Assessing Passenger Electric Vehicle Growth Strategies And Their Impacts On Electricity Demand Load And Co2 Emissions In Aceh Province To Achieve Net Zero Emission Target By 2060,
2026
Department of Interdisciplinary Engineering, Faculty of Engineering, Universitas Indonesia, Depok, West Java 16424, Indonesia
Assessing Passenger Electric Vehicle Growth Strategies And Their Impacts On Electricity Demand Load And Co2 Emissions In Aceh Province To Achieve Net Zero Emission Target By 2060, Taufik Hidayat, Widodo Wahyu Purwanto
Journal of Materials Exploration and Findings
The electrification of the transport sector is a crucial pathway for achieving Indonesia’s Net Zero Emissions (NZE) target by 2060. This study assesses the potential impact of passenger electric vehicle (EV) penetration on electricity demand and CO2 emissions in Aceh Province through a scenario-based modelling approach. Two policy-aligned scenarios are assessed: a low-penetration (LP) scenario and a high-penetration (HP) scenario. Using the Gompertz model and the ASIF framework, total CO2 emissions were projected from 2020 to 2060. Results show that although higher EV penetration reduces direct emissions from internal combustion engine (ICE) vehicles, total CO2 emissions increase more significantly under …
Implementation Of The Fourth Industrial Revolution Technologies In Tanzania’S Downstream Oil And Gas Industries,
2026
College of Business Education
Implementation Of The Fourth Industrial Revolution Technologies In Tanzania’S Downstream Oil And Gas Industries, Vitalis John Mwinyi
Tanzania Journal of Engineering and Technology (TJET)
The advent of the fourth industrial revolution (IR4.0) has resulted in the digital transformation of multiple sectors of the economy due to the disruptive nature of the technologies driving the revolution. The technologies have already found their way into the oil and gas industries across the globe, especially in upstream, midstream, and downstream operations. However, the degree of implementation is not the same for these operations, considering the complexities involved, integrated process, the associated risk and investment cost, among others. This study aimed to establish the implementation level of IR4.0 technologies in the downstream operations. A survey method was employed …
Security Risks Of Ai-Generated Code In Software Development,
2026
Christopher Newport University
Security Risks Of Ai-Generated Code In Software Development, Maame Agyekum
Cybersecurity Undergraduate Research Showcase
Artificial Intelligence(AI) has recently forced change globally, public Institutions and as well as national security. Advancement in machine learning, mixed datasets have enabled significantly powerful systems while being capable of operating at a large scale. As innovation and technological advancement increases at rapid pace, issues like a regulation gap where scientific development far exceeds the government’s ability to regulate and establish an effective oversight. As a result, Artificial Intelligence has been controlled by private companies, leading to an industry where speed and profit often outweigh safety and ethical responsibility.
