MingZe Zou
Abstract: This paper addresses the design requirements for deformable packaging structures by proposing a thin-walled structure based on Origami principles. Using triangles as the fundamental unit, this structure achieves morphological transformation from two-dimensional to three-dimensional through the folding and unfolding of a planar grid, possessing the capability to flexibly wrap irregular objects. The research employs Rhino and Grasshopper for geometric modeling and parametric design, utilizes …
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Mark Yutong Zhao
Abstract: The separability problem, a long-standing open challenge in mathematics and quantum information theory. In this work, we propose and investigate a conjecture as a sub-question of the separability problem. Specifically, we investigate whether the form I8-xx* is separable for any eight-dimensional unit vector x . This is actually the so-called absolute separability problem. For studying the conjecture, we classify the vectors in a finitely-dimensional bipartite Hilbert space, and construct their …
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Zheng Xin, Kechen Li, Zhenghan Zhou, Xiesheng Jiang
Abstract: Large-scale sporting events such as the Super Bowl and the NBA All-Star Weekend generate substantial social and economic value, but they also impose significant environmental pressures through energy consumption, transportation emissions, and urban infrastructure demands. As sustainability becomes an increasingly important criterion in event planning, host-city evaluation requires data-driven, multi-factor analysis rather than reliance on economic indicators alone. This study develops a …
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Wenting Zhao, Liam Ziwei Wang, HaoYi Chen, Haoyi Luo
Abstract: This study develops a three-component sustainability assessment framework for sport mega-event host selection: Baseline Analysis, Contextual Impact Adjustment Model (CIAM), and Entropy-TOPSIS ranking. Using Super Bowl LIX as reference, thirteen environmental indicators quantify venue energy, transportation, waste, and climate re- silience. CIAM transforms raw metrics through: (I) grid carbon intensity adjustment; (II) localized infrastructure reuse benefits; (III) non-linear climate risk …
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Zinuo Yang, Hangzhi Zhang, Jiayang Wu, Rui tong Liu
Abstract: Sport mega-events generate substantial economic benefits but impose significant environ- mental pressures on host cities. This study develops a comprehensive State-Pressure-Impact- Response (SPIR) framework to quantitatively assess environmental sustainability across carbon, water, waste, and energy dimensions. The model integrates a city’s baseline environmental ca- pacity (State) with event-driven pressures (on-site and of-site) through a nonlinear logistic response function, yielding a …
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Yinxi Chen, Haoxuan Li, Ziquan Wang, Victor Quyi Chen
Abstract: In emergencies, every second matters. First responders must ensure that no occupant is left behind while operating under conditions of limited visibility, increasing danger, and incomplete information. Well-designed evacuation plans reduce the risk to responders and improve the effectiveness of their efforts. In particular, efficient sweeping routes and techniques can be the difference between a safe evacuation and a preventable tragedy. To support emergency planning, we develop a rigorous model …
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Yuanheng Qu, Fu Him Huang, Chuhan Zhong, Menglin Sun
Abstract: In emergency scenarios such as fires, earthquakes, or active shooter incidents, the rapid and safe searching of multi-story buildings is critical for saving lives. This paper presents a mathematical framework for optimizing emergency responder routes during building safety sweeps. The proposed system transforms floor plans into weighted graph representations, where nodes denote rooms, hallways, stairwells, and exits, and edges represent traversable paths with associated travel and service times. …
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Mocheng Wu, Jinzhen Qian, Haoran Ni, Yining Xu
Abstract: In recent years, environmental sustainability has become an increasingly important topic when talking about mega events as host cities face growing pressure to address excessive resource consumption, denser pollution, and greater ecological damage. In this paper, our objective was to construct a model to assess the full environmental footprint of large-scale sporting competitions in multiple dimensions. Firstly, we developed a series of specialized models to determine the magnitude of seven key …
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Shengtao Yang, Yicheng Sun, Yile Yang
Abstract: This paper proposes a decision-making model that integrates sampling estimation and combinatorial optimization to address quality control and cost optimization in multi-process production systems. First, a sampling estimation method is developed based on hypothesis testing to perform statistical inference on component defect rates, thereby reliably obtaining quality parameters. Building on this foundation, a multi-stage production decision-making model is established, which unifies the …
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Yuanman Li
