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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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From Classification To Segmentation: Evaluating Machine Learning Defect Localization And Inspector Performance In Manufacturing, Gavin Smithson, Dakota Fulp, William M. Jones, Sharmistha Chakrabarti Oct 2026

From Classification To Segmentation: Evaluating Machine Learning Defect Localization And Inspector Performance In Manufacturing, Gavin Smithson, Dakota Fulp, William M. Jones, Sharmistha Chakrabarti

Journal of the South Carolina Academy of Science

High-volume manufacturing at Los Alamos National Laboratory requires rigorous quality assurance; however, sustained manual inspection can be inconsistent, costly, and fatiguing. This paper presents the model-evaluation component of a larger human-in-the-loop artificial intelligence project for manufacturing anomaly detection. MicroSentryAI uses pretrained models to identify potential anomaly regions, while AnnoMate provides accessible tools for annotating, validating, and comparing those regions. The study emphasizes the distinction between classification, which determines whether a sample is anomalous, and segmentation, which identifies the location of an anomaly. Using Intersection over Union (IoU), precision, recall, and Euclidean distance between centroids, experiments with simulated mask errors demonstrated …

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A Comprehensive Review On The Role Of Deep Learning For Detecting And Identifying Obscured Objects, Baraa Hasan Hadi, Jamila Harbi Saud Oct 2026

A Comprehensive Review On The Role Of Deep Learning For Detecting And Identifying Obscured Objects, Baraa Hasan Hadi, Jamila Harbi Saud

Karbala International Journal of Modern Science

Human operators frequently encounter eye fatigue that typically comes from workload and sleep deprivation. This could affect the efficiency and performance of vigilance significantly. In safety-sensitive applications such as traffic systems, healthcare, and security, this issue is essential. To address this issue, there is a need for situational awareness and maintaining continuous monitoring of the workload of the person. To this end, advanced artificial intelligence (AI) methods, denoted by a deep learning (DL) based approach, can be used. Such methods are also supported by computer vision (CV) to detect and identify obscured objects. Combining CV with AI can overcome the …

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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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Beyond Probability: An Analytical Exploration Of Fuzzy And Neutrosophic Paradigms In Binomial Acceptance Sampling, Uma G, Vela Muruga Anurahini P Oct 2026

Beyond Probability: An Analytical Exploration Of Fuzzy And Neutrosophic Paradigms In Binomial Acceptance Sampling, Uma G, Vela Muruga Anurahini P

Neutrosophic Systems with Applications

Acceptance sampling plans are widely used in Statistical Quality Control to determine the acceptance or rejection of production lots based on sample inspection. Classical sampling plans under the binomial distribution assume precise parameter values, which may not adequately represent uncertainty, vagueness, and indeterminacy encountered in practical inspection environments. This review summarizes acceptance probability formulations for single and double sampling plans developed using fuzzy and neutrosophic logic under the binomial distribution. The focus is on studies that model the fraction defective and related parameters as fuzzy or neutrosophic numbers, allowing imprecise and indeterminate quality information to be incorporated into sampling decisions. …

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Reliability-Calibrated Q-Rung Orthopair Neutrosophic Soft Ranking Under Partial Observability: An Auditable Industrial-Process Benchmark, Nagham Ahmed Abdelmegeed, Zeshan Aslam Khan Oct 2026

Reliability-Calibrated Q-Rung Orthopair Neutrosophic Soft Ranking Under Partial Observability: An Auditable Industrial-Process Benchmark, Nagham Ahmed Abdelmegeed, Zeshan Aslam Khan

Neutrosophic Systems with Applications

Multi-criteria decision systems often interpret disagreement among criteria as evidence that some criteria are unreliable. This is problematic when the disagreement reflects a genuine operational trade-off. We develop a reliability-and-admissibility-calibrated q-rung orthopair neutrosophic soft ranking procedure (RAC-qRON) that distinguishes recorded evidence quality from the direction of criterion preferences. An explicitly bounded interval for each alternative–criterion observation is mapped to truth, indeterminacy and falsity memberships, with an admissibility proof for every integer rung q ≥ 1. Criterion weights are adjusted according to recorded information coverage rather than cross-criterion correlation, and a fixed-reference ideal-distance calculation produces an auditable rank. The method is …

