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Mission-Oriented Combat Effectiveness Evaluation Model For Intelligent Equipment System-Of-Systems, Long Zhang, Wenbo Huang, Xuanming Feng, Zhen Lei, Ying Wang Oct 2026

Mission-Oriented Combat Effectiveness Evaluation Model For Intelligent Equipment System-Of-Systems, Long Zhang, Wenbo Huang, Xuanming Feng, Zhen Lei, Ying Wang

Journal of System Simulation

Abstract: A hierarchical evolutionary adaptive learning (HEAL) framework is proposed to address the problems in the operational simulation of intelligent equipment systems under complex adversarial environments, including fragmented hierarchical decision-making, unclear mapping between algorithmic indicators and operational effectiveness, and the lack of adaptive evolution capability of simulation models. A multi-layer learning architecture that integrates robust autonomous decision-making for single units, emergent collaboration of system networks, and game-theoretic evolution of system-of-systems strategies is constructed by following the “micro-meso-macro” system-oriented hierarchical modeling paradigm. A cross-layer closed-loop coupling among learned policies, cooperative structures, and operational effectiveness is achieved by combining bottom-up behavioral abstraction …

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Multimodal Perception-Based Trajectory Planning Method For Uavs In Forest Environments, Dequan Li, Jiahao Jiang Oct 2026

Multimodal Perception-Based Trajectory Planning Method For Uavs In Forest Environments, Dequan Li, Jiahao Jiang

Journal of System Simulation

Abstract: To address the requirements for low-latency local planning and safe obstacle avoidance in UAV forest-fire patrol under dense tree-trunk occlusion and locally invalid depth observations, this paper proposes a learning-based local trajectory planning method that fuses depth images, local occupancy distance maps, candidate-level collision-risk assessment, and pre-execution safety reranking. The method uses depth images, local occupancy distance maps, motion states, and target direction as inputs and generates 15 quintic-polynomial candidate trajectories in parallel using 3 × 5 angular motion primitives. During training, candidate safety costs, ranking supervision, and near-collision risk labels are constructed. During inference, online LiDAR point clouds …

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Manifold Alignment And Dual Prediction-Based Adaptive Dynamic Multi-Objective Evolutionary Algorithm, Xuezhi Yue, Chao Xiong, Yanshen Jiang, Zhaolu Guo, Hu Peng Oct 2026

Manifold Alignment And Dual Prediction-Based Adaptive Dynamic Multi-Objective Evolutionary Algorithm, Xuezhi Yue, Chao Xiong, Yanshen Jiang, Zhaolu Guo, Hu Peng

Journal of System Simulation

Abstract: To address prediction failure, manifold topology distortion, and insufficient adaptability in environmental response and operator configuration in existing prediction-based algorithms for dynamic multi-objective optimization under complex nonlinear environments and small-sample settings, this paper proposes a manifold alignment and dual prediction-based adaptive dynamic multi-objective evolutionary algorithm, termed MADP-DMOEA. When the environment changes, the algorithm decomposes the decision-variable manifold into center and shape components, effectively aligns manifolds at adjacent time instants via bipartite optimal matching, and identifies environmental change severity using geometric displacement. A dual prediction model is developed, in which a GRNN performs center extrapolation under severe changes, while an …

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Cooperative Hunting Method For Multiple Usvs Based On Improved Maddpg, Yonghao Zhang, Changyou Xue, Xueman Fan, Zhuo Cheng Oct 2026

Cooperative Hunting Method For Multiple Usvs Based On Improved Maddpg, Yonghao Zhang, Changyou Xue, Xueman Fan, Zhuo Cheng

Journal of System Simulation

Abstract: A cooperative hunting method based on improved multi-agent deep deterministic policy gradient (MADDPG) is proposed to address the challenges of non-stationary environments, sparse rewards, and partial observations in the cooperative hunting of targets with unknown motion patterns by multiple unmanned surface vessels (USVs). A Markov game model for hunting is built, and a multidimensional guided reward shaping function incorporating collision avoidance, hunting success, and energy consumption penalties is designed to mitigate the sparse reward problem. ResNet residual networks are introduced to construct the Actor and Critic networks and thus enhance the representation capability of deep networks for complex state-action …