Abstract: In the field of complex system modeling, tree-structured data widely exists in bioinformatics, social network analysis, spatial statistics, and machine learning. Such data faces several core challenges: high-dimensional discrete topological space leads to exponential combinatorial complexity, traditional point estimation methods cannot effectively quantify structural uncertainty, and unconstrained sampling algo- rithms generate massive invalid structures, resulting in low efficiency and unstable …
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Qianyi Zhang
Abstract: Simultaneous localization and mapping, (SLAM), is universally utilized in mobile robot systems to enable mobile robots to achieve accurate perception and decision-making. Aiming at reviewing the development and research progress of SLAM technology, this review introduces academic research findings on the front-end, back-end, and path planning strategies of SLAM systems focusing on fundamental principles of SLAM systems. Followed by discussion focusing on technology such as semantic maps, deep …
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Hongye Zhao
Abstract: Precious metals serve as critical investment assets and industrial commodities in global financial markets. Accurate price forecasting is challenged by their strong nonlinearity, long-range temporal dependencies, and complex inter-metal linkages. Traditional econometric models and existing deep learning approaches often overlook explicit cross-metal interactions, leading to suboptimal multi-metal prediction performance. This paper proposes an improved Transformer architecture for multi-precious …
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Flora Rughwani, Yize Li, Lingyan Chen, Hanya Zhang
Abstract: Emergency evacuation efficiency directly impacts survival rates during fire incidents. Statistics indicate that survival probability decreases by 7–10% per minute after eight min- utes without rescue. We develop a multi-objective route optimization framework balancing sweep completion time and occupant waiting duration. The baseline Mixed Integer Lin- ear Programming (MILP) model minimizes weighted makespan and waiting costs across homogeneous settings. For complex scenarios involving …
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Jiaqi Liu, Kerui Liu, Shunyuan Hou, Wencheng Ouyang, Tianxing Wang
Abstract: Based on rolling bearing vibration signals, this paper proposes an intelligent fault diagnosis model that integrates multi-domain features with attention mechanisms. First, by developing a multi-domain feature fusion strategy, time-domain signals, envelope spectra, and Discrete Cosine S-Transform (DCST) features are combined to form multi-channel inputs, effectively enhancing the information-carrying capacity of the original signals. Second, a deep one-dimensional network architecture combining …
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Xingye Kuang, Yang Sun, Qiuying Ke
Abstract: This paper proposes an inverse inference framework for audience voting based on latent variable modeling and maximum likelihood estimation. By introducing latent performance variables, it integrates judge scores and audience preferences into a constrained probabilistic measurement system to indirectly reconstruct incomplete voting data. Dynamic structural equations are adopted to account for temporal dependence and historical voting inertia, while elimination constraints are converted into …
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Li Zhang, Xiuli Wang
Abstract: This paper investigates an integrated scheduling problem in U-shaped seru production systems under a static and deterministic order environment. The problem jointly determines order-to-seru assignment, intra-seru order sequencing, and multi-skilled worker allocation, with the objective of minimizing the makespan. Compared with conventional parallel-machine scheduling, U-shaped seru scheduling involves stronger decision coupling because workload distribution, learning effects, sequence-dependent …
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Zitong Zhou, Zhenyu Yang, Tianrui Zhou
Abstract: This paper investigates the fairness and stability of competition rankings in multi-source evaluation scenarios. We construct a comprehensive framework that combines audience voting reconstruction, counterfactual simulation, and analysis using random forests and SHAP explanations, and propose the RMF-Ranking fairness mechanism. This method restores unobservable voting distributions through macro- and micro-level constraints, compares the impact of different scoring mechanisms on ranking results, …
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Audrey Mi
Abstract: Wildfires in drought-prone forest regions create urgent search-and-rescue challenges, including limited ground access, low coverage efficiency, and high risk to both victims and rescuers. This study proposes and tests an intelligent quadcopter rescue system, Fire Eagle Rescuer, that integrates victim localization, emergency supply delivery, and localized fire-suppression support. The system first discretizes the search environment into a two-dimensional grid and uses an S-shaped coverage …
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Yelin Luo
Abstract: Satellite land surface temperature (LST) is widely used to map urban heat, yet it characterizes the radiative state of surfaces rather than the near-surface air that people experience. This study quantitatively compares the surface urban heat island (SUHI) and the canopy-layer (air-temperature) urban heat island (CUHI) over Hong Kong, a high-density coastal subtropical city, and evaluates their implications for population heat exposure. SUHI is derived from Moderate Resolution Imaging …