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Risk Prioritization Of ``Digital Drug'' And Consumer Neurostimulation Modalities: A Reproducible Interval-Valued Fermatean Fuzzy Entropy–Topsis Framework, Rawan Emad El-Saadany, Ahmed Samy, Mohamed M. Abdelhafeez, Mahmoud M. Ismail Oct 2026

Risk Prioritization Of ``Digital Drug'' And Consumer Neurostimulation Modalities: A Reproducible Interval-Valued Fermatean Fuzzy Entropy–Topsis Framework, Rawan Emad El-Saadany, Ahmed Samy, Mohamed M. Abdelhafeez, Mahmoud M. Ismail

Neutrosophic Systems with Applications

Consumer audio and multisensory stimulation technologies are increasingly accessible through streaming platforms, mobile applications, and immersive media. The expression digital drug is sometimes used for binaural-beat content intended to alter subjective states, but the term is a consumer/cultural label and does not imply pharmacological equivalence. Risk prioritization in this area is difficult because evidence is heterogeneous, several relevant criteria are qualitative, and judgments may be imprecise rather than point-valued. This paper develops a transparent interval-valued Fermatean fuzzy (IVFF) group decision framework that combines interval-preserving aggregation, Shannon entropy weighting, and TOPSIS for prioritizing digital drug risk scenarios under uncertainty. The method …

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Risk-Based Cybersecurity Threat Prioritization In Digital Twin-Enabled Cyber-Physical Systems, Nada Mohamed, Alshaimaa A. Tantawy, Ahmed M. Abdelmouty Oct 2026

Risk-Based Cybersecurity Threat Prioritization In Digital Twin-Enabled Cyber-Physical Systems, Nada Mohamed, Alshaimaa A. Tantawy, Ahmed M. Abdelmouty

Neutrosophic Systems with Applications

Digital Twin (DT)-enabled cyber-physical systems (CPS) face cybersecurity risks due to their complex connections and high levels of interdependence. Traditional methods, for assessing risk often fail to rank these threats. This is especially true when expert opinions include ambiguity, uncertainty or unclear information. A Type 2 Neutrosophic Entropy– Measurement of Alternatives and Ranking according to COmpromise Solution (Entropy- MARCOS) framework for cybersecurity threat prioritization in DT-enabled CPS is proposed in this paper. The uncertainty and indeterminacy present in expert evaluations are represented by Type 2 Neutrosophic Numbers (T2NNs). While the MARCOS technique is used to assess and rank cybersecurity threats …

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Context-Regulated Q-Neutrosophic Soft Model Selection Under Input Perturbation: Evidence From Three Classification Benchmarks, Poom Kumam, Supak Phiangsungnoen Oct 2026

Context-Regulated Q-Neutrosophic Soft Model Selection Under Input Perturbation: Evidence From Three Classification Benchmarks, Poom Kumam, Supak Phiangsungnoen

Neutrosophic Systems with Applications

Selecting a classifier using a single average metric can conceal instability across validation splits, poor lower-tail behavior, and sensitivity to input perturbations. This study formulates a context-regulated Q-neutrosophic soft model-selection procedure with two fixed evaluation conditions. For each classifier and performance criterion, mean attainment (truth), across-split dispersion (indeterminacy), and the complement of a lower empirical quantile (falsity) form an auditable three-component descriptor. A bounded lower-context regulator aggregates their penalized utilities; monotonicity and perturbation bounds follow directly from its convex representation. Four fixed classifiers are compared using five benefit-oriented criteria, three repetitions of stratified five-fold cross-validation, and paired test-feature perturbations. Three …

