ISSN
2424-8460(Online)
2251-2608(Print)
Published
Table of Contents
Open AccessArticles
by Yiran Yang
2025,12(1);
25 Views
Abstract
This paper focuses on the current booming AIGC technology, aiming at the current situation of Panjin
visual publicity, and discusses the application strategy and practical path of artificial intelligence technology in
rural publicity design. Explore the activation and promotion of rural publicity design under the background of the
era of digital intelligence. It aims to provide emerging productivity for the design field through the application of
AIGC technology, improve the efficiency and quality of rural publicity design, and promote the deep integration
of digital technology and rural revitalization with artificial intelligence technology.
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Open AccessArticles
by Yihan Wang, Juan Cao
2025,12(1);
21 Views
Abstract
In the era of information explosion, traditional computer information management methods are
difficult to extract effective information from massive data to support forward-looking decision-making. Artificial
Intelligence (AI) technology provides a scientific basis for organisational decision-making by predictive analysis
and mining the potential patterns and trends of data. This paper systematically discusses the application of AI in
predictive analysis for computer information management, covering key technologies such as machine learning
and deep learning, and combining cases such as system performance prediction, user behaviour analysis and
market trend prediction to demonstrate the practical effects of AI in improving reliability, conversion rate and
return on investment. At the same time, the article points out the challenges of data quality, model interpretability
and privacy security, and looks forward to the future development direction of the integration with IoT, big data
and other technologies.
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Open AccessArticles
by Tuo Zheng
2025,12(1);
17 Views
Abstract
This paper introduces new energy vehicles and carries out corresponding control and analysis based on
the relevant principles of new energy vehicles. As a remote monitoring and regulation port, drivers supported by
new energy vehicles and corresponding automation equipment need to be further connected and communicated.
The monitoring network of new energy vehicles includes multi-level management control and data acquisition
functions, including communication drive management, PLC process management and automation equipment
process. Through the real-time data recording and alarm, the motor control can be effectively set up to ensure the
safe operation of the motor control system.
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Open AccessArticles
by Xintian Wang
2025,12(1);
28 Views
Abstract
With the growing demand for security monitoring, traditional image signal processing methods are
facing challenges in terms of accuracy and efficiency. The development of deep learning technology has brought
new opportunities for the application of image signal processing in security monitoring. This paper deeply
studies the application of deep learning in signal processing of security monitoring images, including target
detection, behavior recognition, image enhancement and so on. This paper analyzes the advantages of deep
learning algorithm in processing security monitoring images, such as adaptability to complex scenes and efficient
processing of large amounts of data. At the same time, it also discusses the problems it faces, such as data privacy,
computing resource consumption, etc., and looks forward to the future development trend.
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Open AccessArticles
by Yihe Zhao
2025,12(1);
15 Views
Abstract
Shipbuilding is a complex and resource-intensive industry that requires high efficiency and precision.
With the advancement of artificial intelligence (AI) and intelligent manufacturing technologies, there is a
growing opportunity to optimize shipbuilding strategies. This paper explores the application of AI in enhancing
shipbuilding efficiency through intelligent manufacturing, focusing on key areas such as predictive maintenance,
process automation, quality control, and supply chain optimization. By integrating AI-driven techniques such
as machine learning, computer vision, and digital twin technology, the shipbuilding industry can significantly
reduce costs, improve production accuracy, and accelerate delivery times. This research provides an overview of
existing AI methodologies, discusses their potential benefits, and outlines the challenges and future directions of
AI-optimized intelligent manufacturing in shipbuilding.