Quantifying Dag-Ness: A Multi-Component Framework,
2026
Binghamton University--SUNY
Quantifying Dag-Ness: A Multi-Component Framework, Erik Csikos
Northeast Journal of Complex Systems (NEJCS)
Directed acyclic graphs (DAGs) are important structures across many disciplines, including mathematics and network science. They are especially useful in modeling causal and hierarchical relationships in a wide variety of applications. The primary
features of a DAG, directedness and acyclicity, are traditionally treated as binary. A graph is either DAG or it is not. Because of this, graphs are not usually interpreted as partially acyclic or partially directed. To address this gap in understanding, we
introduce a framework, consisting of five components, that will provide a continuous measure of DAG-ness. This measure will take into account edge acyclicity, node cyclicity, …
An Integrated Bayesian Network-Based Zero Trust Model To Quantify Cyber Risk In Small-Medium Businesses,
2026
Old Dominion University
An Integrated Bayesian Network-Based Zero Trust Model To Quantify Cyber Risk In Small-Medium Businesses, Ahmed Abdelmagid
Engineering Management & Systems Engineering Theses & Dissertations
Small-medium businesses (SMBs) play a pivotal role in the worldwide economy as they constitute the most considerable portion of businesses in developed countries like the UK and the US. As such, SMBs are likely targets of cybercrimes by malicious agents because of their vulnerable IT systems. The digital infrastructure of SMBs is more likely to be hit by cyberattacks than large businesses due to many factors that facilitate hackers’ missions. These factors include a limited financial budget devoted to cybersecurity, a lack of knowledge, an underrating of how dangerous cyber threats are, and a shortage of IT expertise. The enormous …
Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines,
2026
Embry-Riddle Aeronautical University
Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines, Walker Hall
Doctoral Dissertations and Master's Theses
The thesis addresses the persistent inefficiency and environmental degradation caused by internal combustion engines in modern vehicles, a major issue as the automotive industry faces increasing pressure to reduce fuel consumption and greenhouse gas emissions. Internal combustion engines, which power most cars today, convert only about 20-30% of fuel energy into useful work, with the remainder lost as heat and exhaust waste, including carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and nitrogen oxides (NOx). This inefficiency contributes to global carbon emissions, with transportation accounting for approximately 29% of U.S. greenhouse gases in 2021 [1]. As regulatory standards tighten (e.g., …
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management,
2026
Dakota State University
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park
Annual Research Symposium
Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …
A Causal Inference Methodology For Root-Cause Diagnosis In Nonstationary Industrial Time Series,
2026
Old Dominion University
A Causal Inference Methodology For Root-Cause Diagnosis In Nonstationary Industrial Time Series, Cansu Yalim
Knowledge and Creativity Expo
Industrial fault diagnosis lacks a procedure that learns time-varying causal structure from observational time series, makes identifiability limits explicit, and uses intervention-based reasoning to support root-cause assessment under industrial constraints. Although predictive maintenance can reduce downtime, diagnosis is often expert-rule-based or association-driven; pipelines may elevate downstream symptoms alongside true drivers and provide limited guidance on which feasible action would change a fault trajectory under current operating conditions. Because operating phases and fault progression create regime shifts, industrial systems rarely follow a single stable mechanism. This study develops and evaluates a three-stage, regime-aware causal diagnostic protocol based on a time-varying Dynamic …
Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks,
2026
Louisiana State University and Agricultural and Mechanical College
Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg
LSU Master's Theses
Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …
Research On Inter-Satellite Topology Design And Simulation Of Giant Leo Constellation Network With Consistent Pattern,
2026
University of Chinese Academy of Sciences, Beijing 100049, China; Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
Research On Inter-Satellite Topology Design And Simulation Of Giant Leo Constellation Network With Consistent Pattern, Zhicheng Li, Shuaijun Liu, Lixiang Liu
Journal of System Simulation
Abstract: The giant low earth orbit (LEO) constellation network uses inter-satellite links to form an intersatellite topology, realizing the transmission of data between satellites. In order to adapt to the nature of uniform and symmetrical distribution of satellites in the constellation, this paper used a consistent connection pattern between satellites to construct an inter-satellite topology, and by analyzing the arrangement of non-mirror links in the constellation, it was found that the connection method of each link of the satellite itself could be independent of each other, which reduced the simulation complexity and the solution space of the inter-satellite topology. …
Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse,
2026
Shenyang Aircraft Design and Research Institute, Shenyang 110066, China
Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse, Fangbo Wang, Jian Guo, Chenglie Du, Yifan Liu, Pengpeng Zhang
Journal of System Simulation
Abstract: The traditional model-based systems engineering (MBSE) method has problems of failing to fully exhibit complex combat logics in manned-unmanned collaborative combat system modeling, neglecting the scenario constraints in interface modeling, and requiring long-term and costly algorithm verification. In order to solve the problems, a methodology and design tool based on MBSE was proposed. An integrated verification method of a system's operational logic, interface design, and algorithmic design was constructed, thus providing a digital and rapidly iterative verification approach for system simulation. A verification environment for multiple key algorithm simulations was established, effectively reducing the economic cost of building verification …
Construction Approach Of Llm-Empowered Tactical Wargame Decision-Making Agents,
2026
Army Arms University of PLA, Beijing 100072, China; PLA 32302 Troops
Construction Approach Of Llm-Empowered Tactical Wargame Decision-Making Agents, Dayong Liu, Zhiming Dong, Qisheng Guo, Ang Gao, Xuehuan Qiu
Journal of System Simulation
Abstract: Decision-making agents are critical enablers for implementing human-machine, machinemachine, and hybrid human-machine adversarial interaction in tactical wargaming, where the intelligence level of the agent is crucial. To address the limitations of traditional decision agents such as insufficient adaptability, simplistic strategies, and high construction costs, a fusion decision framework driven by the large and small models was proposed. It specifically investigated the fusion approach of large language models with conventional decision-making agent construction approaches, including behavior trees, finite state machines, heuristic search, and deep reinforcement learning. New ideas and technical pathways are provided for the construction of tactical wargame …
Integrating Geometric Priors And Importance Sampling For High-Fidelity Indoor Scene Reconstruction,
2026
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Integrating Geometric Priors And Importance Sampling For High-Fidelity Indoor Scene Reconstruction, Tao Yang, Min Shi, Xigang Zhao, Suqin Wang, Qi Wang, Dengming Zhu
Journal of System Simulation
Abstract: Gaussian splatting suffers from geometric distortion during scene reconstruction, particularly in weakly textured indoor scenes. To address this issue, this paper proposes a high-precision indoor scene reconstruction method that integrates geometric priors and importance sampling. The proposed method fully considers the effect of the initialization process on reconstruction quality. An advanced feed-forward model is employed to generate high-quality geometric initialization, thus improving overall reconstruction stability and accuracy. An importance sampling strategy is introduced to mitigate the adverse effects of blurry images. Furthermore, a supervision mechanism based on a geometric prior model is designed to constrain the scene structure, further …
Key Problems Of Intent Recognition Research: A Survey On Activity, Plan And Goal Recognition,
2026
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Key Problems Of Intent Recognition Research: A Survey On Activity, Plan And Goal Recognition, Yi Zhang, Kai Xu, Shuilin Li, Dejun Chen, Yunxiu Zeng, Yong Peng
Journal of System Simulation
Abstract: With the development of artificial intelligence technology, realizing intent recognition in human-computer interaction has become one of the key challenges. In this paper, the current research status of three fields was systematically sorted out, namely activity recognition, plan recognition, and goal recognition, and the progress from the problem proposal to the current development was analyzed. The main research approaches in each field were reviewed, and a survey of research on activity recognition, a development overview of plan recognition, and a retrospective analysis of hotspots in goal recognition were conducted. This general view of the problem helped to clarify …
A Precise Damage Assessment Method For Lethal Blast Warheads Against Quadruped Robots,
2026
State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, China
A Precise Damage Assessment Method For Lethal Blast Warheads Against Quadruped Robots, Xueqian Wang, Jianbing Men, Xin Zhou, Shuyou Wang, Mei Li
Journal of System Simulation
