-advisories/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-context-aware-xgboost-framework-for-vulnerability-remediation-recommendation-using-github-security-advisories/]]></link>
			<title>A Context-Aware XGBoost Framework for Vulnerability Remediation Recommendation Using GitHub Security Advisories</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 13:04:47 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-lightweight-ensemble-deep-learning-framework-for-automated-malaria-parasite-detection-from-microscopic-blood-cell-images-3/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-lightweight-ensemble-deep-learning-framework-for-automated-malaria-parasite-detection-from-microscopic-blood-cell-images-3/]]></link>
			<title>An Attention-Enhanced Explainable Deep Learning Framework for Cervical Cancer Detection Through Microscopic Image Analysis</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:59:15 +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[Sat, 31 Oct 2026 12:49:38 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/computer-vision-based-soil-health-analysis-using-machine-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/computer-vision-based-soil-health-analysis-using-machine-learning/]]></link>
			<title>Computer Vision-based Soil Health Analysis using Machine Learning</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:49:10 +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 “Aakash Deep” Hub: A Sustainable and AI- Driven Li-Fi Framework for the Consumer Market in Bangladesh</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:48:19 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/chi-square-feature-selection-and-smote-balanced-ensemble-learning-for-explainable-cervical-cancer-risk-prediction/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/chi-square-feature-selection-and-smote-balanced-ensemble-learning-for-explainable-cervical-cancer-risk-prediction/]]></link>
			<title>Chi-Square Feature Selection and SMOTE-Balanced Ensemble Learning for Explainable Cervical Cancer Risk Prediction</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:35:04 +0000]]></pubDate>
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					<item>
			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/esg-and-investment-decisions-the-moderating-role-of-risk-tolerance-among-individual-investors-in-bangladesh-2/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/esg-and-investment-decisions-the-moderating-role-of-risk-tolerance-among-individual-investors-in-bangladesh-2/]]></link>
			<title>ESG and Investment Decisions: The Moderating Role of Risk Tolerance among Individual Investors in Bangladesh</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:30:31 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/banglaclr-structure-aware-contrastive-representation-learning-for-bengali-character-recognition/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/banglaclr-structure-aware-contrastive-representation-learning-for-bengali-character-recognition/]]></link>
			<title>BanglaCLR: Structure-Aware Contrastive Representation Learning for Bengali Character Recognition</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:25:04 +0000]]></pubDate>
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			<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[Sat, 31 Oct 2026 12:16:47 +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[Sat, 31 Oct 2026 12:10:32 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/brixnet-efficient-depthwise-separable-cnn-for-lightweight-brain-stroke-classification-from-ct-images/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/brixnet-efficient-depthwise-separable-cnn-for-lightweight-brain-stroke-classification-from-ct-images/]]></link>
			<title>BriXNet: Efficient Depthwise-Separable CNN for Lightweight Brain Stroke Classification from CT Images</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 12:10:14 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/crop-yield-prediction-using-explainable-machine-learning-on-multi-state-agricultural-data/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/crop-yield-prediction-using-explainable-machine-learning-on-multi-state-agricultural-data/]]></link>
			<title>Crop Yield Prediction Using Explainable Machine Learning on Multi-State Agricultural Data</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 11:58:32 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/dual-attention-resnet50-lstm-for-video-based-human-action-recognition/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/dual-attention-resnet50-lstm-for-video-based-human-action-recognition/]]></link>
			<title>Dual-Attention ResNet50-LSTM for Video-Based Human Action Recognition</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 11:57:42 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-transfer-learning-framework-for-early-detection-of-diabetic-retinopathy-using-deep-learning/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/an-explainable-transfer-learning-framework-for-early-detection-of-diabetic-retinopathy-using-deep-learning/]]></link>
			<title>An Explainable Transfer Learning Framework for Early Detection of Diabetic Retinopathy Using Deep Learning</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 11:24:40 +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[Sat, 31 Oct 2026 11:04:40 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/transfer-learning-for-dermatological-image-classification-a-comparative-study-of-adaptation-strategies-under-leakage-aware-evaluation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/transfer-learning-for-dermatological-image-classification-a-comparative-study-of-adaptation-strategies-under-leakage-aware-evaluation/]]></link>
			<title>Transfer Learning for Dermatological Image Classification: A Comparative Study of Adaptation Strategies under Leakage-Aware Evaluation</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 11:04:37 +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[Sat, 31 Oct 2026 11:03:50 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/development-of-smart-grid-distribution-systems-in-emerging-economies-a-bangladesh-perspective/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/development-of-smart-grid-distribution-systems-in-emerging-economies-a-bangladesh-perspective/]]></link>
