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Full-Text Articles in Entire DC Network
The Nist Artificial Intelligence Risk Management Framework: Adoption Challenges And Opportunities, Gillian Kennedy, Devin Patel, Humza Sheikh, Paul Wagner, Robert J. Honomichl
The Nist Artificial Intelligence Risk Management Framework: Adoption Challenges And Opportunities, Gillian Kennedy, Devin Patel, Humza Sheikh, Paul Wagner, Robert J. Honomichl
Journal of Cybersecurity Education, Research and Practice
Artificial intelligence (AI) is being adopted at an exponential rate to improve efficiency, decision-making, and cybersecurity, but its rapid integration introduces new and often poorly understood risks, including system errors, algorithmic bias, data privacy concerns, security vulnerabilities, and ethical dilemmas. This paper examines how organizations are implementing AI and evaluates the National Institute of Standards and Technology's AI Risk Management Framework (NIST AI RMF) as a tool for managing these risks. It reviews the benefits of AI adoption alongside the risks emerging from its use in business and broader society and examines the legal and ethical challenges organizations face when …
Parametric Modular Answer Set Programs Made Declarative, Jorge Fandinno, Yuliya Lierler, Torsten Schaub
Parametric Modular Answer Set Programs Made Declarative, Jorge Fandinno, Yuliya Lierler, Torsten Schaub
Computer Science Faculty Publications
In this paper, we explore the concept of modularity in first-order answer set programming (ASP). We introduce a new formalism called parametric modular logic programs, which allows defining subprograms with parameters and intensionality statements. We demonstrate how this formalism can capture the semantics of clingo-programs with collective control , a feature that enables structuring and instantiating subprograms. We provide theoretical foundations for modular ASP, illustrate its usefulness, and connect to traditional non-modular ASP.
On The Use Of Lorawan For Smart Fishing Applications In The Blue Economy Sector, Eva Shayo
On The Use Of Lorawan For Smart Fishing Applications In The Blue Economy Sector, Eva Shayo
Tanzania Journal of Engineering and Technology (TJET)
The growth of digital technology is expected to transform small-scale fishery sectors, where a need for robust, low-cost, long-range communication networks becomes critical. There exist several technologies that are used in the fishery sector but they are never affordable to small scale fisheries. This study evaluates the feasibility of using low cost Long Range Wide Area Network (LoRaWAN) technology specifically tailored for smart fishing environments to small scale fishery sector. Using simulation, we assess the performance of the key performance metrics including probability of success and energy efficiency under varying device densities and time. During evaluation, we considered end devices …
The Impact Of Gender Sensitization On Requirements Elicitation: A Controlled Experiment, Ruthbertha Kateule, Salome Maro, Leonard Peter Binamungu
The Impact Of Gender Sensitization On Requirements Elicitation: A Controlled Experiment, Ruthbertha Kateule, Salome Maro, Leonard Peter Binamungu
Tanzania Journal of Engineering and Technology (TJET)
Previous studies in software engineering have reported the importance of considering gender aspects in various software engineering activities, including requirements engineering, however, to the best of our knowledge, no work has investigated the impact of gender sensitisation on eliciting gender inclusive software requirements. The objective of this study was to understand the impact of gender sensitisation on software requirements elicitation. We conducted a controlled experiment using 40 undergraduate students from three different computing programs at the University of Dar es Salaam. The 40 participants were divided into 9 groups with both males and females. The participants were asked to elicit …
Enhancing Community Engagement Through ‘Nitunze Kilombero’ Mobile App: Case Of Climate Land Use And Cover Management For Kilombero Basin, Ghanima Chanzi, Subira Munishi
Enhancing Community Engagement Through ‘Nitunze Kilombero’ Mobile App: Case Of Climate Land Use And Cover Management For Kilombero Basin, Ghanima Chanzi, Subira Munishi
Tanzania Journal of Engineering and Technology (TJET)
The Kilombero Basin in southeastern Tanzania faces significant challenges due to rapid land use and land cover (LULC) changes driven by climate change, population growth, and unsustainable farming practices. This study assessed the role of community engagement and digital reporting through the 'NITUNZE KILOMBERO', mobile application in supporting water resources management in the basin. The App facilitates real-time reporting of environmental issues, provides educational resources, and enables collaboration between local communities and authorities. A mixed-methods approach, including household surveys and key informant interviews, was employed to assess the app's effectiveness. Results indicate high community awareness of LULC impacts, with 85% …
