ISSN
2424-8460(Online)
2251-2608(Print)
Published
Table of Contents
Open AccessArticles
by Xiqiao Zhang
2025,12(4);
1 Views
Abstract
Nowadays, with the rapid development of science and technology, the integration of artificial intelligence (AI) technology and the manufacturing industry is deepening, and intelligent manufacturing has become an important direction of industrial transformation. Starting from the basic concept of intelligent manufacturing, this paper explores the speciffc applications of AI in intelligent design, intelligent production, quality inspection, supply chain management, and equipment maintenance, analyzes the advantages brought by these applications, and ffnally brieffy mentions the challenges faced. The aim is to demonstrate the changes AI has brought to the manufacturing industry and inspire thinking on the integration of technology and industry.
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Open AccessArticles
by Jingyi Shao
2025,12(4);
6 Views
Abstract
This paper gives an in-depth exploration of the transformative ability of Artificial Intelligence across graphic design and e-commerce logistics. It examines how Canva and Adobe apply AI to change visual communication and how Amazon deploys AI for record-breaking operational efficiency andpredictive accuracy. For graphic design, neural networks and computer vision in applications like Canva's Color Palette Generator popularizes graphic design for a mass user base by decomposing advanced color theory. Adobe with its proprietary Adobe Sensei platform integrates AI across Creative Cloud to augment professional capabilities while driving innovation and brand consistency.
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Open AccessArticles
by Wenjing Yan, Jun Yang
2025,12(4);
2 Views
Abstract
As the digital media industry shifts towards original and creative-oriented development, traditional teaching models exhibit significant deficiencies in fostering innovation capability and practical application. Taking the Brand Packaging Design course as a case study, this paper explores the application and empowering value of AIGC in the teaching of digital media programs.By integrating AIGC technology,a cyclical teaching model of "generation-evaluation-regeneration" is constructed, achieving efffcient synergy in creative ideation, solution iteration, visual presentation, and interdisciplinary integration. Practical results demonstrate that AIGC not only signiffcantly enhances students' creative efffciency and iteration speed but also boosts learning interest, engagement, and teamwork capabilities, while optimizing course structure and teaching processes. Furthermore, through virtual exhibition environments and immersive scenario designs, students can systematically train their design thinking in contexts closely resembling real-world enterprise projects, thereby enhancing their professional adaptability. This paper summarizes the experiences from this teaching reform and proposes improvement strategies for further expanding interdisciplinary integration and deepening university-industry collaboration, offering a replicable practical pathway for innovating teaching models in digital media education. The study highlights the signiffcant role of AIGC in advancing professional education reform and cultivating high-quality, interdisciplinary design talent.
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Open AccessArticles
by Yifan Gou
2025,12(4);
1 Views
Abstract
This study addresses the "last mile" delivery challenge in campus environments by exploring the application and route planning of unmanned delivery vehicles. By analyzing the dense pedestrian flow and complex architectural features of campus environments, we developed a dynamic scheduling model integrating timetable data with a multi-sensor fusion positioning solution, while optimizing the Dijkstra algorithm for path planning. The research introduced solar-powered systems and redundant control mechanisms to enhance reliability, along with an optimized user interface based on ffeld surveys. Experimental results demonstrate that the improved algorithm reduces path length by 12.7%, increases efffciency by 27% during peak hours, and cuts operation time by 51%. In the future, we will explore air-land collaborative distribution and ethical norms to help build a smart logistics system on campus.
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Open AccessArticles
by Jinfu Liao
2025,12(4);
2 Views
Abstract
The United States has consistently been a world leader in the development and governance of artiffcial intelligence (AI). This study focuses on U.S. AI policy, employing the theory of digital hermeneutics as the research method. By combining quantitative and qualitative analyses, it examines Executive Order 14110 from the perspective of attitude analysis and co-existence analysis. The results indicate that the United States maintains a proactive attitude toward AI technology while also paying attention to the regulation of "high-risk"AI.
Overall, the approach is characterized by "promoting development, valuing talent, and mitigating risks,"and this trend is expected to continue.
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Open AccessArticles
by Xiangyu Chen, Qinglin Wang, Zhen Wang
2025,12(4);
1 Views
Abstract
This paper provides an overview of multimodal representation learning, using modal combination types as the core classiffcation framework. It systematically reviews representation learning methods, association mechanisms, and fusion strategies under different modal pairs. Unlike previous reviews based on model architectures or task categories, this paper adopts a bottom-up perspective on modal interactions, revealing how the collaborative characteristics of different modal pairs inffuence representation modelling and summarizing the technical evolution of cross-modal learning. Additionally, this paper summarizes the general paradigms and practical challenges in multi- modal architecture design, offering new perspectives for model optimization in complex scenarios.
