Application gaps in Computer Science

Representative open questions

Showing 30 of 170 — one per source paper, highest-quality first.

• Federated learning for privacy-preserving skin cancer classification using deep neural networks (2026) · doi

  The proposed method outperforms state-of-the-art methods on the ISIC 2018 dataset, but its performance on other datasets (ISIC 2019 and PH2) is not compared.

• Blockchain-integrated machine learning framework for transparent smart contract vulnerability detection (2026) · doi

  CatBoost achieved macro-F1 of 0.98918 and 0.99156 accuracy on SmartBugs-Wild cluster classification, substantially outperforming vulnerability detection (F1 ~0.78-0.79). The transferability of cluster-level structural representations to vulnerability detection tasks within the same blockchain-integrated framework has not been explored.

• Inferring High-Dimensional Dynamic Networks Changing with Multiple Covariates (2026) · doi

  The observed inverse relationship between network size (decreasing node count) and network density (increasing interconnectivity) as radiation dose increases from 0 to 2 Gy is descriptive rather than mechanistically explained; the biological reasons why higher radiation selectively eliminates nodes while strengthening remaining gene-gene interactions in cancer versus control groups are not addressed.

• A Machine Learning Perspective on FinTech-Driven Inclusion: Addressing Algorithm Bias in Credit Scoring Systems in Developing Economies (2026) · doi

  The model fit indices (CFI = 0.943, TLI = 0.927, RMSEA = 0.058) demonstrate theoretical framework validity, but the paper does not address how explainability techniques (LIME, SHAP, attention mechanisms) should be implemented and evaluated within credit scoring algorithms to maintain the measured fairness-trust relationships when deployed across different cultural and regulatory contexts in developing economies.

• Prediction of sedimentation concentration profiles in inclined suspension systems: A data-driven neural network framework (2026) · doi

  The study reconstructed concentration profiles for inclined suspensions using TARG (time-averaged radiography) measurements, but the framework has not been extended to predict behavior under dynamic conditions such as flow reversal, oscillatory motion, or time-varying inclination angles relevant to drilling operations.

• AI in Cybersecurity: A Systematic Review and Conceptual Audit Model (2026) · doi

  The firewall rule management example demonstrates limitations of binary checks in identifying overly permissive rules and lateral movement risks, but the paper does not specify what AI techniques (machine learning classification, anomaly detection, knowledge graphs) should be applied to automate detection of these context-dependent vulnerabilities at scale.

• Research on a strongly generalizable fault diagnosis method based on adversarial transfer learning (2026) · doi

  Cross-type and cross-power level fault diagnosis (Table 5) showed significantly degraded HDAL performance (88.642% accuracy with 1.983% standard deviation) compared to same-type transfer (91.067%), yet the paper does not analyze which fault classes or reactor parameter combinations are most challenging across different reactor types and power levels. Specific investigation into how reactor type differences and variable power levels affect feature transferability in the HDAL adversarial domain adaptation framework is needed.

• Ocean: Object-aware Anchor-free Tracking with Matching-relation Learning (2026) · doi

  Ocean++ shows adaptability to first-person perspective tracking on the TREK dataset, but the specific challenges of egocentric viewing angles and potential limitations of the matching-relation learning mechanism under varied first-person camera motion and occlusions are not analyzed.

• Automated design of heuristics for resource-constrained project scheduling problem via regression algorithms (2026) · doi

  The paper demonstrates that single regression-designed priority rules require tens of times fewer schedule computations than AllPR on large projects, but does not investigate whether this computational savings generalizes to projects with atypical resource constraint characteristics (e.g., renewable vs. non-renewable resources, multiple constraint types). The efficiency advantage should be validated across heterogeneous constraint configurations in resource-constrained project scheduling.

• GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Model (2026) · doi

  GaussianSeal is evaluated only on the LGM 3D generative model. The transferability and adaptability of the lightweight bit modulation design to other 3D generative architectures (e.g., NeRF-based models, mesh generation models, or alternative diffusion-based 3D generators) has not been demonstrated or discussed.

• DAFRL: a dynamic adaptive mean field game-based multi-agent cooperative decision-making method (2026) · doi

  The DAFRL algorithm has not been extended to three-dimensional space with altitude coordination for UAV swarm operations. Current validation is limited to 2D interception scenarios, and the integration of altitude dimension and complex airflow disturbance models into the dynamic adaptive mean field game framework requires investigation.

• Scour depth prediction using machine learning and explainable AI: assessment of bridge vulnerability (2026) · doi

  ANN-GA achieved the highest NNSE value (0.9468) among neural network models, demonstrating effectiveness of genetic algorithm-based optimization; however, the paper does not compare computational training time, convergence speed, or resource requirements between ANN-GA, ANN-PSO, and ensemble methods, which is critical for deploying real-time scour prediction systems.

• A Motion-Based Compression and Tracking System for Video Camera Trap-Based Insect Behaviour Studies (2026) · doi

  Zero-shot object detection models show promise for addressing limitations of existing deep learning models in camera trap-based animal studies, but their application in camera trap-based insect behavior analysis and video compression workflows has not been evaluated. Future research should specifically test zero-shot object detection models for identifying previously undocumented insect species and behaviors in compressed camera trap videos.

• A general framework for Gaussian Splatting-based human-centric volumetric videos (2026) · doi

  Relighting and material editing techniques for 3D Gaussian Splatting remain underdeveloped, preventing realistic compositing of reconstructed human-centric subjects into large-scale or virtual environments, and blocking downstream applications requiring photorealistic material and lighting manipulation in volumetric videos.