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Open AccessArticles
by Chongyang Kang, Xiaofang Yang, Zhuoying He, Kedi Mi, Jie Hu, Xiaorong Yu
2025,12(1);
17 Views
Abstract
Sulfur dioxide(SO2) is an important pollutant gas that affects environment of our lives. Although we
had made lots of detections, but still can not receive the distribution of SO2 in the world. Compared with great
success in UV-vis spectrometers from remote sensing in OMI and OMPS, can provide SO2 data in a huge range
and daily, but cannot receive data as there is no sunshine, this is difficult for researchers to do their study in global
or area in high latitudes. In this paper, we tried to supplement the PBL SO2 in the whole world, based on the data
of OMISO2, by the function derivative algorithm to segment approximation, and verified the method in the area,
where OMI SO2 data are complete. The results show that the spatial distribution of SO2 in the global atmospheric
boundary layer is obviously latitudinal zonality. SO2 columns and its variation trend are the same or similar in
the same latitude during the year. Through verification we found that the partition below 5° latitude seldom affect
the estimation, The accuracy is good in the region where there is no SO2 columns mutation, more than 90% of
the grids which differences between the estimation and the truth are in a range of [-0.2DU, 0.2DU], less than the
multi-day OMI monthly error of 0.2DU, the function is suitable in this situation, and the estimation will be biased
in the region where the volcanic eruption, causes the monthly average SO2 columns mutation, but choosing data
from the month nearby with no volcanic eruption can helps to eliminate the effects of volcanic eruptions and also
can estimate the areas affected by volcanic eruptions.
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Open AccessArticles
by Bo Huang, Yanni Hu
2025,12(1);
19 Views
Abstract
This paper explores the connection and effective management of smart home systems with renewable
energy devices. Analyzing the current status of connections and existing issues, it proposes effective management
strategies such as energy monitoring and data analysis, energy storage system management, and device operation
control. Through two practical case studies, the paper validates the feasibility and benefits of the collaborative
application of smart homes and renewable energy devices. Research indicates that by unifying communication
protocols, applying middleware, and leveraging Internet of Things (IoT) technologies, combined with intelligent
management strategies, the utilization efficiency of renewable energy in smart homes can be significantly
improved, achieving energy-saving and environmental protection goals. Finally, the paper looks ahead to
future development trends, pointing out that the deeper integration of artificial intelligence technologies and
the improvement of industry standards will further promote the integrated development of smart homes and
renewable energy.
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Open AccessArticles
by Yuqing Sun
2025,12(1);
18 Views
Abstract
Community is the foundation of urban governance. Digital technology has become central to
modernizing China’s grassroots governance. This study examines the “Xiaowu Life” platform in Wuhou District,
Chengdu, revealing how it integrates community resources and fosters collaborative governance. By forming
an organizational community linking government and residents, a value community with shared goals, an
action community with coordinated efforts, and an interest community balancing diverse needs, the platform
drives governance innovation. Future research should explore deeper digital integration to enhance efficiency,
collaboration, and sustainability in urban community governance.
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Open AccessArticles
by Jin Zhang
2025,12(1);
18 Views
Abstract
Against the backdrop of the globalization era, cross - cultural communication is not only a current
economic and social necessity but also an inherent need for the dissemination of Chinese culture. At present, the
international dissemination of Chinese excellent traditional culture faces the dilemma of “cultural aphasia”, and
this paper explores the role of artificial intelligence (AI) technology in breaking this situation. Firstly, it deeply
analyzes the applicability of core AI technologies such as machine learning, deep learning, natural language
processing, and computer vision in cultural dissemination. Secondly, in combination with the actual situation,
it discusses the challenges in terms of technical performance, technology update, and talent adaptation during
the process of AI - powered cultural dissemination, and proposes targeted countermeasures. This paper provides
certain theoretical support and practical guidance for the transformation of Chinese excellent traditional culture
from “cultural aphasia” to “global voice”.
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Open AccessArticles
by Bo Han, Hua Zhu
2025,12(1);
18 Views
Abstract
This research compares Tencent Hunyuan and ChatGPT 4 in translation. While these models excel
in long-text processing and multilingual translation, they still struggle with capturing deeper meanings, tones,
and culturally specific expressions. Context sensitivity affects translation accuracy and fluency, and each
model has pros and cons in complex contexts. The study offers references for improving model translation and
understanding language - processing mechanisms.