Abstract: To accurately evaluate the damage efficiency of a lethal blast warhead on quadruped robots, a typical quadruped robot replication model and vulnerability damage tree were constructed through Autodesk Inventor. The power field calculation model of a lethal blast warhead was introduced. Based on the high-precision collision detection and graphic rendering technology of UE, this paper carried out the intersection detection of destructive elements and targets and realistic scene visualization. A visualization system for damage assessment of quadruped robots by a lethal blast warhead was developed, featuring capabilities such as parametric modeling of the lethal blast warhead, power field evolution …
Virtual Train Operation Platform Based On Digital Twin,
2026
CRRC Qingdao Sifang Rolling Stock Research Institute Co., Ltd., Qingdao 266000, China
Virtual Train Operation Platform Based On Digital Twin, Ziying Wang, Congjun Sun, Guihu Li, Tianhao Zhang
Journal of System Simulation
Abstract: In response to the limitations of traditional train operation simulation modeling, such as simplification, lack of adaptive adjustment capability for parameters, and proneness to error accumulation, a virtual train operation platform based on digital twin technology was proposed. A train model under specific railway lines was constructed. By combining with the intelligent operation and maintenance platform of the railway line, real-time train operation data was obtained and preprocessed. The adaptive chaos optimization algorithm was used to optimize the key parameters of train operation simulation online and establish a digital twin model of the railway line. This model adopted a …
Task Planning Method For Cross-Domain Cooperative Combat Operations Of Unmanned Systems Under Complex Constraints,
2026
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Task Planning Method For Cross-Domain Cooperative Combat Operations Of Unmanned Systems Under Complex Constraints, Haojie Fang, Ziyang Zhen, Huajun Gong, Xu Xie, Wei Luo
Journal of System Simulation
Abstract: In pre-combat task planning for cross-domain cooperative combat operations, to solve the problems of diverse and complex constraints and difficulties in solving planning models caused by performance differences of unmanned systems and increased requirements for cooperative combat operations, a multi-strategy enhanced grey wolf optimization (MSEGWO) algorithm was proposed. By considering various complex constraints such as performance of each type of unmanned systems, munition usage, task timing, task time window, and flight path, a task planning mathematical model with minimizing the comprehensive cost as the objective was established. Improvement strategies such as nonlinear adjustment of convergence factor, alternative solution space …
Review Of 3d Human Reconstruction Methods Empowering Vr/Ar,
2026
School of Informatics, Xiamen University, Xiamen 361102, China
Review Of 3d Human Reconstruction Methods Empowering Vr/Ar, Lisha Zhang, Yuchi Huo, Qi Ye, Anjun Chen, Shihui Guo, Jiming Chen
Journal of System Simulation
Abstract: 3D human reconstruction is critical for VR/AR. Early methods relied on multi-view cameras and depth sensors but were costly. Mid-term approaches using parametric human models enabled efficient single-image reconstruction, while implicit neural representations improved fidelity yet suffered from low efficiency. Currently, 3D Gaussian Splatting achieves high accuracy and real-time rendering as a new paradigm. Challenges include detail distortion and limited generalization, and future development will focus on VR/AR integration.
Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention,
2026
School of Computer Science and Technology, Anhui University, Hefei 230601, China
Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention, Mingwei Cao, Fengna Wang, Zilong Wang, Haifeng Zhao
Journal of System Simulation
Abstract: To address the problems that neural radiance fields(NeRF) are prone to artifacts and texture blurring in novel view synthesis under sparse view input and complex scenes, this paper proposed neural radiance fields based on explicit feature matching and scaled dot-product attention(EMD-NeRF). A multiscale feature extraction network was used to extract multi-scale feature information from the input sparse views. A fusion dot-product module was utilized to calculate view interaction information as a shared branch. Cosine similarity was adopted as a matching clue for similarity embedding volume rendering. A regularization loss function was used to enhance the quality of the scene …
Research On Gaussian Splatting Modeling Of Power Equipment In 3d Scenes,
2026
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Research On Gaussian Splatting Modeling Of Power Equipment In 3d Scenes, Haiying Li, Haonan Xu, Junfang Hao
Journal of System Simulation
Abstract: To address the issues of missing camera poses in captured images and poor reconstruction quality in 3D modeling of power equipment, a 3D Gaussian splatting 3D modeling method for power equipment based on video sequences was proposed. Theffmpeg was adopted to extract video frames at a reduced rate, and the Scharr operator was employed to quantify the sharpness of video frames to screen high-quality images for forming an input dataset, ensuring the completeness of equipment poses and the quality of modeling data. Through multi-view feature point extraction and matching, combined with an incremental structure-from-motion algorithm to optimize and …