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Open AccessArticles
by Yifan Luo
2025,12(4);
2 Views
Abstract
This paper focuses on English digital advertising targeting Generation Z consumers, employing multimodal discourse analysis theory to delve into the collaborative role of visual and linguistic elements, as well as the mechanisms of discourse construction.Through the study of numerous advertising samples, it reveals the unique advantages of visual elements in capturing attention and conveying emotions, along with the pivotal role of linguistic elements in precisely conveying information and guiding consumer behavior.The research ffnds that successful English digital advertisements often skillfully integrate visual and linguistic elements, forming a powerful and persuasive multimodal discourse system to meet Generation Z consumers' pursuit of individuality and emphasis on experience.
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Open AccessArticles
by Yuxin Wei
2025,12(4);
2 Views
Abstract
Against the backdrop of deep integration between globalization and digital technology, English online forums have emerged as crucial platforms for international youth to engage with Chinese philosophical concepts. This paper takes the cross-cultural dissemination of Confucian "Ren" (benevolence) and Daoist "Dao" (the Way) as case studies, employing textual analysis, user behavior tracking, and a theoretical framework of cross-cultural communication to reveal how forums facilitate the transformation of Chinese philosophy from "cultural symbols" to "practices in daily life." The study finds that the interactive, decentralized nature, and multimedia integration capabilities of forums signiffcantly enhance international youth's cognitive depth and emotional identiffcation with Chinese philosophy, albeit facing challenges such as cultural misinterpretation and struggles for discourse power.
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Open AccessArticles
by Fan Wu
2025,12(4);
2 Views
Abstract
This paper focuses on the performance differences between machine translation and human translation in the English versions of Chinese official documents.By collecting a large number of Chinese offfcial documents along with their corresponding machine-translated and human-translated English versions, a thorough comparative analysis is conducted from multiple dimensions, including lexical accuracy, grammatical correctness, semantic coherence, and stylistic appropriateness.The study ffnds that while machine translation exhibits high efficiency and acceptable accuracy in handling conventional vocabulary and simple sentence structures, it significantly falls short in accurately translating specialized terminology, processing complex sentence structures, and conveying cultural connotations.In contrast, human translators leverage their profound language skills, cultural background knowledge, and flexible translation strategies to more precisely convey the original information, ensuring the quality and style of the translation align closely with the requirements of offfcial documents.This research aims to provide valuable Referencess for translation practices and related studies, fostering the improvement of machine translation technologies and the collaborative development of human and machine translation.
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Open AccessArticles
by Yurui Zhong
2025,12(4);
1 Views
Abstract
This paper shifts the research focus from marketing demand to language learning demand, exploring the signiffcant value of English slang in social media advertising for improving learners' pragmatic competence, cross-cultural language application ability, and ability to analyze language in real contexts. Through a comprehensive analysis of various social media advertising campaigns, linguistic theoretical frameworks, and language learning-related studies, it reveals how the strategic use of English slang in advertising can serve as a valuable teaching resource to enhance learners' language skills. The ffndings suggest that in-depth analysis of slang-infused ads can help learners understand the pragmatic functions of slang, grasp cross-cultural language usage rules, and improve their ability to interpret language in real communication scenarios. These are crucial factors for promoting effective language learning and avoiding cross-cultural pragmatic failures.
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Open AccessArticles
by Fengzhi Yan
2025,12(4);
3 Views
Abstract
This paper delves into the realm of English digital storytelling and its profound impact on interactive
visual communication design innovation. With the rapid advancement of digital technology, English digital
storytelling has emerged as a powerful medium that transcends traditional linguistic and cultural barriers. By
integrating immersive visual elements, interactive features, and narrative techniques, it offers a novel approach
to engaging audiences and conveying messages. This study explores the key components, strategies, and
potential applications of English digital storytelling in driving design innovation within the field of interactive
visual communication. Through a comprehensive analysis of existing works and case studies, we aim to provide
valuable insights for designers, educators, and researchers seeking to harness the full potential of this dynamic
medium.
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Open AccessArticles
by Yuk Cho Randy， Wang
2025,12(4);
2 Views
Abstract
This article analyzes the social harm of data breaches from three dimensions: firstly, the technological
models and social impacts of information breaches; Secondly, there are differences in the risks faced by different
social groups, especially vulnerable targets such as children and the elderly; Thirdly, there are regulatory
deficiencies at the institutional level and a lack of corporate responsibility.