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Five-Axis Multi-Station Process Planning Based On Multi-Task Graph Reinforcement Learning, Junjie Liu, Jianlei Xu, Litao Ju, Yanhai Hu, Qinghao Zhang, Qiang Liu Oct 2026

Five-Axis Multi-Station Process Planning Based On Multi-Task Graph Reinforcement Learning, Junjie Liu, Jianlei Xu, Litao Ju, Yanhai Hu, Qinghao Zhang, Qiang Liu

Journal of System Simulation

Abstract: A hierarchical intelligent planning architecture integrating multi-task graph and masked proximal policy optimization (MTG-MPPO) is proposed to address the challenges of factorial expansion of the state space and multi-objective interference in five-axis multi-feature machining. An attributed adjacency graph integrating boundary representation and machining direction vectors is constructed. Probabilistic soft labels are output through a multi-task network to quantify process flexibility and thus achieve prior topological pruning of solution space. An MDP model integrating directed acyclic graph masks and dense reward shaping is built. A Monte Carlo (MC) optimization mechanism based on policy distribution is introduced to coordinate cutting, tool-changing, …

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Dynamic Multi-Objective Optimization Algorithm Based On Residual-Driven Two-Stage Prediction And Its Application, Xin Zhang, Han Wang, Pengjiang Qian, Wei Fang Oct 2026

Dynamic Multi-Objective Optimization Algorithm Based On Residual-Driven Two-Stage Prediction And Its Application, Xin Zhang, Han Wang, Pengjiang Qian, Wei Fang

Journal of System Simulation

Abstract: A dynamic multi-objective optimization algorithm based on residual-driven two-stage prediction (RDTP) is proposed to address the dilemma of prediction strategies in dynamic multi-objective optimization struggling with insufficient samples in the early stage and low accuracy in the later stage. In the initial stage, if an environmental change is detected, grey prediction, which is fast and suitable for small samples, is employed to generate individuals for the new environment. A residual analysis is performed to determine whether to switch to a LSSVM to improve prediction accuracy as more samples become available. The Pareto front is clustered to select detection objects. …

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Optimization Of Mobile Power Resource Allocation And Scheduling For Multi-Point Emergency Response, Ding Ma, Tao Zhang, Bo Jiang, Yajie Liu, Shuijia Li Oct 2026

Optimization Of Mobile Power Resource Allocation And Scheduling For Multi-Point Emergency Response, Ding Ma, Tao Zhang, Bo Jiang, Yajie Liu, Shuijia Li

Journal of System Simulation

Abstract: In extreme event scenarios, urban mobile power resources (MPRs) suffer from uneven spatial distribution and capacity mismatch during emergency scheduling. To achieve globally rational allocation and improve resource configuration and power supply guarantee, a two-stage decision-making method for MPR allocation and scheduling is proposed for multi-point emergency power demands. First, the characteristics of MPRs and travel energy consumption are modeled. In the first stage, an allocation model considering demand satisfaction, capacity matching, and dispatch time is established to solve the macro-level matching problem between MPRs and demand points. In the second stage, an interface scheduling model is constructed based …

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Coordinated Optimization Of Heterogeneous Fleet Configuration And Multimodal Routing For Industrial Clusters, Renxin Xiao, Yifan Xu, Guisheng Chen, Nan Pan Oct 2026

Coordinated Optimization Of Heterogeneous Fleet Configuration And Multimodal Routing For Industrial Clusters, Renxin Xiao, Yifan Xu, Guisheng Chen, Nan Pan

Journal of System Simulation

Abstract: A two-level optimization model integrating heterogeneous electric vehicle fleet configuration with multimodal path coordination is built to address the challenges in industrial cluster freight transportation involving electric heterogeneous fleet scheduling, such as diverse tasks and stringent constraints on energy consumption and delivery timeliness. Considering the performance coupling characteristics of heterogeneous electric fleets in terms of load-energy consumption-endurance, based on the coordination of multimodal paths and fleet configuration coding, the upper level employs the GWO to optimize task splitting and fleet configuration. The lower level adopts a multi-neighborhood SA algorithm to achieve path coordination scheduling. Simulation results show that the …

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Simulation Study On Circular-Track Rgv Scheduling Based On Railway Operating Rules, Hualan Wang, Li Wang, Zhongning Fu Oct 2026