Trustworthy Reinforcement Learning And Communication-Efficient Multi-Agent Systems, Rui Zuo
Trustworthy Reinforcement Learning And Communication-Efficient Multi-Agent Systems, Rui Zuo
Dissertations - ALL
The rapid proliferation of autonomous systems, such as Unmanned Aircraft Systems (UAS) transitioning to large-scale Beyond Visual Line of Sight (BVLOS) operations, demands a paradigm shift toward reliable, transparent, and resilient autonomy. While Deep Reinforcement Learning (DRL) and Multi-Agent Reinforcement Learning (MARL) have demonstrated exceptional capabilities in complex decision-making and coordination, their real-world deployment in safety-critical domains is hindered by two fundamental challenges. First, the opaque, "black-box" nature of DRL models prevents human operators from understanding and trusting the agents' underlying logic. Second, as multi-agent operations scale, they become severely constrained by the stochastic link qualities and strict bandwidth limitations …
Scaling Logical Reasoning On Modern Hpc Hardware, Yihao Sun
Scaling Logical Reasoning On Modern Hpc Hardware, Yihao Sun
Dissertations - ALL
Deductive logic reasoning has evolved from a theoretical symbolic artificial intelligence tool into a massive computational workload. Modern domains, ranging from static program analysis and binary reverse engineering to knowledge-graph reasoning, rely on Datalog, a logical query language, to express deeply recursive, declarative specifications. However, scaling logic reasoning to these industrial workload exposes two interlocking ceilings in traditional engines. Architecturally, the memory bandwidth and parallel throughput of single-node CPUs fall drastically short of the read- and write-heavy demands of semi-naive evaluation. Asymptotically, traditional query processing algorithms, such as binary join algorithms generate massive intermediate relations that exhaust device memory on …
(R2077) Enhancing Queue Management: Dynamic Server Allocation And Optional Services In Stochastic Modeling, G. Ayyappan, S. Sankeetha
(R2077) Enhancing Queue Management: Dynamic Server Allocation And Optional Services In Stochastic Modeling, G. Ayyappan, S. Sankeetha
Applications and Applied Mathematics: An International Journal (AAM)
Consider a queueing system with a single server, where customer arrivals follow a Markovian arrival process and service times follow a phase-type distribution. The main server has the capability to recruit an additional server when the number of customers in the system exceeds a certain threshold, denoted as L. Both servers provide normal service to customers, and optional service is provided upon request. The main server takes multiple vacations, with the durations following an exponential distribution with rate parameter η, until there is at least one customer in the system. This system can be represented as a Markov chain process, …
(R2142) Queueing System With Batched Services, Server-Controlled Re-Service, Set-Up Time And Multiple Vacation, S. Karpagam, N. Aarthy, B. Somasundaram
(R2142) Queueing System With Batched Services, Server-Controlled Re-Service, Set-Up Time And Multiple Vacation, S. Karpagam, N. Aarthy, B. Somasundaram
Applications and Applied Mathematics: An International Journal (AAM)
To analyze a bulk queueing system with server-controlled admission for reservice, low-batch service, multiple vacation and set-up time. The study explores how the server dynamically adjusts between low-batch and bulk services based on the queue size. After completing a bulk service, the departing batch may request reservice with a certain probability. However, accepting the request is not mandatory, and the server admits it with some probability. Whenever the queue becomes empty, whether after reservicing, completing service with no reservice request, or ending the low-batch service, the server enters a random-length vacation. If the queue still has less than ‘a’ customers …
From Detection To Segmentation: A Foundation Model Approach To Organoid Brightfield Image Analysis Using Sam 3, Hiren Manani
From Detection To Segmentation: A Foundation Model Approach To Organoid Brightfield Image Analysis Using Sam 3, Hiren Manani
Theses - ALL
This thesis presents the first systematic application of SAM 3, a unified foundation model for promptable segmentation, to mouse small intestinal organoid brightfield microscopy image analysis. The work spans the complete pipeline from zero-shot baseline evaluation through domain-specific fine-tuning on a GPU cluster, and documents the full engineering process required to adapt a state-of-the-art foundation model to a novel biomedical imaging domain. A comprehensive literature review of over 20 papers spanning detection-based, classical segmentation, foundation model, and morphological analysis approaches identified a clear research gap that this thesis addresses. Five critical compatibility patches were developed to deploy SAM 3 on …
Constrained Neural Intelligence: Investigations Into Deep Multi-Objective Optimization, Naveed Tahir
