Innovation in Science and Technology

Hacking Is an Unauthorized Access in Electronic Devices: Skills Technologies Are Necessary to Enhance Defense Strategies

Haradhan Kumar Mohajan — 2026-07-03

Hacking is the technique of finding the weaknesses in the network system that exploits to gain unauthorized access to personal or business data that are in the networks, and the hacker is responsible for the legal consequences of his/her actions. The hacker has basic knowledge, desire, motivation, deep patience, planning workability, and financial supports. Usually an unethical hacker (black hat hacker) is a malicious guy who tries to steal, leak, and destroy confidential and valuable data and other sensitive information of the computer systems without permission of the user. S/he can usually be organized into two types of attacks: mass attacks and targeted attacks. On the other hand, an ethical hacker (white hat hacker) tries to strengthen the security mechanisms of the organization by exploring the weaknesses of it. This study tries to discuss the aspects of unethical hacking, types of hackers, and their behaviors.

Design of BIM and IoT-Based Tunnel Construction Monitoring Data Fusion and Safety Early Warning System

Xiaoqing Cheng — 2026-07-03

The tunnel construction environment is complex, and traditional monitoring methods suffer from poor timeliness and insufficient data utilization, making it difficult to support real-time safety management and control during tunnel construction. This paper designs a construction monitoring and early warning system that integrates Building Information Modeling (BIM) and Internet of Things (IoT) technologies, adopting a “cloud-edge-device” three-tier distributed architecture. At the device layer, a multi-source heterogeneous sensor network is deployed; at the edge layer, edge computing gateways are installed for local data preprocessing and real-time analysis; at the platform layer, a data fusion analysis engine and a BIM visualization engine are integrated. For data fusion, the belief Hellinger distance is introduced to improve the Dempster-Shafer (D-S) evidence theory, effectively resolving conflicts among highly contradictory evidence sources. For safety early warning, a “4+4+N” hierarchical index system is established, and a progressively deepened three-level early warning mechanism is constructed, encompassing single-index threshold judgment, multi-parameter fusion evaluation, and Long Short-Term Memory (LSTM) time-series prediction. Finally, the system is validated through field deployment at the Yingeling extra-long tunnel in Hainan Province. The results that the proposed data fusion method achieves an accuracy of 92.5%, a 20.2% improvement over traditional D-S evidence theory. The early warning system attains an accuracy of 92.5% with a false alarm rate of 8.3%, a missed alarm rate of 3.1%, and an average response time of 2.8 seconds providing reliable technical support for tunnel construction safety management.

A Survey of Classic Machine Learning Algorithms: Principles and Applications

Xi Long — 2026-07-07

Classical machine learning algorithms constitute the fundamental cornerstone of modern data science and intelligent system development. While deep learning has achieved transformative breakthroughs across numerous fields in recent years, classical methods remain indispensable in practical scenarios characterized by limited training data, stringent interpretability requirements, or constrained computational resources. Nevertheless, existing studies generally lack a systematic, unified, and beginner-friendly comprehensive survey that integrates theoretical elaboration, multi-dimensional comparative analysis, and actionable algorithm selection guidance.

To fill this research gap, this paper presents a thorough investigation of ten representative classical machine learning algorithms: Linear Regression, Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Adaptive Boosting, K-Means, and Principal Component Analysis. Each algorithm is explicated within a consistent structural framework, covering its mathematical formulation, core working mechanism, distinct advantages, inherent limitations, and typical application scenarios. Furthermore, a horizontal comparative analysis is conducted across seven critical dimensions, and a practical algorithm selection framework with targeted recommendations for typical industrial scenarios is proposed.

This work constructs a complete and logically coherent knowledge system of classical machine learning, serving as an accessible and pragmatic reference for novice learners and engineering practitioners. It also provides insights into future integration trends between classical algorithms and emerging technologies including large language models, explainable artificial intelligence, edge intelligence, automated machine learning, and federated learning.

Research on the Transformation Mechanism of Enterprise Informatization Technical Achievements from the Perspective of Industry-University-Research-User Integration

Yingjie Feng — 2026-07-10

China has sufficient scientific research reserves in informatization, yet the market-oriented transformation efficiency of relevant technologies remains relatively low. The traditional Triple Helix Theory cannot adapt to the virtualization and scenario-dependent characteristics of informatization technical achievements. Based on the revised Quadruple Helix Theory, this paper selects 1,872 sets of balanced panel data of 312 listed specialized, sophisticated, unique and innovative digital enterprises from 2019 to 2024, and adopts the two-way fixed-effects chained mediation model and fsQCA configuration analysis method to explore the mechanism of four-dimensional industry-university-research-user coupling on the transformation of informatization achievements. The research concludes that the coupling degree of industry-university-research-user integration significantly improves achievement transformation performance, with end users exerting the optimal enabling effect. Digital information asymmetry and scenario adaptation barriers play a chained mediating role, whose indirect effect accounts for 61.29%. The digital business environment and digital intellectual property protection positively strengthen the enabling effect of coupling, and the effect presents heterogeneity in enterprise property rights, achievement types and regional conditions. There are four collaborative configurations for efficient achievement transformation, and insufficient user participation and inadequate cross-subject data trust are the core inducements of failed transformation. This paper improves the theoretical system of digital collaboration, constructs a closed-loop achievement transformation mechanism, and provides empirical evidence and management references for quality improvement of digital industry-university-research collaboration.