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Autofield-Poa: A Hybrid Automl–Metaheuristic Framework For Automated Feature Selection In Recommender Systems, Mohammed Dheyaaldeen Taha, Waleed Kareem Ahmed, Rana Saad Mohammed, Zied O. Ahmed Oct 2026

Autofield-Poa: A Hybrid Automl–Metaheuristic Framework For Automated Feature Selection In Recommender Systems, Mohammed Dheyaaldeen Taha, Waleed Kareem Ahmed, Rana Saad Mohammed, Zied O. Ahmed

Karbala International Journal of Modern Science

The problem of automated feature selection is one of the most important aspects of modern recommender systems, as overestimating the number of feature fields used, which can increase model complexity, inference latency, and performance degradation due to redundancy and noise. Although differentiable Automated Machine Learning (AutoML) based feature selection methods, including AutoField, are effective, they remain susceptible to initialization and local optima. Conversely, population-based metaheuristic algorithms are effective at global exploration, but are often inefficient in high-dimensional discrete spaces when randomly initialized. This paper presents AutoField-POA, a hybrid AutoML-metaheuristic framework that combines a differentiable controller with the Pelican Optimization Algorithm …

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A Yolov8x Framework For Breast Lesion Localization Using Real-World Mammographic Images, Hadeel Abdul Majeed Ghazi, Yarub Alazzawi, Hussein Hasan Nsaif Oct 2026

A Yolov8x Framework For Breast Lesion Localization Using Real-World Mammographic Images, Hadeel Abdul Majeed Ghazi, Yarub Alazzawi, Hussein Hasan Nsaif

Karbala International Journal of Modern Science

Breast cancer is one of the leading causes of mortality among women worldwide, and early and accurate mammographic assessment is important for timely diagnosis and improved patient survival. However, accurate breast lesion detection requires overcoming the issues of low lesion contrast, dense breast tissue, image noise, and variation in mammographic acquisition. In this study, we present a YOLOv8x-based computer-aided detection framework for automated breast lesion localization in full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) images acquired under heterogeneous clinical conditions. The framework was developed and evaluated using 501 clinical mammographic images obtained from multiple mammography systems, namely GE …

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An Object-Level Semantic Video Transmission Framework For Iomt Based On Lightweight Yolo And Motion Triggering, Iman Kadhum Abbood, Alaa Shawqi Jaber Oct 2026

An Object-Level Semantic Video Transmission Framework For Iomt Based On Lightweight Yolo And Motion Triggering, Iman Kadhum Abbood, Alaa Shawqi Jaber

Karbala International Journal of Modern Science

In Internet of Multimedia Things (IoMT) environments, video capture and frame transmission consume substantial sensor energy and impose considerable network overhead because of redundant data transmission. Traditional approaches often rely on repeated pixel-level operations and frequent execution of deep segmentation models, thereby increasing computational and transmission costs. This paper proposes an Object-Level Semantic Video Transmission Framework (OSVT) for resource-constrained IoMT environments in which high-definition visual data must be transmitted over low-bandwidth wireless multimedia sensor networks (WMSNs). The proposed OSVT incorporates a dual-stage wake-up mechanism that remains in sleep mode during static scenes, thereby reducing transmission load. The high-power YOLOv11-seg module …

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Data Without Borders, Sovereignty Without Guarantees: Cybersecurity Risks Of Cross-Border Data Hosting In The Global South, Evidence And Policy Lessons From Mozambique, Faztudo Languisse Eng. Oct 2026

Data Without Borders, Sovereignty Without Guarantees: Cybersecurity Risks Of Cross-Border Data Hosting In The Global South, Evidence And Policy Lessons From Mozambique, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The digital transformation of public and private institutions across the Global South has produced a paradox: as states digitize government services, financial systems, and citizen records, an increasing share of this data is hosted on servers physically located in the United States, the European Union, and other developed economies. This article develops a taxonomy of the cybersecurity and sovereignty risks generated by this dependency, distinguishing deliberate risks, arising from extraterritorial legal instruments such as the United States CLOUD Act, foreign surveillance regimes, and a concentrated hyperscale cloud market, from non-deliberate risks, arising from undersea cable failures, hyperscaler outages, misconfiguration, and …