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Open AccessArticles
by ZheMing Xing
2025,12(1);
22 Views
Abstract
With the rapid advancement of electronic science and technology, the automation control of smart
substations has become increasingly intelligent and efficient. This paper explores the deep integration of
electronic science and technology in power system automation, focusing on key technologies such as advanced
sensors, digital signal processing, artificial intelligence (AI), and the Internet of Things (IoT). Through extensive
data analysis, case studies, and experimental evaluation, this research demonstrates how these technologies
enhance power system automation, improve grid stability, optimize energy management, and address existing
challenges in power distribution.
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Open AccessArticles
by Wuyun Zhaola
2025,12(1);
21 Views
Abstract
This paper introduces the impact of quantum computing on the security of financial data encryption
and analyzes the potential threats that quantum computing may pose to traditional encryption algorithms.
Firstly, the basic principles and advantages of quantum computing were briefly described, especially its
potential to crack classical encryption algorithms such as RSA and ECC and improve computational efficiency.
Secondly, the impact of quantum computing on financial transactions, payment systems, privacy protection, and
identity authentication was explored, and the security risks faced by financial data were pointed out. Finally,
countermeasures were proposed, including post quantum encryption technology, quantum key distribution (QKD),
and cross domain cooperation, aimed at improving the security of the financial system. Although quantum
computing brings challenges, the financial industry can address this emerging threat and ensure data security
through technological innovation and strategic deployment.
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Open AccessArticles
by Zihui Ding, Chenyang Wang, Di Zhang, Xin Hu, Jin Wang, Sheng Chen
2025,12(1);
18 Views
Abstract
Rolling bearings are often in a state of high-speed operation, making them highly susceptible to
failure. To address this issue, the WOA-VMD-YOLOv8 fault diagnosis model was designed by combining the
advantages of Whale optimization algorithm (WOA), variational mode decomposition (VMD) and YOLOv8.
The bearing vibration signals collected by Case Western Reserve University were used as experimental data.
WOA was applied to optimize the VMD parameters, and the time-frequency diagrams of the WOA-VMD output
signals were used as the dataset for YOLOv8. The experimental results show that, compared to the Wavelet
Transform(WT)-YOLOv8, the WOA-VMD-YOLOv8 achieves better predictive performance for bearing faults,
with Recall rate of 99.7%, mAP@0.5 of 99.5%, and mAP@0.5-0.95 of 99.4%. Therefore, the WOA-VMDYOLOv8 demonstrates practical value in bearing fault detection technology.
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Open AccessArticles
by Haolan Li
2025,12(1);
21 Views
Abstract
This paper delves into the optimization of computer vision algorithms for large - scale models.
With the rapid development of deep learning in computer vision, large - scale models have shown remarkable
performance in various tasks. However, their high computational demands and memory requirements pose
significant challenges. This research explores techniques such as model compression, acceleration strategies, and
efficient data handling to optimize these algorithms. Through the analysis, it demonstrates the effectiveness of
these optimization methods in improving the efficiency and performance of large - scale computer vision models,
making them more applicable in real - world scenarios.
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Open AccessArticles
by Ran Wang
2025,12(1);
17 Views
Abstract
With the rapid development of robotics technology, real-time object detection has become increasingly
crucial in robotic application scenarios. YOLO (You Only Look Once), as an efficient object detection algorithm,
has been widely applied in the field of robotics. However, in practical applications, it still faces issues such as the
balance between speed and accuracy, and poor performance in detecting small objects. This paper delves deeply
into the optimization strategies for YOLO real-time object detection in robotic applications. By improving the
network structure, optimizing the training algorithm, and adopting multi-modal data fusion and other methods,
it aims to enhance the performance of the YOLO algorithm in robotic applications, providing strong support for
robots to achieve accurate perception and decision-making in complex environments.