Simulation Study On Circular-Track Rgv Scheduling Based On Railway Operating Rules, Hualan Wang, Li Wang, Zhongning Fu

Journal of System Simulation

Abstract: To address the limitations of circular RGV systems under high-density operating conditions, including a simple operational structure and limited parallel operation capability, this study investigates track structures and dispatching mechanisms for complex operational requirements. Based on the agent-based modeling method implemented on the AnyLogic platform, a simulation model of an RGV system with a nested circular track layout was developed, in which an embedded sub-loop equipped with track-switching devices is introduced into the traditional circular track structure. Operating and dispatching rules suitable for the nested circular structure are designed by incorporating the concepts of section operation and overtaking in …

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Air Defense Resource Allocation And Reconstruction Method Based On Kggom, Jiaoxiong Chen, Chenglong Zhang, Yuqiang Zhao, Xianglin Li, Qiang Zhao Oct 2026

Air Defense Resource Allocation And Reconstruction Method Based On Kggom, Jiaoxiong Chen, Chenglong Zhang, Yuqiang Zhao, Xianglin Li, Qiang Zhao

Journal of System Simulation

Abstract: To address the challenge that traditional solving methods cannot meet real-time requirements in the intelligent allocation and reconstruction of air defense operation resources, this paper focuses on an intelligent solving method for the dynamic allocation and reconstruction of intercept timing sensor-weapon-target. A multi-constraint model is established with damage effectiveness and operation cost as optimization objectives, and a knowledge-guided genetic optimization method (KGGOM) is proposed. Through knowledge-guided population generation and evolution, constraint-aware operators with correction mechanisms, and multi-path search combined with simulated annealing for gene correction, it improves its optimization capability and speed. Historical superior solution retention and dynamic elite …

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Hybrid Jaya-Transformer-Based Task Scheduling Algorithm For Super-Agile Satellites, Haoyu Zhao, Guanghui Zhang, Lanting Hao, Meijia Guo Oct 2026

Hybrid Jaya-Transformer-Based Task Scheduling Algorithm For Super-Agile Satellites, Haoyu Zhao, Guanghui Zhang, Lanting Hao, Meijia Guo

Journal of System Simulation

Abstract: Super-agile satellite task scheduling is characterized by complex constraints and tight coupling among task transitions. To address the relatively long online solution times of traditional heuristic algorithms, this paper establishes a super-agile satellite task scheduling model that aims to maximize the task profit ratio while considering constraints on visible time windows, attitude transition time, energy, and storage capacity. A Transformer is used to learn task requirements, visible time windows, and global correlations among tasks, and a dynamic mask and a task scheduler are incorporated to generate feasible task sequences. To enhance the model's ability to learn complex task correlations …

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Aerial Refueling Scheduling Plan Generation Method For Multi-Position Task Management *, Jiachen Hu, Huanyu Li Oct 2026

Aerial Refueling Scheduling Plan Generation Method For Multi-Position Task Management *, Jiachen Hu, Huanyu Li

Journal of System Simulation

Abstract: An aerial refueling scheduling plan generation method based on hierarchical hybrid strategy is proposed to address the high complexity of aerial refueling scheduling for multi-position tasks and the difficulty for traditional manual operations or single-position-oriented solutions to manage tasks effectively. A multi-level strategic framework based on fixed-rule heuristics, rolling horizon optimization, and steady-state cyclic scheduling is developed and integrated into a hierarchical hybrid strategy to balance scheduling efficiency, optimization capability, and emergency response capability. Simulation results demonstrate that the proposed method effectively generates feasible refueling scheduling plans, producing viable plans under both undisturbed rotational operations and disturbed dynamic support …

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Flight Test Mission Planning Method Based On Adaptive Large Neighborhood Search, Luofu Wu, Xinyang Wu, Lunhao Ju, Guopeng Song, Rui Wang, Jiang Jiang Oct 2026

Flight Test Mission Planning Method Based On Adaptive Large Neighborhood Search, Luofu Wu, Xinyang Wu, Lunhao Ju, Guopeng Song, Rui Wang, Jiang Jiang