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Open AccessArticles
by Muzi Ouyang, Jinhong Yu
2025,12(4);
3 Views
Abstract
Aviation technical English translation plays a crucial role in advancing China's aerospace technology
and facilitating international exchanges in this field. This study utilizes Deepseek's machine translation system
and selects representative aviation technical texts as the research corpus. Through a comparative analysis of
Deepseek's translations and human translations, this study identifies several challenges in the Chinese-to-English
translation process and proposes corresponding pre- and post-editing strategies.
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Open AccessArticles
by Jingyi Chen, Xiaorui Tang, Fei Yuan, Ping Pan, Congcong Zhang
2025,12(4);
1 Views
Abstract
This study focuses on how to optimize the co parenting support strategies of rural grandparents
through AI voice assistants, in order to address the challenges of low information literacy and lagging
educational concepts in intergenerational education of left behind children in rural areas. The study identified
the core needs of rural grandparents and designed the core functions of AI voice assistants accordingly. The
results showed that AI voice assistants significantly improved the parenting efficacy and parent-child interaction
frequency of grandparents, effectively compensating for their shortcomings in scientific knowledge answering.
The study proposes innovative strategies such as dynamic feedback adjustment and optimization of teacher
monitoring, and provides practical suggestions for policy formulation and the training of normal university
students, aiming to promote educational equity and sustainable development.
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Open AccessArticles
by Wanting Xu, Amirrudin Kamsin
2025,12(4);
5 Views
Abstract
Voltage sags are critical power quality disturbances in modern smart grids, worsened by renewable
energy integration and distributed generation. Traditional physics-based methods fail to handle high-dimensional
data and non-linear dynamics, prompting the adoption of machine learning (ML) for prediction and multi-agent
reinforcement learning (MARL) for cooperative control. This review synthesizes key advances in ML (traditional
techniques and deep learning) for sag detection/classification, and MARL (via the CTDE paradigm) for
distributed voltage regulation. Critical gaps—Rigid architectures, deployment barriers, lack of benchmarks—are
identified, with pathways to unify prediction and control. It provides a foundation for advancing intelligent sag
management in smart grids.
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Open AccessArticles
by Siyu Gao
2025,12(4);
2 Views
Abstract
This paper aims to explore the influence of blended learning on college students' advanced English
writing proficiency. Through a comprehensive analysis of relevant theories and empirical research, it delves into
how blended learning, combining online and face-to-face instruction, affects students' writing skills, including
language accuracy, coherence, and creativity. The study reveals that blended learning can significantly enhance
students' advanced English writing ability by providing a more flexible and personalized learning environment,
promoting active engagement, and facilitating peer feedback. However, challenges such as technological barriers
and students' self-regulation issues also need to be addressed. Based on the findings, practical suggestions are
proposed to optimize the implementation of blended learning in advanced English writing courses.
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Open AccessArticles
by Hong Zhang
2025,12(4);
1 Views
Abstract
This paper examines the historical evolution of the epistemic subject against the rise of generative
artificial intelligence. By analyzing key phases of knowledge production, storage, and dissemination, it argues
that the epistemic subject is undergoing a trend of de-anthropocentrism. In response to these shifts, humanity
should leverage its unique agency, ground itself in embodied reality, and formulate reasonable expectations to
balance the human-machine dynamic, thereby seeking a foundation for human subjectivity that transcends pure
intelligence.
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Open AccessArticles
by Fan Cui, Dan Wang, Zundong Mao
2025,12(4);
2 Views
Abstract
Chinese spelling correction (CSC) is an important task in natural language processing (NLP), with
applications in text generation, intelligent input methods, and other scenarios. Although many advanced
models have improved general-purpose correction performance, two major challenges remain. First, under the
dominance of pinyin-based input methods, phonetic similarity errors have become prevalent, yet existing models
still struggle to correct them effectively. Second, the presence of low-frequency domain-specific terms (e.g., in
medicine or law) makes it difficult for general models to adapt to out-of-domain texts. To address these issues,
we propose Pinpin-BERT, a CSC approach that enhances BERT with continuous pinyin features. Leveraging
the property that consecutive Chinese characters often have stable pinyin patterns, the model employs a
convolutional neural network to extract continuous pinyin features and integrates them with BERT’s semantic
representations for more accurate correction. In addition, a user-defined lexicon is incorporated to improve
domain adaptability. Experimental results on three official benchmark datasets and a self-constructed medical
dataset demonstrate that the proposed method achieves consistently strong performance across all evaluations.