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Open AccessArticles
by Zijie Zhou
2025,12(1);
16 Views
Abstract
This paper aims to study the application of feature selection technology in software defect prediction,
explore the influence of different feature selection methods on the performance of prediction model, and then
improve the accuracy and efficiency of software defect prediction. Three common feature selection methods
were used: information gain, chi-square test and recursive feature elimination (RFE), and experimental validation
was conducted using support Vector Machine (SVM), decision tree, random forest and logistic regression. The
experimental results show that the combination of random forest with recursive feature elimination (RFE)
method shows optimal performance on multiple indicators, with accuracy of 0.89, precision of 0.84, recall of
0.91, F1 value of 0.87 and AUC value of 0.93, which are better than the other combinations. The junction feature
selection can significantly improve the accuracy and efficiency of the model in the software defect prediction.
Through the appropriate feature selection methods, it can effectively reduce the redundant features, reduce the
model complexity, and improve the prediction accuracy.
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Open AccessArticles
by Dajun Tao
2025,12(1);
18 Views
Abstract
Objective: This paper investigates the methods for robotic dynamic modeling and evaluates the
performance of motion control strategies, focusing on accuracy, stability, and real-time capabilities in complex
trajectory tracking. The aim is to provide theoretical support for optimizing motion control strategies. Methods:
A six-degree-of-freedom robotic manipulator dynamic model is established based on the Lagrangian method.
Three control strategies—PID control, sliding mode control (SMC), and model predictive control (MPC)—
are implemented for simulation experiments. Their performance is compared in terms of trajectory error,
torque fluctuation, and computational cost. Results: The experiments demonstrate that MPC achieves the
highest trajectory accuracy (RMS error: 0.009 m) and the lowest torque fluctuation (0.14 Nm), but has a longer
computation time (4.3 ms/step). Sliding mode control exhibits strong robustness with moderate computational
efficiency, while PID control provides the best real-time performance but with relatively larger errors (0.018
m). Conclusion: MPC is suitable for high-precision and complex tasks, sliding mode control is appropriate for
scenarios requiring strong robustness, and PID control is more suitable for industrial environments with high realtime demands. This study provides a reference for the application of dynamic modeling and control strategies.
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Open AccessArticles
by Feifei Zhang, Linying Cai
2025,12(1);
19 Views
Abstract
With the rapid advancement of drone and low altitude aircraft technology, it is particularly important
to establish a comprehensive low altitude flight safety guarantee system. The article focuses on the key
requirements of chip design in this context, aiming to improve the safety, reliability, and efficiency of flight.
Firstly, the current technological challenges were analyzed, including high-precision positioning and navigation,
real-time data processing capabilities, low energy consumption, and security guarantees. To address these issues,
requirements are proposed in terms of hardware to improve integration, optimize signal processing units, and
power management strategies; At the software level, the importance of developing lightweight operating systems
and optimizing algorithms is emphasized. By comprehensively considering these factors, specific suggestions are
provided for the design of low altitude aircraft chips, aiming to promote the industry’s development towards a
safer and more efficient direction.
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Open AccessArticles
by Zeyu Cui
2025,12(1);
22 Views
Abstract
In the power system, the local discharge of electrical signal of power transformer are rich and complex,
easy to noise interference, and the traditional analysis method has obvious limitations. To this end, the author
innovatively puts forward the time frequency analysis and machine learning technology fusion of local discharge
electrical signal diagnosis method, through the short Fourier transform and wavelet transform capture high
frequency signal component, reuse support vector machine machine learning methods, greatly improve detection
accuracy and reliability, provide scientific basis for power equipment on-line monitoring and fault early warning.
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Open AccessArticles
by Ming Tang
2025,12(1);
18 Views
Abstract
With the explosion and increasing complexity of network traffic, management faces various technical
challenges. Artificial intelligence (AI) technologies, including machine learning, deep learning, reinforcement
learning and big data analysis, are used for traffic feature analysis, prediction, dynamic scheduling and
optimization strategy formulation. The proposed optimization scheme is based on these techniques, including
architecture construction and data processing.