Journal of System Simulation

Abstract: Flight test mission planning is critical to aircraft performance evaluation, but traditional manual methods often struggle with extensive solution spaces and complex constraints. This paper constructs an overall flight test mission planning model and introduces a flight test planning algorithm (FTPA) based on adaptive large neighborhood search. FTPA utilizes Kahn topological sorting to generate an initial test-item priority sequence, which is then decoded into an initial solution, and jointly schedules flight test items and test aircraft within the adaptive large neighborhood search framework. A comparison with the CPLEX solver shows that the FTPA algorithm yields solutions with a gap …

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Large Language Model-Assisted Control Framework For Mixed Remote Sensing Satellite Constellations, Guohua Wu, Ziyan You, Lei Li, Yi Gu, Shuanglin Li Oct 2026

Large Language Model-Assisted Control Framework For Mixed Remote Sensing Satellite Constellations, Guohua Wu, Ziyan You, Lei Li, Yi Gu, Shuanglin Li

Journal of System Simulation

Abstract: A LLM-assisted control framework for mixed remote sensing satellite constellations is proposed to address the problem that the control and scheduling of mixed remote sensing satellite constellations cannot process users' raw natural language observation requirements and realize full-process automation from requirement input to scheduling schemes. LLMs are utilized to enhance the construction of domain knowledge graphs, requirement understanding and task characterization, and realize intelligent generation of scheduling schemes and optimal solution of scheduling models. A scheduling scheme generation method based on the "planning and execution" dual-Agent architecture is designed. Combined with the constellation scheduling toolset, the capability boundary of …

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On-Orbit Refueling Mission Planning Of Satellites Based On Improved Nsga-Ii, Guozheng Li, Rui Wang, Yi Lu Oct 2026

On-Orbit Refueling Mission Planning Of Satellites Based On Improved Nsga-Ii, Guozheng Li, Rui Wang, Yi Lu

Journal of System Simulation

Abstract: An improved NSGA-II solution framework based on multi-tree encoding is proposed to address the problems of high modeling complexity under large-scale scenarios and the tendency of traditional algorithms to fall into local optima. Based on multi-tree modeling, the complex mixed-integer programming problem is transformed into a multi-tree configuration optimization problem, thus reducing the constraint handling difficulty and improving the search efficiency of the solution space. Multi-tree crossover and mutation operators as well as the calculation method for objective functions are designed. A large neighborhood search (LNS) strategy is introduced, and the global exploration and local exploitation capabilities of the …

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High-Fidelity Dynamic Digital Twin Modeling Method For Permanent Magnet Synchronous Motor, He Lai, Jinquan Yang, Cong Peng, Bei Li Oct 2026

High-Fidelity Dynamic Digital Twin Modeling Method For Permanent Magnet Synchronous Motor, He Lai, Jinquan Yang, Cong Peng, Bei Li

Journal of System Simulation

Abstract: Conventional mechanism models often suffer from model mismatch due to the absence of nonlinear mechanical damping representation and the dynamic drift of electromagnetic parameters. To address this issue, a high-fidelity dynamic digital twin modeling method for permanent magnet synchronous motors is proposed. In the static mechanism modeling dimension, a friction energy decoupling strategy is proposed, which fundamentally overcomes the inherent conflict between steady-state accuracy and transient response from a physical logic perspective. For dynamic model updating, a distributed cascaded sensing architecture based on the multi-innovation recursive least squares and extended Kalman filter (MIRLS-MIEKF) algorithms is proposed. This architecture enables …

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Scheduling Optimization For Cascaded Hybrid Flow Shop Integrating Llm And Rl, Fuqing Zhao, Bin Wu, Tianpeng Xu, Ningning Zhu, Houbin Song, Yukai Yao Oct 2026

Scheduling Optimization For Cascaded Hybrid Flow Shop Integrating Llm And Rl, Fuqing Zhao, Bin Wu, Tianpeng Xu, Ningning Zhu, Houbin Song, Yukai Yao

Journal of System Simulation

Abstract: For the cascaded hybrid flow shop scheduling problem with AGV transportation, a multiobjective optimization model is built to minimize the makespan and total energy consumption. A hybrid algorithm framework integrating the LLM, covariance matrix adaptation evolution strategy, and RL strategy selection mechanism is proposed. LLMs are employed to generate heuristic priority rules and construct high-quality initial solutions. Covariance matrix adaption evolution strategy is adopted to optimize the search in continuous priority space, and an enhanced scalar fitness function integrating hypervolume gain and solution diversity is introduced. An RL strategy selection module based on the upper level information boundary is …