• Adaptive distribution network reconfiguration with renewable energy and EV integration using reverse-multiverse learning archimedes algorithm (2026) · doi

  Comparative analysis shows RMLAA computation time improvements (5.93-6.96 seconds for IEEE test systems) but lacks evaluation on real-time reconfiguration requirements, communication delays in remote terminal units, and the minimum reconfiguration interval needed between successive switch operations in practical distribution systems with dynamic EV loads.

• Sensor Data Fusion in Healthcare Monitoring System with Appropriate Rule-based Model for Error Reduction (2026) · doi

  The $700 total cost of the fused system versus $100-$200 for individual sensors presents a significant cost-benefit trade-off, yet the paper does not analyze clinical outcomes, reduced hospitalizations, or long-term cost-effectiveness of the integrated approach to justify the implementation cost in real healthcare environments.

• Smart Prediction of Weather-Induced Flight Delays Applying Deep Learning (2026) · doi

  User session authentication does not persist credentials to the SQLite database, reducing multi-session continuity in the Flask-based flight delay prediction system. Database schema and authentication middleware must be redesigned to support stateful user sessions and historical prediction tracking.

• International Journal of Intelligent Data and Machine Learning (2026) · doi

  The paper applies probability adjustment techniques to two automotive use cases (SUV purchase and brake service response), but does not explore whether the adjustment formula remains valid across different industry verticals or product categories with fundamentally different response rate distributions and imbalance ratios beyond the 10% and 40% examples provided.

• ENHANCING IOT SECURITY USING LIGHTWEIGHT BLOCKCHAIN FOR DATA INTEGRITY AND TRACEABILITY (2026) · doi

  Interoperability between the proposed lightweight blockchain system and heterogeneous IoT devices using different communication protocols (Zigbee, LoRaWAN, NB-IoT) was mentioned as future work but not addressed in the current model. Integration mechanisms and protocol translation requirements for multi-protocol IoT networks remain undefined.

• Deep Learning Based Fish Species and Freshness Detection Using Convolutional Neural Networks (2026) · doi

  No evaluation of the Tamil text-to-speech module's accuracy, intelligibility, or performance in high-noise fish market environments is provided; the effectiveness of this accessibility feature for non-technical users requires field testing and user satisfaction metrics.

• Artificial Intelligence and Multi-Omics for Anticancer Drug Development and Repurposing (2026) · doi

  Generative models for anticancer drug discovery have not been thoroughly integrated into standard laboratory workflows for practical application. The specific computational architectures (GANs, generative models) required to augment sparse multi-omics datasets and improve drug repositioning predictions need empirical validation in clinical oncology settings.

• Unified URL and QR Based Phishing Detection Framework (2026) · doi

  The web-based implementation uses Flask/Streamlit, but the paper does not address how the framework integrates with existing security infrastructure (email gateways, browser extensions, corporate proxies) or handles browser-based QR scanning with varying camera quality and lighting conditions.

• Microscopic Image-Based TB Detection Using an Enhanced Bi-LSTM Model Optimized by Firefly Algorithm (2026) · doi

  The paper claims suitability for low-resource clinical environments but provides no evaluation of inference time, computational memory requirements, or model size for deployment on resource-constrained devices (e.g., field microscopy workstations with limited GPU/CPU capacity).

• Multiple-Class Classification of a Diesel Locomotive Engine’s Mechanical Condition Based on Wavelet Properties of Vibration Signals via Machine-Learning Techniques (2026) · doi

  The paper establishes that logistic regression with L1 regularization is suitable for real-time on-board diagnostic systems but does not provide algorithmic specifications for embedded implementation, memory footprint requirements, computational latency analysis, or optimization strategies for deployment on locomotive microcontroller platforms with limited processing capability.

• Employee Performance Classification and Monitoring using Machine zearning Models (2026) · doi

  Cloud integration is mentioned as a future enhancement but lacks specifics on data synchronization protocols, latency requirements, or how the Mediapipe facial landmark recognition and Flask backend architecture would be adapted for distributed edge-cloud deployments in hybrid workforce monitoring.

• A Comprehensive Review of Machine Learning Techniques for Student Academic Performance Prediction (2026) · doi

  Federated learning approaches for privacy-preserving student performance prediction across institutions have not been empirically evaluated. Implementation and validation of federated learning systems that maintain student privacy while enabling cross-institutional collaboration in predictive modeling remains an open research direction.

• Real-Time Bank Transaction Fraud Detection Using Kafka and Machine Learning (2026) · doi

  Integration of blockchain technology for improving transparency and tamper-resistance of transaction records in the Kafka-based fraud detection system has been suggested but no technical specifications, consensus mechanisms, or performance trade-offs have been defined or evaluated.

• ON DOMINATION IN COARSE DEG-CENTRIC GRAPHS (2026) · doi

  The paper provides domination results for wheel-derived graphs (double wheel, gear, web, sunflower) and cycle-derived graphs (sunlet), but no results are presented for domination in coarse deg-centric graphs of path-based families, tree families, or bipartite graph constructions such as crown graphs or complete bipartite graphs.

• Batik Motif Recognition Using the BGP-Model: A Hybrid GLCM-PCA Approach with Machine Learning Classifiers (2026) · doi

  The study does not address computational complexity or inference time for the BGP-Model pipeline. Real-time and mobile implementation requirements for batik digitization systems require benchmarking of processing time, memory footprint, and model optimization techniques on edge devices.

• A Systematic Review of Machine Learning Approaches For AI-Driven Fraud Detection in Loyalty Programs (2026) · doi

  Graph-based models for mileage pooling and partner-transfer abuse require an integrated graph-ready data architecture, but the paper does not specify which graph construction methods, node/edge feature representations, or graph neural network architectures perform best when legacy loyalty systems lack native relational data infrastructure.