Constrained Neural Intelligence: Investigations Into Deep Multi-Objective Optimization, Naveed Tahir
Dissertations - ALL
Neural intelligence is identified with complex learning problems optimized over the high-dimensional, non-convex parameter spaces of deep neural networks. Solving such problems generally requires handling competing objectives and conflicting constraints. This is traditionally dealt with using heuristic methods that collapse such complexity into unconstrained, singular objectives. While computationally convenient, this invites a tradeoff against the precision and stability afforded by non-heuristic, geometry-aware approaches. This dissertation explores constrained multi-objective learning in various applied and theoretical contexts and highlights the feasibility of approximate methods as well as the necessity of exact methods. We propose a framework for equality-constrained deep learning via approximate …
Molecular Identification Of Cryptococcus Albidus Isolated From A Gingivitis Infection In A Male From Karbala City, Iraq, Maysaa Taqi Al-Khazali, Zahraa Raheem Murshidy, Sarah Kadhim Al-Rahimy, Sura Abd Ali Kadhim Mohammed, Dhuha Ali Hussein
Molecular Identification Of Cryptococcus Albidus Isolated From A Gingivitis Infection In A Male From Karbala City, Iraq, Maysaa Taqi Al-Khazali, Zahraa Raheem Murshidy, Sarah Kadhim Al-Rahimy, Sura Abd Ali Kadhim Mohammed, Dhuha Ali Hussein
Karbala International Journal of Modern Science
The current study presents a case of gingivitis caused by Cryptococcus albidus in a 35-year-old male from the city of Karbala in Iraq. This fungal species was identified via morphology, microscopy, additionally to the VITEK system. C. albidus was further confirmed using the polymerase chain reaction (PCR) technique by amplifying the 18S rRNA gene as a universal primer and sequencing. Sequences analysis revealed that this strain of C. albidus had not been previously documented in the NCBI database. Hence, the newly obtained sequences were submitted to the GenBank repository and assigned the accession number OQ975882.1, marking the first report of …
A Scoping Review Of Sycophancy In Large Language Models: Operational And Theoretical Recognition, Kallen Zhou, Manning Littlejohn, Isabella Garrard
A Scoping Review Of Sycophancy In Large Language Models: Operational And Theoretical Recognition, Kallen Zhou, Manning Littlejohn, Isabella Garrard
Endeavors: Mississippi State Undergraduate Research Journal
As large language models (LLMs) usage grows across different domains, sycophancy, the tendency for output to align with users, is increasingly being recognized as a primary issue arising from applying LLMs into critical areas. Current research has provided a variety of theoretical definitions, mitigation techniques, and quantification for sycophancy. However, there is little to no consistency across different papers. This scoping review seeks to connect different works on LLM sycophancy by identifying themes in theoretical definitions, measurement methods, and inducement techniques of sycophancy. By analyzing 26 papers (preprints, conference proceedings, and journal articles) from arXiv, ACL Anthology, and Scopus, this …
Exploration Of Talent Cultivation System And Practical Model For Simulation And Optimization Of Intelligent Manufacturing System, Xinyu Li, Zheng Duan, Liang Gao, Chunjiang Zhang, Peigen Li
Exploration Of Talent Cultivation System And Practical Model For Simulation And Optimization Of Intelligent Manufacturing System, Xinyu Li, Zheng Duan, Liang Gao, Chunjiang Zhang, Peigen Li
Journal of System Simulation
To address problems such as the insufficient integration of science and education in the talent cultivation system for traditional manufacturing system simulation and optimization, the insufficient integration of industry and education in cultivation goals and approaches, and the lack of full-chain industrial-level practical cultivation means, a "1223" reform scheme for innovative talent cultivation in the intelligent manufacturing system was formed. Research and practice were carried out focusing on the talent cultivation system, cultivation approaches, and practical cultivation resources for the simulation and optimization of the intelligent manufacturing system. Significant outcomes were achieved in aspects of innovative talent cultivation, faculty and …
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Journal of System Simulation
The accuracy of the traditional EKF in parameter identification of the PMSM tends to be degraded under load changes or abrupt changes in internal parameters of the motor. This paper proposes an IGWO adaptive interconnected Kalman filter observer, which constructs an adaptive mechanism that combines the innovation and residuals to achieve dynamic adjustment of the process noise matrix and system noise matrix, thereby avoiding the problem of reduced parameter identification accuracy due to reliance on fixed covariance matrices under operating condition changes. A multi-parameter interconnected coupling compensation identification model for PMSM is built to mitigate the effects of measurement noise …
