Cover
Issue:2026 - Vol. 11 - Iss.2
Published:2026.06
Articles:12 articles
International Journal of Advanced Network, Monitoring and Controls
IJANMC
The journal aims to providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills, especially in the fields of advanced network, future network, monitoring, sensors and controls. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed, Only original… More
2026 Vol.11 Iss.2 (12 articles)
Cover
Cover
Cover202602
IJANMC 2026, 11(2), 0-0;
Content
Contents202602
IJANMC 2026, 11(2), 0-0;
Research paper
Research on the MS-YOLO Model Based on Deep Learning for Small Object Detection in Product Recognition
Abstract: Traditional product recognition methods are limited by human experience and complex environments, leading to low accuracy and efficiency. The algorithm proposed in this paper significantly enhances the efficiency of retail and warehouse management, addressing these issues. This paper improves upon the YOLOv7 model and proposes a new model, MS-YOLO, to tackle the challenges of small object and occlusion detection. An improved CSPNet backbone network is designed, and the Ghost module is introduced to improve computat…
Keywords: Deep Learning; Product Recognition; YOLOv7; Dataset; Algorithm Optimization
IJANMC 2026, 11(2), 1-11;
https://doi.org/10.58244/ijanmc.263895
Research paper
A MOOC Course Recommendation Method Integrating Reinforcement Learning and Neural-Symbolic Reasoning
Abstract: To address the issue of overloaded course resources on MOOC platforms and the poor effectiveness of personalized course recommendations for users, this paper proposes a MOOC course recommendation method that integrates reinforcement learning and neural-symbolic reasoning. The method uses neural networks to extract features of user behavior in MOOCs, the neural-symbolic reasoning module to explore paths in the knowledge graph, and reinforcement learning to simulate user-course interactions for recommendation decisio…
Keywords: Knowledge Graph; Reinforcement Learning; Neuro-Symbolic; Explainable Recommendation
IJANMC 2026, 11(2), 12-19;
https://doi.org/10.58244/ijanmc.263660
Research paper
Research on Image Super-Resolution Algorithm Based on Improved GAN
Abstract: Image super-resolution reconstruction aims to transform low-resolution blurred images into high-resolution images under the same scene. Due to its practical value and theoretical significance, this technology is widely used in computer vision and image processing. In recent years, deep learning-based super-resolution algorithms have shown strong performance. However, most existing deep learning methods suffer from a common issue: when reconstructing images at large magnification factors, the results tend to be over…
Keywords: Deep Learning; Image Super Resolution; Generative Adversarial Network; Attention Mechanism
IJANMC 2026, 11(2), 20-28;
https://doi.org/10.58244/ijanmc.263661
Research paper
A mapping method integrating enhanced multi-line laser radar and IMU
Abstract: Most traditional SLAM algorithms suffer severe performance degradation in complex outdoor scenes with pedestrians and moving vehicles, leading to blurred and deformed environmental maps. This paper proposes FE-LIM, a mapping algorithm fusing multi-line LiDAR and IMU. The algorithm judges dynamic points via inter-frame point offset differential analysis, clusters dynamic outliers by DBSCAN and removes them. LiDAR and IMU timestamps are strictly aligned, and EKF is used for sensor fusion to reduce cumulative drift. A…
Keywords: Simultaneous Positioning and Mapping; Complex Outdoor Environment; Differential Analysis; Dynamic Point Cloud Removal
IJANMC 2026, 11(2), 29-38;
https://doi.org/10.58244/ijanmc.263662
Research paper
Hybrid Genetic and Ant Colony Optimization Multipath Congestion-Free Routing Algorithm
Abstract: In response to the critical issues of link saturation and excessive latency stemming from inter-cluster coordination within partitioned Vehicular Ad-hoc Networks (VANETs), this research develops a Hybrid Genetic-Ant Colony Multipath Routing scheme (GAAC) designed for congestion-free data dissemination. By synthesizing node buffer occupancy, relative mobility patterns, and temporal constraints into a comprehensive assessment framework, the routing selection is reformulated as a multi-constrained optimization challen…