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Q-Learning Enhanced Memetic Algorithm For Robust Scheduling Of Space Launch Missions, Rui Lin, Xiaolu Liu, Yonghao Du, Mingyang Geng, Zhenshun Shi Oct 2026

Q-Learning Enhanced Memetic Algorithm For Robust Scheduling Of Space Launch Missions, Rui Lin, Xiaolu Liu, Yonghao Du, Mingyang Geng, Zhenshun Shi

Journal of System Simulation

Abstract: A robust optimization mathematical model and an enhanced memetic algorithm (MA) for space launch mission scheduling are proposed to address the practical challenges in space launch mission scheduling under the influence of multiple uncertainties such as equipment failure, process rework due to quality issues, and technological changes. A robust optimization scheduling model for space launch missions is built by integrating the makespan under the worst-case scenario, the average maximum makespan, and the average deviation of process start times. A Q-learning enhanced memetic algorithm (QMA) is proposed, which can dynamically select parent solutions based on the population state. Simulation experiments …

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Assessor Experiences In Cmmc Level 2 Certification Assessments: An Interpretative Phenomenological Analysis Of Role Expectations, Samuel Heuchert, John Hastings Oct 2026

Assessor Experiences In Cmmc Level 2 Certification Assessments: An Interpretative Phenomenological Analysis Of Role Expectations, Samuel Heuchert, John Hastings

Research & Publications

The Cybersecurity Maturity Model Certification program requires that third-party assessments be conducted under a non-consultative model. The model is intended to ensure impartiality for organizations seeking certification. While this structure defines expectations for assessor behavior, assessor experiences and interpretations of these constraints remain underexamined. The study examines the lived experiences of CMMC-Certified Assessors and how they navigate role expectations within the non-consultative model. Using Role Conflict Theory as a guiding framework, the study applied Interpretative Phenomenological Analysis (IPA) to semi-structured interviews to explore how assessors make sense of their roles. The analysis identified experiential themes that describe how assessors construct …

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Dynamic Graph Mamba Model For Crime Count Forecasting Based On Adaptive Geographic Fusion, Wadhah R. Baiee Oct 2026

Dynamic Graph Mamba Model For Crime Count Forecasting Based On Adaptive Geographic Fusion, Wadhah R. Baiee

Journal of Intelligent Informatics, Networking, and Cybersecurity

Daily crime counts are hard to predict due to variations in the patterns of crime across neighborhoods and over time, as well as that the patterns vary by offence type. Areas with a shared border can give different information for forecasts than areas with similar crime histories. This study investigates if the joint use of these two relationships would give better prediction than using one or the other, and whether the algorithm can be adapted to the frequent occurrence of zeros and variance greater than the mean. It evaluates the functionality of Dynamic Graph Mamba for Crime Prediction (DG-Mamba-CP), a …

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Optimized Fully Sharded Data Parallel For Efficient Distributed Training Of Bilstm With Multi-Head Attention For Network Intrusion Detection Systems, Noor Al-Huda H. Oleiwi, Ameer K. Hadi Oct 2026

Optimized Fully Sharded Data Parallel For Efficient Distributed Training Of Bilstm With Multi-Head Attention For Network Intrusion Detection Systems, Noor Al-Huda H. Oleiwi, Ameer K. Hadi

Journal of Intelligent Informatics, Networking, and Cybersecurity

The expanding volume of network traffic, the growing size of cybersecurity datasets, and the increasing complexity of deep learning models present major computational challenges to training deep learning-based Network Intrusion Detection Systems (NIDSs). Fully Sharded Data Parallel (FSDP) enables distributed training by sharding model parameters across multiple GPUs; however, the synchronization and communication overhead can limit its training efficiency. To overcome these limitations, this paper proposes an Optimized Fully Sharded Data Parallel (Optimized FSDP) framework that improves distributed training efficiency by dynamic gradient accumulation and synchronization scheduling. The proposed framework is integrated with a Bidirectional Long Short-Term Memory (BiLSTM) network …