Adaptive Path Planning For Robotic Arms Integrating Rrt* And Apf, Zhirun Chen, Jie Yuan, Erkenbieke Jia, Ningning Zhang, Chao Liu, Yushan Ye
Adaptive Path Planning For Robotic Arms Integrating Rrt* And Apf, Zhirun Chen, Jie Yuan, Erkenbieke Jia, Ningning Zhang, Chao Liu, Yushan Ye
Journal of System Simulation
To address the issues of large search space, low efficiency, and slow convergence of the RRT* algorithm in 3D path planning of robotic manipulators, an adaptive path planning algorithm integrating RRT* and APF is proposed. In the sampling phase, a Sobol sequence-based obstacle avoidance strategy and an APF adaptive-threshold, goal-biased sampling method are used to improve the quality of sampling points. During the expansion phase, sampling, attractive, and repulsive vectors are integrated, and adaptive weights are designed based on environmental information to generate a resultant force direction, thus enhancing the expansion guidance. For step size control, the obstacle repulsive potential …
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Journal of System Simulation
Insufficient friction force compensation accuracy degrades motion smoothness, stability, and assistive compliance of elbow joint rehabilitation robots. To address this issue, an improved Stribeck friction force model integrating temperature and speed factors was proposed. The model employed an exponentially decaying friction factor to describe the characteristic that the increase rate of friction force slowed down with the rise of the robot's operating speed and designed a viscous function considering temperature effects to suppress friction force fluctuations caused by temperature changes. Experimental results indicate that the model achieves stable friction force compensation under different operating states of the robot and has …
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Journal of System Simulation
To address the severe degradation of object detection performance under extreme weather conditions, a detection framework based on the Kolmogorov-Arnold theorem, termed KADet, is proposed. A dynamic Kolmogorov-Arnold Transformer is designed, which leverages learnable nonlinear activation functions to enhance the modeling capability for complex distortions introduced by weather degradation. A Kolmogorov-Arnold spatial-channel network is developed by integrating KAT convolution with spatial-channel convolution to strengthen feature learning of relationships between targets and backgrounds in degraded scenes. An improved loss function is introduced to guide the optimization of the activation functions, and interpretability is analyzed through visualization of their curves. …
Exploration Of Online-Offline Integrated Practical Teaching Path Driven By Digital-Intelligent Simulation, Zhen Zuo, Dong Zhang, Zhi Wang, Zhongxin Li
Exploration Of Online-Offline Integrated Practical Teaching Path Driven By Digital-Intelligent Simulation, Zhen Zuo, Dong Zhang, Zhi Wang, Zhongxin Li
Journal of System Simulation
To address the disconnection between theory and practice, industry and education, and scientific research and teaching in traditional practical teaching, this paper utilized digital-intelligent simulation to empower practical teaching, promoted the collaborative linkage between national-level science and education platforms and high-quality industrial research and development platforms, and constructed a vehicle-oriented "CAE simulation, autonomous driving simulation, and performance testing simulation" practical system. Guided by the constructivist learning theory, this paper innovated the practical model by integrating online and offline approaches, built a competency-oriented practical education ecosystem through competition-education integration, and formed a new "competency-led, industry-oriented, and project-driven" paradigm of …
Algorithmic Monocultures In Hiring, Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel, Dan Saul Jurafsky, Percy Liang
Algorithmic Monocultures In Hiring, Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel, Dan Saul Jurafsky, Percy Liang
Economics Faculty Articles and Research
Many employers screen job applicants with algorithms built by the same few algorithm vendors. We hypothesize that algorithmic monoculture leads to the same individuals and members of the same racial groups facing rejection. We acquire and analyze a novel dataset of 3 million applicants submitting 4 million applications where all the applications are screened by algorithms built by the same vendor. We find clear racial disparities in applicant outcomes. Of all applications submitted by Asian and Black applicants, 14.74% and 25.87% are submitted to positions that adversely impact Asian and Black applicants, respectively, according to U.S. employment discrimination standards. Individuals …
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Journal of System Simulation