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Open AccessArticles
by Leyi Ye
2025,12(4);
2 Views
Abstract
This study proposes a new method for simulating stellar evolution based on a dynamical convection
model (DCM) and adaptive mesh refinement (AMR). This method overcomes the limitations of conventional
algorithms through three key innovations: First, a nuclear burning-driven term is innovatively introduced
into the dynamic convection model, directly coupling the nuclear reaction energy with the turbulent kinetic
energy, addressing the traditional model's neglect of combustion-convection interactions. Second, a rotational
modulation term and a chemical composition term are used to achieve a self-consistent description of rotation,
chemical gradients, and turbulence for the first time. Third, an intelligent adaptive mesh refinement criterion
is developed, which, through the synergistic effect of the gradient compression factor and the nuclear burning
priority term, improves the resolution of key regions such as the burning shell. Numerical experiments
demonstrate that the new method significantly improves simulation accuracy: RMSE errors were reduced in
eight of ten comparisons. Furthermore, mixing efficiency was significantly improved, increasing by 12.5%, 40%,
and 20% for low-mass, medium-mass, and high-mass stars respectively. This method provides a new tool for
accurately simulating the evolution of stellar interior structures and predicting element abundance distributions.
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Open AccessArticles
by Weile Huang
2025,12(4);
2 Views
Abstract
This paper provides a faster algorithm for multivariate square-free decomposition, using random
primes as coefficients of univariate substituting variables instead of p-adic construction, and returning to the
multivariate expression using the unique prime factorization property of integers.
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Open AccessArticles
by Mingjun Ouyang
2025,12(4);
5 Views
Abstract
The Chinese Remainder Theorem (CRT) for polynomials is an extension of the well-known theorem in number theory, which deals with the existence and uniqueness of solutions to a system of congruences. One formulation of CRT involves recovering an unknown polynomial f given its reductions modulo a se- quence of polynomials g i , i = 1, 2, ...,s. In the classical setting, the polynomials g i are required to be coprime, and the sum of their degrees ∑=1 degg i must exceed degf. In this paper, we present a sparse algorithm tailored for the case where the number of terms in f is no more than T, and the polynomials g i have the form gi = x pi − 1. Our algorithm demonstrates that under these conditions, the sum of the degrees of gi needs only satisfy ∑ s i=1 degg i ≥ O~ (T 2 log 2 D) to uniquely determine f, where degf is at most D. This smaller degree sum con- dition provides an advantage over traditional Polynomial Chinese Remainder Theorem approaches when T 2 log 2 D < D, particularly when f is sparse. Our sparse algorithm thus offers an efficient way to recover sparse polynomials.
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Open AccessArticles
by Jiayu Jian, Shuhan Guo
2025,12(4);
2 Views
Abstract
With the deepening of the digital transformation of archives in colleges and universities, freshmen's
mental health service faces the opportunity of technical empowerment and model innovation. The traditional
mental health education model can't meet the psychological needs of freshmen in the transitional period because
of scattered information and delayed early warning. The multi-dimensional student data accumulated in the
digital transformation of archives provides a new basis for accurately identifying psychological risks. Based on
the perspective of archives management, this paper expounds the connotation and characteristics of the digital
transformation of archives in colleges and universities and the big data platform for freshmen's mental health,
deeply analyzes the significance of building a big data platform for freshmen's mental health, and finally puts
forward the specific implementation path from the dimensions of consolidating the data foundation, building
a technical framework, building a closed loop of "monitoring-early warning-intervention" and improving the
guarantee mechanism. The purpose of this study is to provide theoretical References and practical guidance for
colleges and universities to optimize freshmen's mental health service by using digital archives resources, and to
promote the transformation of mental health education to digitalization and intelligence.
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Open AccessArticles
by Meng Zhang, Qingwei Zhou, Shun Chen
2025,12(4);
2 Views
Abstract
Large-scale 3D reconstruction holds crucial application value in fields such as digital twins, smart
cities, and cultural heritage protection. However, it faces technical bottlenecks including massive data volume,
low detail restoration accuracy, and poor adaptability to dynamic scenes. Gaussian Splatting technology,
leveraging the advantages of flexible point cloud representation, high rendering efficiency, and strong detail
preservation capability, provides a new approach to address the challenges of large-scale reconstruction. This
paper systematically sorts out the core principles and technical characteristics of Gaussian Splatting technology.
It constructs a complete technical route for large-scale 3D reconstruction from four dimensions: data acquisition
and preprocessing, Gaussian point cloud generation and optimization, dynamic scene adaptation, and accuracy
evaluation. Combined with practical application scenarios, the technical advantages and existing challenges
are analyzed, providing theoretical reference and practical guidance for the engineering application of this
technology in complex large-scale scenes.