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Calculation Of Alpha-Decay Half-Lives Using A Numerical Approach, Daniel Suescún-Díaz, Rosemberg Gómez-Noguera, Diego Rasero-Causil Oct 2026

Calculation Of Alpha-Decay Half-Lives Using A Numerical Approach, Daniel Suescún-Díaz, Rosemberg Gómez-Noguera, Diego Rasero-Causil

Karbala International Journal of Modern Science

This study introduces a numerical approach for estimating alpha-decay half-lives of alpha-emitting nuclei using a modified five-parameter Woods-Saxon potential. The radial Schrödinger equation is solved with the Numerov method to calculate the wave function and the barrier transmission probability, without relying exclusively on the WKB approximation. The calculations were performed for 398 nuclides taken from the NUBASE2020 database. Of these, 264 nuclides were used for the MWS5 parameter-adjustment stage, whereas the remaining 134 nuclides were reserved for an independent evaluation of the model. The results were compared with those obtained from two reference models: the modified Gamow-Like Model (MGLM) and …

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Antioxidant, Anti-Tyrosinase, Anti-Elastase, And Anti-Collagenase Activities Of Propolis Extracts From The Stingless Bee Tetragonula Laeviceps (Smith, 1857), Tri Hadi Handayani, Dimas Andrianto, Sih Kahono, Pamungkas Rizki Ferdian, Raden Lia Rahadian Amalia, Muhamad Ridwan Oct 2026

Antioxidant, Anti-Tyrosinase, Anti-Elastase, And Anti-Collagenase Activities Of Propolis Extracts From The Stingless Bee Tetragonula Laeviceps (Smith, 1857), Tri Hadi Handayani, Dimas Andrianto, Sih Kahono, Pamungkas Rizki Ferdian, Raden Lia Rahadian Amalia, Muhamad Ridwan

Karbala International Journal of Modern Science

Stingless bees incorporate propolis into their nest as a structural and protective material. Information remains limited on how solvent fractionation affects the antioxidant and enzyme-inhibitory activities of propolis produced by Indo nesian Tetragonula laeviceps. This study examined a crude extract prepared with 70% ethanol together with the n- hexane, ethyl acetate, and water fractions obtained from it. The analysis comprised total phenolic content (TPC), total flavonoid content (TFC), three antioxidant assays (ABTS, CUPRAC, TBARS), and inhibition of tyrosinase, elastase, and collagenase. The largest TPC and TFC values were obtained from the ethyl acetate fraction, at 85.93 ± 1.28 mg GAE/g …

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A Biased Variant Of The Ladybug Clock Problem, Jacob Vogelpohl, Russell May Oct 2026

A Biased Variant Of The Ladybug Clock Problem, Jacob Vogelpohl, Russell May

Communications on Number Theory and Combinatorial Theory

Instead of the common assumption of uniform probabilities for steps in a random walk on a graph, we generalize the steps to be biased and compute several statistics related to biased random walks on a cycle graph, more fancifully known as the ``ladybug clock problem." We obtain new explicit formulas for the distribution of probabilities for a walk to end on a particular node, the expected cover time for the cycle, and other similar statistics. We carry out these computations solely with generating functions related to the classic gambler's ruin problem.

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Constructing The Cyber Workforce Gap: Measurement And Its Consequences, Ryan Straight Oct 2026

Constructing The Cyber Workforce Gap: Measurement And Its Consequences, Ryan Straight

Journal of Cybersecurity Education, Research and Practice

Cyber workforce-gap figures steer federal strategy, industry advocacy, and the growth of educational programs. Rather than estimating the U.S. gap, this review examines how the estimates are made: through job-posting analytics, survey-based estimation, and federal accounting, each of which must assume its way from instrument to labor market. A census of this journal's complete run illustrates what those figures underwrite in one venue: of 176 items published across eleven years, 51 invoke a labor-market workforce claim, 46 treat it as settled fact, and only one, an editorial, interrogates it. Meanwhile, the producers and auditors of those figures have diverged. Between …

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Repeated Games In The Presence Of Incomplete Information, Reza Habibi Oct 2026