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Yiqing Hu, Bowen Zhou, Jiangyuxuan Dai
Abstract: To address the issues of inconsistency between public scores and implicit voting scales, as well as significant fluctuations in the generation of competition results, this paper investigates stable ranking methods based on the fusion of multi-source evaluation data. First, historical competition rules are transformed into computable constraints, and the distribution of undisclosed votes is estimated using a Bayesian framework and MCMC sampling. Subsequently, consistency tests and mechanism …
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Caizhi Fei, Xiaoqing Liu, Siyu Qi
Abstract: The overlapping and aliasing of multi-voice signals in complex scenes can easily lead to the blurring of discourse boundaries, the disorder of hierarchical structure and the distortion of key semantic information, which is a key and difficult problem in the field of speech analysis and information processing. Based on the neural network model, this paper constructs a time series feature modeling mechanism for the mixed speech characteristics of multi-person voice, excavates the deep correlation …
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Mengqi Gao
Abstract: This paper develops a dynamical interpretation of the K theory of graph C star algebras through a systematic analysis of five canonical graph families, selected to isolate distinct dynamical phenomena: transient flow, periodic recurrence, mixing, and component interaction. For each family, the groups K0 and K1 are computed and the resulting invariants are correlated with explicit features of the associated graph groupoid and shift dynamics. The free part of K0 is shown to count irreducible …
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Bo Wu
Abstract: With the rapid digitalisation of financial markets, many new kinds of complex and interconnected risks for commercial banks have emerged that cannot be controlled by the old ways of risk management. Big data technology can help to better solve the problem of risk prevention and control in finance by collecting a large amount of data, analysing it, and issuing timely early warnings. A complete big data-driven financial risk prevention and control model for commercial banks has been put forward in …
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Ken Ning
Abstract: The challenge of ensuring robust autonomous driving control under sensor perception bias arises from the coupling among uncertainties in perception, hydraulics, computation, and actuation. A single deterministic controller or classifier cannot guarantee safety in such conditions. This paper proposes a diagnostic and control framework that integrates bias-aware residual construction, model-predictive reasoning, and conservative fallback rules using multi-sensor inputs. Parametrisation will be …
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Jianbo Ding, Dai Teng
Abstract: Release decisions for multi-tenant Zero Trust Secure Access Service Edge (SASE) platforms are difficult because a change that is acceptable in aggregate can violate a critical tenant's security objective under workload shift, missing telemetry, or configuration faults. This paper presents RA-DT, a risk-aware digital-twin framework that validates release readiness by replaying versioned release candidates against tenant-aware stress scenarios and issuing a joint risk certificate. The certificate …
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Haijian Zhang
Abstract: Large language models (LLMs) already emit syntactically plausible Verilog, yet a large share of generated designs fails functional verification, and the designs that do pass are not necessarily good implementations. We present VGMA, a verification-guided multi-agent framework that closes the loop between an RTL generator and open-source EDA tooling. VGMA synthesises a differential testbench directly from the reference port interface, compresses every failing simulation into a counterexample …
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Wenbin Shang, Jie-Si Yang, Guanyu Ding, Shiyu Yang
Abstract: Migrating Objective-C systems to Swift is not a token-level translation problem: API-name import rules, Foundation bridging, value semantics, optionality, collection behavior, and project-specific contracts interact with compiler constraints. This paper presents ArchMigrate-Swift, a compiler-in-the-loop, retrieval-augmented multi-agent framework that decomposes migration into schema retrieval, structural intent analysis, candidate generation, diagnostic repair, executable criticism, and …
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Wenyu Zhao, Tingjie Chen, Boyuan Wang, Zijian Shen
Abstract: Retrieval-augmented code generation can reduce hallucinated application programming interfaces and encourage reuse, but machine-learning (ML) pipelines impose constraints that ordinary semantic retrieval does not capture: the estimator, task type, data schema, preprocessing order, scoring metric, library version, and executable outputs must agree simultaneously. This paper presents PIPE-RAG, an execution-guided, language-model-compatible framework that treats reusable pipeline code as structured …
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