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Open AccessArticles
by Yuanming Yao
2025,12(4);
1 Views
Abstract
This study systematically analyzes the development status of China's Electronic Health Record (EHR)
systems, revealing core issues such as data fragmentation, inconsistent standards, limited cross-institutional
collaboration, and insufficient intelligence. By applying large language models (LLMs) and integrating federated
learning with blockchain technology, a new paradigm for medical data sharing is constructed. This research aims
to provide theoretical support for EHR system optimization, promote efficient allocation of medical resources,
foster medical research innovation, and ultimately achieve the dual objectives of improving healthcare service
quality and optimizing medical costs.
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Open AccessArticles
by Tianhao Wu, Hongxiao Liu, Yayu Zhai, Xiaoquan Gao
2025,12(4);
1 Views
Abstract
To address the controllability and observability issues in distributed testing of intelligent autonomous
systems, this paper proposes an automatic test system framework based on multi-port finite state machine (npFSM) and greedy algorithm, introducing real-time middleware to support multi-task parallel testing. Firstly, a
two-level architecture of "management node - test node" is constructed, ensuring test real-time performance
and accuracy through dynamic scheduling and fault recovery mechanisms. Secondly, an np-FSM model is
established for the formal description of the system under test (SUT), and a greedy algorithm is proposed to
optimize the selection of key ports, reducing the number of control coordination messages and thus lowering
communication overhead. Finally, a distributed test platform is designed based on real-time middleware,
supporting loosely coupled combination and task collaboration of resource components, and four types of test
case timing constraint relationships are defined to realize scalable automated testing. Experimental results show
that the framework outperforms traditional methods in terms of test sequence length, communication overhead,
and real-time performance.
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Open AccessArticles
by Yongqiu Yang, Zongping Zhang, Dairong Zhu
2025,12(4);
2 Views
Abstract
Based on the foundation of smart customs construction during the 14th Five-Year Plan period,
this paper explores the path for high-quality development of customs informatization in response to new
requirements and challenges during the 15th Five-Year Plan period. The study points out that in the future,
we should adhere to the core concept of 'Smart Customs, Intelligent Borders, and Smart Connectivity',
and systematically promote customs informatization through four key tasks: building an intelligent digital
foundation through technological empowerment, achieving full-process intelligent transformation through
business restructuring, creating a port ecosystem community through collaborative sharing, and strengthening
national border defenses through security support. Combining local practical cases, the paper proposes phased
implementation paths and policy recommendations, aiming to provide reference for the compilation of the 15th
Five-Year Plan and future work, and to help build an internationally advanced smart customs system by 2030.
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Open AccessArticles
by Songsong Zuo
2025,12(4);
1 Views
Abstract
With the rapid development of digital communication technology, the integration of UAV flight
control and various positioning means is a hot research topic. Especially with the widespread use of digital
maps and other technologies, integrating GIS into UAV flight control is of great significance. This paper reviews
the research status of UAV flight control and GIS applications, discusses the significance of optimizing UAV
flight control through GIS fusion, and analyzes its application scenarios in many fields. Research shows that
integrating GIS significantly improves UAV flight control performance, meets the requirements of intelligent
inspection tasks, effectively controls costs, and enhances safety. Finally, the paper looks forward to the prospect
of optimizing UAV intelligent inspection based on GIS and believes it has broad application and development
space in the future.
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Open AccessArticles
by Yiqian Lin, Yuquan Wang, Yuewen Hua, Yongling Jiang, Qi Li, Haifeng Wang
2025,12(4);
1 Views
Abstract
With the rapid growth of the aging population, ensuring the health and safety of elderly people
living alone has become increasingly important. This paper presents the design and implementation of an
embedded health monitoring system based on the STM32F103C8T6 microcontroller. The system integrates a
DS18B20 temperature sensor, a MAX30102 heart rate and blood oxygen sensor, an MPU6050 inertial sensor,
a GPS positioning module, an OLED display, and an ESP32 wireless communication module, enabling realtime acquisition of physiological parameters, motion status, and location information. Alarm thresholds can be
configured locally or remotely via a mobile application. When abnormal physiological conditions or fall events
are detected, the system triggers alarm notifications and uploads data to a cloud platform for remote monitoring.
Experimental results show that the proposed system provides stable wireless communication, reliable data
acquisition, and effective abnormal event detection, demonstrating its feasibility and practicality for elderly
health monitoring applications.
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