			<title>Smart Grid Transformation of Bangladesh Distribution Networks: Current Status, Challenges, and Future Roadmap</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 11:02:32 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/supercapacitor-based-energy-storage-for-residential-pv-applications-a-quantitative-comparative-study/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/supercapacitor-based-energy-storage-for-residential-pv-applications-a-quantitative-comparative-study/]]></link>
			<title>System-Level Assessment of Supercapacitors in Residential PV Storage: Economics and Hybrid Integration</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 10:58:39 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/global-diabetes-mortality-analysis-a-reproducible-who-data-driven-study-of-trends-regional-disparities-and-prevalence-mortality-relationships-2000-2014-3/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/global-diabetes-mortality-analysis-a-reproducible-who-data-driven-study-of-trends-regional-disparities-and-prevalence-mortality-relationships-2000-2014-3/]]></link>
			<title>Global Diabetes Mortality Analysis: A Reproducible WHO Data-Driven Study of Trends, Regional Disparities, and Prevalence-Mortality Relationships (2000–2014)</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 10:56:42 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/international-equity-markets-market-integration-financial-contagion-volatility-correlation-analysis-risk-adjusted-return-stationarity-jarque-bera-test-augmented-dickey-fuller/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/international-equity-markets-market-integration-financial-contagion-volatility-correlation-analysis-risk-adjusted-return-stationarity-jarque-bera-test-augmented-dickey-fuller/]]></link>
			<title>international equity markets, market integration, financial contagion, volatility, correlation analysis,  risk-adjusted return, stationarity, Jarque–Bera test, Augmented Dickey–Fuller test.</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 10:10:00 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/polypsegnet-an-attention-guided-multi-scale-feature-fusion-network-for-accurate-colorectal-polyp-segmentation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/polypsegnet-an-attention-guided-multi-scale-feature-fusion-network-for-accurate-colorectal-polyp-segmentation/]]></link>
			<title>PolypSegNet: An Attention-Guided Multi-Scale Feature Fusion Network for Accurate Colorectal Polyp Segmentation</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 10:00:01 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/vehicle-to-grid-for-renewable-energy-integration-in-bangladesh-a-degradation-aware-critical-review-and-future-research-framework/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/vehicle-to-grid-for-renewable-energy-integration-in-bangladesh-a-degradation-aware-critical-review-and-future-research-framework/]]></link>
			<title>Vehicle-to-Grid for Renewable Energy Integration in Bangladesh: A Degradation-Aware Critical Review and Future Research Framework</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 09:50:53 +0000]]></pubDate>
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			<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>mIoU Under Scrutiny: Benchmarking Self-Supervised Pretraining for Lung Tumor CT Segmentation</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 09:43:55 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-modular-distributed-iot-architecture-for-closed-loop-hydroponic-monitoring-and-control-with-image-based-plant-observation/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/a-modular-distributed-iot-architecture-for-closed-loop-hydroponic-monitoring-and-control-with-image-based-plant-observation/]]></link>
			<title>A Modular Distributed IoT Architecture for Closed-Loop Hydroponic Monitoring and Control with Image-Based Plant Observation</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 09:31:37 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/bridging-the-gap-use-symbolic-language-as-a-prompt-between-human-emotion-and-machine-logic/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/bridging-the-gap-use-symbolic-language-as-a-prompt-between-human-emotion-and-machine-logic/]]></link>
			<title>Bridging the Gap: Using Symbolic Language as a Prompt Between Human Emotion and Machine Logic*</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 09:24:28 +0000]]></pubDate>
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			<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, 31 Oct 2026 09:21:48 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/do-macroeconomic-predictors-improve-bangladesh-inflation-forecasts-a-leakage-safe-econometric-and-machine-learning-evaluation-2010-2025-abstract-this-study-evaluates-whether-lagged-macroeconomic-in/]]></guid>
			<link><![CDATA[https://nps-ss.com.au/nps-paper-submissions/do-macroeconomic-predictors-improve-bangladesh-inflation-forecasts-a-leakage-safe-econometric-and-machine-learning-evaluation-2010-2025-abstract-this-study-evaluates-whether-lagged-macroeconomic-in/]]></link>
			<title>Do Macroeconomic Predictors Improve Bangladesh Inflation Forecasts? A Leakage-Safe Econometric and Machine-Learning Evaluation, 2010-2025 Abstract- This study evaluates whether lagged macroeconomic indicators improve</title>
			<pubDate><![CDATA[Sat, 31 Oct 2026 09:17:11 +0000]]></pubDate>
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			<guid><![CDATA[https://nps-ss.com.au/nps-paper-submissions/leveraging-ai-driven-cloud-computing-for-advanced-health-prediction-models/]]></guid>
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			<pubDate><![CDATA[Sat, 31 Oct 2026 09:16:08 +0000]]></pubDate>
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