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Open AccessArticles
by Yanan Song, Xirui Jin
2025,12(1);
17 Views
Abstract
The popularization of the Internet has promoted globalization, but it has also increased the risk of
cybercrime. Cybercrime is difficult to combat due to its cross - border nature, and many institutions choose
not to disclose attack incidents to avoid damage to their reputations. To address this challenge, countries have
formulated cybersecurity policies, while the International Telecommunication Union (ITU) plays a leading role
in setting standards, promoting cooperation, and assessing global cybersecurity. After researching this issue, our
team believes that the core of the problem should focus on three aspects: the distribution and pattern recognition
of global cybercrime, the evaluation of policy effectiveness, and the correlation analysis of demographic data.
Therefore, this paper analyzes the core issues based on VCDB data and provides effective suggestions for the
development and improvement of national cybersecurity policies and laws.
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Open AccessArticles
by Jie Fang, Xiaoshu Wang, Ping Wu
2025,12(1);
18 Views
Abstract
This paper explores the importance of the “Signals and Systems” course in practical applications and
its integration with artificial intelligence (AI) technologies from an AI perspective. By analyzing the fundamental
concepts and theories of signals and systems, along with examples of AI applications in signal processing, it
demonstrates how AI enhances the performance of signal processing systems and discusses future development
directions. Research shows that AI technologies bring new opportunities and challenges to the field of signals and
systems, driving innovation and progress in this domain.
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Open AccessArticles
by Taijung Huang
2025,12(1);
17 Views
Abstract
: In many conditions, it is necessary for a node in a WSN to be aware of its location in the physical
world. If tracking or event-detection functions are not useful if the WSN cannot provide any information
where the event has happened. Some location procedures have been proposed in the IEEE 802.15.4a standard,
including the TOA estimation, the location estimation, and network location algorithms. In this paper, we discuss
an effective TOA estimation scheme with the DLC receiver [7], which employs impulse radio UWB signals
compliant with the IEEE 802.15.4a standard. By modifying the synchronization algorithm with the DLC receiver,
the TOA can be obtained straightly.
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Open AccessArticles
by Shanshan Wu, Yuda Wang
2025,12(1);
20 Views
Abstract
This paper systematically composes the domestic and international research literature on digital
currencies, summarizes the origin and related concepts of digital currencies, and elaborates on the classification
of digital currencies. Based on the development status of digital currency in recent years, we have deeply studied
the technical principles, key technologies and operating modes of digital currencies, analyzed the risk challenges
in terms of cyber security, cryptographic security, data security and personal information protection. Finally,
this paper provides an expectation on the future development of digital currencies and proposes suggestions for
further research in cross-border payment and cyber security.
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Open AccessArticles
by Yangchun Shi
2025,12(1);
19 Views
Abstract
With the booming development of the cruise industry, passengers’ requirements for the cruise
ship interior installed multimedia entertainment system are increasingly diversified and personalized. This
study focuses on how to realize the collaborative integration and innovative optimization of the multimedia
entertainment system installed in cruise ships with the help of big data and artificial intelligence interaction
technology. Through in-depth study of relevant cutting-edge technologies and analysis of practical cases, a
complete system architecture and optimization strategy are designed to improve the entertainment experience of
passengers, enhance the efficiency of cruise operation, and promote the upgrading of the cruise industry towards
the direction of intelligence.
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Open AccessArticles
by Taijung Huang
2025,12(1);
17 Views
Abstract
This paper proposes a novel non-data aided timing synchronization algorithm designated as ”timing
with delay line combination” (TDLC), to improve the synchronization speed of differential impulse radio ultrawideband systems. Continuously integrating the combinative output signal provided by the proposed ”framedifferential delay line” (FDL), it is found that the integration output exhibits a sharp rising or falling transition at
the moment that the first signal per symbol arrives. By accurately detecting the time of the rising or falling edge,
the symbol boundary can be simply derived. The proposed scheme achieves timing synchronization within a
single symbol duration.