Repeated Games In The Presence Of Incomplete Information, Reza Habibi

The Journal of Economics and Politics

There are many strategic situations at which a game theoretical framework should be used to analyze the equilibrium decisions at which the incomplete information annoy the process of deriving the certain rules for making decisions. In these cases, players use signals of each other's to get proper decisions. For example, in economic environment, some macro-economic latent variables induce incomplete information. Morris and Shin (2000) referred this type of game as global game and studied one-shot type of it. However, in practical situations, it is a type of repeated game. In the current paper, following notations of Morris and Shin (2000), …

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Specification And Internal Assessment Of A Self Reported Protective Application Use Composite Among Computer Science Undergraduates In Enugu State Nigeria, Adesegun Nurudeen Osijirin, Leonard C. Anigbo, Oliver Okechukwu Oct 2026

Specification And Internal Assessment Of A Self Reported Protective Application Use Composite Among Computer Science Undergraduates In Enugu State Nigeria, Adesegun Nurudeen Osijirin, Leonard C. Anigbo, Oliver Okechukwu

Journal of Cybersecurity Education, Research and Practice

This study specifies a Protective Application Use Composite restricted to self-reported protective application use. A cross-sectional survey provided 364 complete records from Computer Science undergraduates at four universities in Enugu State, Nigeria, from 393 distributed questionnaires. The score is the equal-weight average of five questionnaire categories: antivirus, firewall, encryption, multi-factor authentication, and virtual private network use. Reanalysis of the author-supplied item records yielded category means from 2.097 to 2.376 and internal-consistency coefficients from 0.958 to 0.971. The composite mean was 2.170, with a standard deviation of 0.469. The first component of the category-score correlation matrix explained 50.98 percent of variance. …

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Agrivoltaics: Combining Food And Solar Power On Agricultural Lands, Dharla Soteros, Kendall Becker, Spencer J. Good, Ngoni Mufute, Matt Yost, Logan Mitchell, Scott Hotaling Oct 2026

Agrivoltaics: Combining Food And Solar Power On Agricultural Lands, Dharla Soteros, Kendall Becker, Spencer J. Good, Ngoni Mufute, Matt Yost, Logan Mitchell, Scott Hotaling

All Current Publications

Utah’s ranchers and farmers face pressure to sell land to developers, conserve water, and manage increasing production costs (Li et al., 2019). One way producers can keep growing food while diversifying and increasing revenue is by integrating agriculture and solar electricity generation on the same land, a practice known as agrivoltaics. In this fact sheet, the authors describe agrivoltaic setup options, summarize agrivoltaics' impacts on livestock and crop production, and discuss implementation economics.

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Wilson's Phalarope, A Migratory Bird, Depends On The Declining Great Salt Lake, William Christenson, Kendall Becker, Spencer J. Good, T.J. Clark-Wolf, Scott Hotaling Oct 2026

Wilson's Phalarope, A Migratory Bird, Depends On The Declining Great Salt Lake, William Christenson, Kendall Becker, Spencer J. Good, T.J. Clark-Wolf, Scott Hotaling

All Current Publications

This fact sheet describes how declining water levels and increasing salinity degrade habitat for brine flies and other prey Wilson’s phalaropes rely on. Because human use drives low water levels, changes to water management could reverse the lake’s decline and improve habitat quality for Wilson’s phalaropes and other species that depend on the Great Salt Lake.

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Research On Data Risk And Governance Of Generative Artificial Intelligence Empowering Intelligence Work, Yonghui Guo, Xiaobei Guo, Yuan Feng, Yapeng Li Oct 2026

Research On Data Risk And Governance Of Generative Artificial Intelligence Empowering Intelligence Work, Yonghui Guo, Xiaobei Guo, Yuan Feng, Yapeng Li

Journal of Scientific Information Research

[Purpose/significance] Generative Artificial Intelligence（GAI）generates numerous data risks in the process of empowering intelligence work. Fully understanding, identifying, and governing the data risks are the key to the effective empowerment of intelligence work by GAI. [Method/process] Based on the four stages of intelligence work, this paper subdivides the main data activities in intelligence work empowered by generative artificial intelligence from the perspective of the data workflow. Based on risk management theory, the data risks in data input, data processing, data content generation and data content dissemination, are systematically analyzed and identified. From three perspectives of institution, subject, and technology, a data …

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