Keywords: Keywords-Congestion Control; Genetic-Ant Colony Optimization; Link Stability; Multipath Routing; Vehicular Networking
IJANMC 2026, 11(2), 39-52;
https://doi.org/10.58244/ijanmc.263664
Research paper
Research on Small Object Detection in UAV Aerial Imagery Based on Improved YOLOv11
Abstract: To enhance the robustness of small object detection in UAV aerial imagery, this paper proposes an improved detection method based on the YOLOv11 architecture. Initially, to mitigate the occlusion of small-target features by surrounding background clutter, a Multi-scale Edge Information Enhancement module is introduced to amplify fine-grained local details. Subsequently, an efficient feature fusion architecture is constructed to achieve comprehensive integration of global contextual semantics with small-object featu…
Keywords: Small Object Detection; Feature Enhancement; Feature Pyramid; Task Aligned
IJANMC 2026, 11(2), 53-62;
https://doi.org/10.58244/ijanmc.263665
Research paper
Apricity: An AI-Powered Mental Health Companion for CBT-Based Emotion Tracking and Analysis
Abstract: The escalating global mental health crisis has high- lighted a critical shortage of accessible therapeutic resources. While digital health interventions exist, many rely on static jour- naling or rudimentary rule-based chatbots that fail to capture the semantic nuance of complex human emotions. This paper presents the design, development, and evaluation of “Apricity,” a comprehensive AI-powered mental health companion application. Grounded in the principles of Cognitive Behavioral Therapy (CBT), the system provides…
Keywords: Mental Health; Cognitive Behavioral Therapy (CBT); Natural Language Processing (NLP); DeBERTa; Trans-former Models; Full-Stack Development; Emotion Recognition
IJANMC 2026, 11(2), 63-72;
https://doi.org/10.58244/ijanmc.263666
Research paper
Theoretical Model for Balancing Reliability and Latency in Hybrid CRC–Polar Coding for 6G Wireless Networks
Abstract: Polar codes and their CRC-assisted derivatives have become important facilitators of ultra-reliable low-latency communication (URLLC) in 5G wireless networks, especially in the cases of applications where short packets have to be transmitted, and error rates must be nearly zero, such as autonomous vehicles, remote medical treatments, and automation of industrial devices. Although the dependability has been proved to be beneficial when the incorporation of codes of CRC-Polar is performed previously, the studies freq…
Keywords: Polarcodes; Blocklength; Latency
IJANMC 2026, 11(2), 73-88;
https://doi.org/10.58244/ijanmc.263667
Research paper
Design and Implementation of a Low-Threshold Automatic Virtual Scene Generation Framework Based on Pix2Pix and Unity
Abstract: To address the issues of low efficiency in manual modeling of virtual scenes and the high engineering threshold of existing AI generation technologies, an offline automatic virtual scene generation framework based on Generative Adversarial Networks (GAN) and the Unity engine is proposed. With the Pix2Pix conditional generation model as its core, this framework enables the automatic generation of indoor scene layouts. It completes the reconstruction from layouts to 3D scenes through the Unity parsing-generation modu…
Keywords: Virtual Scene Generation; Generative Adversarial Network; Pix2Pix; Unity Engine; Offline Collaboration; Procedural Content Generation
IJANMC 2026, 11(2), 89-98;
https://doi.org/10.58244/ijanmc.263668
Research paper
Research on Multi-modal Object Detection Methods for Low-Light Scenarios Based on Dual-Stream Interleaved Fusion
Abstract: Object detection in low-light environments poses a challenging task. Existing work involving visible and infrared light primarily focuses on fusion enhancements across multiple scales of the backbone network. This paper proposes and constructs the Prior Difference Interleaved Network (PDIN), a dual-stream detector based on the YOLOv11n framework. Its core innovation lies in the interleaved deep fusion strategy combining CPCA and SDI. Specifically, the model introduces a Channel-Prior Convolutional Attention (CPCA)…
Keywords: Object Detection; Feature Fusion; Visible-Infrared Light; Dynamic Weighting; Semantic Differences
IJANMC 2026, 11(2), 99-110;
https://doi.org/10.58244/ijanmc.263663