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Open AccessArticles
by Daihao Zhou, Jianxin Chen, Ruihan Zhang
2025,12(1);
12 Views
Abstract
The marine environment is complex and dynamic, and maritime operations and related offshore
projects face numerous safety risks. During offshore operations or the boarding and disembarking process, manoverboard incidents frequently occur. Rapid and timely emergency response and rescue measures are crucial to
ensuring the safety of maritime operations. The maritime personal search and rescue system based on the Beidou
Satellite Navigation System provides precise positioning and alarm services, enabling efficient distress alerts,
self-rescue, and mutual rescue capabilities. Moreover, this system can serve as a vital complement to the global
maritime distress and safety system, offering technological support to enhance maritime safety
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Open AccessArticles
by Zhengquan Liu
2025,12(1);
19 Views
Abstract
To promote the high synchronization and deep integration of new urbanization and rural revitalization,
it is inseparable from the integration of urban and rural development empowered by new quality productivity.
Urban-rural relations are the most basic form of relations in the process of social development. Urban-rural
integration should include the integration of space, industry and social services. The integrated development of
urban and rural areas is a new historical stage that must be experienced in the development and evolution of
China’s urban-rural relations, a practical path for the Party to lead the people to get rid of poverty and promote
the realization of common prosperity in the initial stage of socialism, and an important theoretical achievement
of the sinicization of the Marxist theory of urban-rural relations. Promoting the integrated development of urban
and rural areas and making systematic institutional arrangements has become a requirement of the times.
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Open AccessArticles
by Baodong Ma
2025,12(1);
18 Views
Abstract
X-ray technology plays a crucial role across healthcare, industrial, and security sectors, but managing
equipment globally presents challenges due to technological disparities, regulatory differences, and supply chain
issues. This paper examines innovative maintenance strategies, focusing on preventive maintenance, predictive
analytics, and IoT integration. Case studies demonstrate how these approaches improve equipment lifespan,
reduce downtime, and enhance performance. The study also emphasizes the need for balancing standardized
maintenance protocols with localized adaptations to ensure global efficiency. Advancements in AI and remote
monitoring are transforming maintenance practices, offering cost savings and improved reliability
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Open AccessArticles
by Rong Pei
2025,12(1);
27 Views
Abstract
According to Miller and Kelekian (2015), meal kits are considered a transformative technology as
they disrupt the traditional grocery supply chain, fundamentally changing how food is sourced, distributed, and
consumed. This article analyzes HelloFresh, a leading representative of the meal kit industry, to demonstrate its
efficiency and effectiveness. Through a data-driven approach, HelloFresh ensures operational efficiency while
delivering high-quality, fresh meal kits to its customers.
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Open AccessArticles
by Jing Huang
2025,12(1);
20 Views
Abstract
Augmented reality (AR) technology, with its unique composite of real and imaginary, threedimensional visualization, and deep immersion, has injected new vitality and change into traditional classroom
teaching models and learning styles. This study examines the literature to determine the applications of AR
in education, which include empowering subject teaching, integrating educational games, and inventing topic
teaching materials. Several studies have shown that AR has a positive effect on student learning. However, the
majority of current research focuses on the objective effect evaluation of AR applications and does not examine
students’ visual patterns and behavior paths in AR learning environments from a subjective perspective. Given
the relevance of this perspective, the study recommends a research route for students’ visual behavior in an AR
education environment based on existing research.
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Open AccessArticles
by Taijung Huang
2025,12(1);
22 Views
Abstract
Synchronization poses a major of challenge in UWB systems because low duty cycles in UWB. This
research develops an better synchronization scheme for FD-IR- UWB receivers to improve the synchronization
speed.The mechanism reduces the search durarion of the symbol boundaries to only a single frame duration.