Existing occupancy models fail to fully consider the interference of underwater time-varying ocean currents and task time constraints, and AUVs lacks real-time motion control. To address these issues, a shortest time occupancy method based on quantile regression and distributed TD3 was proposed. The Bayesian inference method was used to identify hydrodynamic parameters, and the kinematic and dynamic models of AUVs were established; the shortest time occupancy equation was constructed, and the occupancy target point and occupancy time were solved; a first-order Gauss-Markov process was introduced to simulate the time-varying ocean current environment, and the training of control strategy for AUV …
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering, Jun Guo, Yixian Liu, Lianbo Ma, Jian Liu, Chunyan Xu
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering, Jun Guo, Yixian Liu, Lianbo Ma, Jian Liu, Chunyan Xu
Journal of System Simulation
In view of the structural disconnection between talent training and industry needs caused by the limitations of traditional computer experiment teaching in scenario authenticity, technological frontier, interdisciplinary integration, and student subjectivity, this paper proposed and practiced a new simulation-based experimental teaching system deeply integrating Chinese educational wisdom. Taking "incremental progress and learning by guided inquiry" as the core philosophy, through a four-in-one paradigm transformation of "task modularization, scenario virtualization, technological frontier, and integration deepening", this paper promoted the teaching to shift from closed skill verification to open engineering innovation and constructed a complete implementation path including "closed-loop iterative teaching process" …
Design Of Teaching Model For Simulation Engineering Comprehensive Practical Course, Meigen Huang, Xin Zhou, Tian Jing, Tao Wang
Design Of Teaching Model For Simulation Engineering Comprehensive Practical Course, Meigen Huang, Xin Zhou, Tian Jing, Tao Wang
Journal of System Simulation
To cultivate postgraduates' comprehensive engineering problem-solving ability to complex problems, based on Wittrock's generative learning theory and the agile systems engineering paradigm, this paper proposed an overall idea of curriculum construction reform promoted by the integration of teaching and research, independently developed an unmanned swarm attack and defense simulation experimental teaching platform, constructed a comprehensive practical case of "warship defense against unmanned aerial vehicle swarm attacks", and refined a relatively advanced and distinctive teaching model for the simulation engineering comprehensive practical course. This model effectively strengthens postgraduates' engineering problem-solving thinking for complex problems, stimulates their independent innovation ability, elevates …
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Journal of System Simulation
To investigate the energy release characteristics of extended sources in low-pressure environments, a combined experiment and simulation approach was adopted. Four typical altitudecorresponding pressures were selected as experimental conditions. An infrared thermal imager was employed to monitor parameters such as combustion temperature, radiance, and combustion area during the combustion process of the extended source. When the pressure decreases from 101 kPa to 30 kPa, the ignition time of the extended source doubles; the total energy release attenuates by 44.78%, and the combustion area reduces by 45.95%, but the fluctuations of peak temperature and average temperature are less than 3%, …
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane, Minghui Li, Daoxiang Gao
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane, Minghui Li, Daoxiang Gao
Journal of System Simulation
An output feedback control algorithm is designed based on reinforcement learning for the optimal control problem of overhead crane system. A high gain observer (HGO) is designed using output data to estimate the unmeasurable states of the overhead crane system. Based on the estimated states from the high-gain observer, a policy iteration (PI) method is designed with integral reinforcement learning, which uses Critic and Actor neural networks to approximate the optimal value function and control strategy, and adjusts the neural network weights in real time through online adaptive algorithms. According to the Lyapunov stability theory, the uniform ultimate boundedness of …
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Journal of System Simulation
Three-dimensional Gaussian splatting (3DGS) provides an alternative approach for novel view synthesis from the perspective of explicit representation. By reconstructing scenes using 3D Gaussian primitives and replacing traditional ray integration with a point-based rasterization process, it not only improves training and rendering efficiency but also offers new insights for complex scene reconstruction. This paper divided 3DGS-based complex scene reconstruction methods into three major categories and elaborated on them around large-scale scenes, sparse views, and dynamic scenes. It reviewed the current development status of this field and pointed out possible future research directions.