Moreover,delay element is needed in each branch, since a SLD is also proposed to lower complexity of the
parallel search mechanism. performance analysis and simutaitons show that the proposed scheme achieves a
lower MSE and a higher PD than other alternatives.
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Open AccessArticles
by TaiJung Huang
2025,12(1);
21 Views
Abstract
Because of the norrow signal duty cycles, SYNC is the most critical issue in UWB-IR systems. Some
synchronization schemes like a SD-IR-UWB receiver have been proposed to synchronize received signals
rapidly. Yet, SD IR-UWB receiver is not suitable for operation in multi-user stiution because of MAI. By taking
advantage of FD-IR-UWB receivers, we propose a PFD-IR-UWB receiver to do so. Our proposed PFD IRUWB receiver manifests better immunity against message passing interface and MAI than the SD IR-UWB.
Based on this PFD IR-UWB receiver, search regions are limited to one frame duration without any symbol-level
synchronization sheme. Performance of PFD and SD receivers are compared by simulations, showing that the
proposed PFD receiver not only achieves significantbit error rate performance but also better and more robust
results than the SD receiver in this paper
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Open AccessArticles
by Qin Yaping, Liu Hongjian
2025,12(1);
18 Views
Abstract
Image segmentation is a fundamental and challenging task in the field of image processing. This
article proposes a two-stage strategy image segmentation algorithm based on deep plug and play. By conducting
numerical experiments on pyCharm and MATLAB, we have verified the robustness and superiority of our
proposed algorithm.
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Open AccessArticles
by Ke Hu
2025,12(1);
23 Views
Abstract
The purpose of this paper is to explore the potential of artificial intelligence and electroencephalogram
(EEG) analysis in optimizing anesthesia depth monitoring. research methods include data collection and quality
improvement, multimodal data fusion, algorithm generalization and robustness enhancement, and model
interpretability improvement. The results show that the combination of AI and EEG significantly improves
precision monitoring of anesthesia depth and personalized anesthesia management, reduces postoperative
complications, and improves patient safety. The study shows that AI and EEG analysis have great potential
for use in deep anesthesia monitoring, but further research and validation are needed in key areas such as data
quality, algorithm generalization, and ethical safety. In the future, increasing the interpretability of models
through multimodal data fusion is expected to further advance the widespread use of AI in anesthesia medicine to
improve clinical outcomes and patient safety.
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Open AccessArticles
by Xiuan Fu
2025,12(1);
20 Views
Abstract
Environmental sustainability has become a global concern, and the integrated application of intelligent
optical cable laying and low voltage electrical engineering technology, as a key link in the construction of
modern information and communication infrastructure, is of great significance in promoting the process of social
informatization and facilitating green and low-carbon development. This paper deeply explores the connotation
and current situation of intelligent optical cable laying technology and low voltage electrical engineering
technology, analyzes the main problems and challenges faced by the integrated application of the two, proposes
targeted countermeasures, and demonstrates the effectiveness of the integrated application through practical
cases. Research shows that the integrated application of intelligent optical cable laying and low voltage electrical
engineering technology not only improves construction efficiency and quality, reduces energy consumption and
emissions, but also promotes the green development of the information and communication industry, providing
strong support for achieving environmental sustainability goals.
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Open AccessArticles
by Enhui Yu
2025,12(1);
15 Views
Abstract
The purpose of this paper is to design and implement a simple advertisement image recommendation
system based on user profiles. The system constructs a user profile by analyzing the user’s historical behavior,
interests and preferences, and makes use of advanced machine learning models for personalized recommendation
of advertising images. This paper firstly introduces the theoretical and technical background of the
recommendation system, and then elaborates the requirements, outline design and detailed design of the system.
In order to improve the recommendation effect, this paper also explores the click rate prediction method based
on Z-NFFM (a kind of improved neural network factorization machine) model and the advertisement cold start
strategy based on LightGBM-LR (Light Gradient Boosting Machine combined with logistic regression) model.