Exploration And Practice Of Talent Cultivation System For System Modeling And Simulation, Shaoping Wang, Chao Zhang, Ni Li, Yong Cui, Yongjia Zhao, Quan Quan
Exploration And Practice Of Talent Cultivation System For System Modeling And Simulation, Shaoping Wang, Chao Zhang, Ni Li, Yong Cui, Yongjia Zhao, Quan Quan
Journal of System Simulation
Focusing on the cultivation of innovative talents in modeling and simulation of aerospace and safety-critical control systems and facing the problems and challenges in the education and teaching of talent cultivation for system modeling and simulation, this paper inherited the "red ambition, soaring far" spirit of simulation researchers in Beihang University, constructed an integrated bachelor, master, and doctoral course system empowered by the latest key technologies, designed open and collaborative aerospace teaching cases, independently developed a control system simulation teaching platform based on Chinese simulation software MWORKS, and constructed a hardware-in-the-loop simulation experimental verification system for C919 aircraft, to …
Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan
Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan
Journal of System Simulation
In the process of course implementation, local universities generally face problems such as students' weak mathematical and physical foundations, disconnection between teaching content and technological frontiers, single teaching method, and fragmented cultivation of practical capability. Based on long-term teaching reform practice, a four-dimensional gradient integration teaching model of "value guidance, knowledge restructuring, scenario innovation, and capability progression" was proposed, and its theoretical logic, implementation path, and practical effect were systematically elaborated. This model can effectively stimulate students' intrinsic motivation for learning, promote the digital and intelligent updating of teaching content, expand the teaching scenario of industry-education integration, and realize …
Dynamic Analysis Of Flexible Mechanism With Lubrication Clearances Considering Uncertain Parameters, Xiulong Chen, Yi Sun, Aiguo Wang
Dynamic Analysis Of Flexible Mechanism With Lubrication Clearances Considering Uncertain Parameters, Xiulong Chen, Yi Sun, Aiguo Wang
Journal of System Simulation
This paper conducted a dynamic analysis on a seven-link mechanism suitable for a hybriddriven press, simultaneously considering lubrication clearances, interval parameters, and link flexibility. Based on the Lagrange equations of the first kind, the dynamic equations of the flexible mechanism with lubrication clearances under deterministic parameters were established; interval variables were introduced to establish a dynamic model considering interval parameters, and the Chebyshev interval algorithm and the Runge - Kutta method were used to solve the response interval curves of interval parameters such as clearances value, dynamic viscosity, and cross-sectional area. The results show that compared with the results under …
Energy Management Strategy For Hybrid Electric Buses Considering Vehicle Mass Variation, Jinjun Tang, Shuaijie Zhang
Energy Management Strategy For Hybrid Electric Buses Considering Vehicle Mass Variation, Jinjun Tang, Shuaijie Zhang
Journal of System Simulation
The vehicle mass variation during the operation of buses affects power demand of the vehicle, which can result in poor performance of energy management strategies. To this end, a hybrid electric bus energy management strategy based on proximal policy optimization-adaptive simulated annealing (PPOASA) is proposed. ASA is introduced into PPO to perturb policy parameters according to policy entropy before the policy update, and the perturbed policies are adaptively accepted or rejected by employing the Metropolis criterion, thus improving the exploration capability of the policy and convergence stability. Experimental results show that the proposed method outperforms the charge depleting-charge sustaining (CD-CS) …