The experimental results show that the system can effectively improve the click-through rate of advertisements,
optimize the user experience, and bring higher conversion efficiency for advertisers.
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Open AccessArticles
by Yin Zheng
2025,12(1);
19 Views
Abstract
In this paper, the application of artificial intelligence technology in software defect prediction and
repair is studied with respect to the shortcomings of traditional software defect prediction models in terms of
interpretability and robustness. Focusing on the modeling method of Bayesian network in the field of software
defect prediction, a software defect prediction model based on Bayesian network is established through data
discretization, Bayesian network structure learning algorithm, and probabilistic inference technology. Further,
this paper integrates Bayesian network with common predictors such as K-nearest neighbor, decision tree,
logistic regression and so on in a soft-voting manner to construct an integrated software defect prediction model.
Experimental simulations are carried out on six publicly available software defect datasets, and the results show
that the integrated model based on Bayesian network significantly outperforms the traditional integrated model in
terms of evaluation indexes such as F1, Recall, and G-Mean.
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Open AccessArticles
by Yan Li, Hongxiu Duan, Genjuan Ma, Wenting Ding, Yongyi Lin
2025,12(1);
23 Views
Abstract
Internet Application Development Technology" is an important professional course of computer
science in colleges and universities. This paper aims to discuss the teaching reform of "Internet application
development technology" under the applied talent training mode. The paper first analyzes the current
existing problems in the independent undergraduate course teaching, and then puts forward a series of targeted
teaching reform measures. These measures include the optimization of course content, the innovation of teaching
methods, the strengthening of practical teaching and the improvement of assessment and evaluation. Finally, this
paper also verifies the effectiveness of these reform measures through empirical research, in order to provide
useful reference for the teaching reform of relevant courses. In order to improve students' professional
knowledge and practical ability, to meet the needs of talents, students with the ability of applied talents.
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Open AccessArticles
by Yan Li, Yanbin Bu, Long Zhang, Yuhao Gou, Xinyue Cheng, Renqin He, Huiting Zhang
2025,12(1);
27 Views
Abstract
This paper analyzes an AIoT-based indoor fire inspection and early warning system that utilizes a
layered architecture to achieve multi-source data collection and fusion. The system integrates IoT technology, big
data analysis, and artificial intelligence algorithms to build an intelligent fire warning model. Through three major
functional modules - real-time monitoring, intelligent analysis, and remote management - the system achieves
precise identification and early warning of fire risks, providing reliable theoretical support for indoor fire safety.
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Open AccessArticles
by Qingye Wei
2025,12(1);
19 Views
Abstract
The field of integrated circuit (IC) design has witnessed remarkable advancements driven by the
need for higher performance, reduced chip size, and enhanced energy efficiency. This review explores state-ofthe-art methodologies in IC design, with a focus on layout optimization and the application of metaheuristic
algorithms such as simulated annealing and genetic algorithms. It also examines novel representation techniques
like sequence pair, B*-tree, and corneal block sequences that address layout complexity. Furthermore, the study
proposes integrating machine learning, reinforcement learning, and predictive models to enhance the adaptability
and efficiency of design processes. By offering a comprehensive overview and presenting forward-looking
perspectives, this review aims to contribute to the development of next-generation ICs, addressing scalability
challenges and ensuring improved performance for advanced electronic systems.
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Open AccessArticles
by Taijung Huang
2025,12(1);
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Abstract
Synchronization poses a major challenge to UWB systems due to the low acquisition time in UWB.
This study develops an Shared Loopded Delay -Line for FD-IR-UWB receivers to improve the synchronization
performance. The proposed parallel search architecture reduces the search time of the symbol boundaries.
Moreover, one branch needs a time delay element, since SDL was proposed to lower the implementation
complexity of the parallel search architecture. Finally, simulations and theoretical analysis show that the proposed
architecture obtains a lower MSE and a higher PD than other alternatives.
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