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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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Innovative Development Of Synthetic Biology Industry From Perspective Of Deep Integration Of Four Chains, Qin Guo, Chao Zhang Oct 2026

Innovative Development Of Synthetic Biology Industry From Perspective Of Deep Integration Of Four Chains, Qin Guo, Chao Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Future industries represent the development direction of technological innovation and emerging industries, and are the main path to accelerate the formation of new quality productivity. As an important subsector of the future industry, synthetic biology industry is becoming a new track and new format for new quality productivity, and various regions are making cutting-edge directions such as synthetic biology industry a hot topic for future industrial layout. Based on the analysis of typical cities such as Shenzhen, Beijing, Tianjin, Shanghai, Hangzhou, and Changzhou, the current integration of the Four Chains in the synthetic biology industry is facing a four-dimensional dilemma …

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Ai-Driven Drug Innovation Research: Trends, Challenges, And Countermeasures, Tian Miao, Qi Zhou, Lianzheng Zhou, Weijun Xu, Siyuan Liu Oct 2026

Ai-Driven Drug Innovation Research: Trends, Challenges, And Countermeasures, Tian Miao, Qi Zhou, Lianzheng Zhou, Weijun Xu, Siyuan Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is profoundly transforming the innovation paradigm, industrial ecosystem, and business model of drug research and development. In recent years, the global AI-driven pharmaceutical market has grown rapidly. Major economies, multinational pharmaceutical enterprises, and technology giants are accelerating their strategic deployment. AI pharmaceutical industry has entered a critical stage of transitioning from proof-of-concept to commercial-application. China attaches great importance to the integrated development of AI and the biopharmaceutical industry, but it still faces challenges, including data scarcity, talent shortages, algorithmic black-boxes, regulatory lag, and weak foundations. This study proposes measures from the aspects of data supply, talent cultivation, …

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Toward 2035: 20 Fundamental Scientific Problems In Artificial Intelligence, Working Group For Artificial Intelligence Advancement Chinese Academy Of Sciences Oct 2026

Toward 2035: 20 Fundamental Scientific Problems In Artificial Intelligence, Working Group For Artificial Intelligence Advancement Chinese Academy Of Sciences

Bulletin of Chinese Academy of Sciences (Chinese Version)

The development of the artificial intelligence （AI） discipline is effectively expanding the capability boundaries of AI. To explore the foundational theories and underlying core technologies for next-generation of general AI, the Chinese Academy of Sciences (CAS) has formulated 20 fundamental scientific problems in AI. Centered on “disciplinary reconstruction of AI foundational theories (Y+AI)” and “AI-enabled applications of complex systems across multiple domains (AI+X)”, these problems are characterized by multiple complexities including openness, high dimensionality, high dynamism, large scale, and cross-scale properties.

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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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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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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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Stewards Of Data: A Practical Handbook For Undergraduate Researchers In Engineering And Applied Sciences, Şenay Purzer, Wei Zakharov, Carla B. Zoltowski Oct 2026

Stewards Of Data: A Practical Handbook For Undergraduate Researchers In Engineering And Applied Sciences, Şenay Purzer, Wei Zakharov, Carla B. Zoltowski

Purdue University Press Books

Filled with actionable guides and real-world examples, Stewards of Data: A Practical Handbook for Undergraduate Researchers in Engineering and Applied Sciences allows readers to utilize the provided templates and guides almost immediately. In today’s world, data is ubiquitous and AI is growing exponentially. Practicing ethical data management is, therefore, crucial. Ensuring that data is findable, accessible, interoperable, and reusable is essential. This book is an interdisciplinary effort aimed at embedding ethical data life-cycle management education into undergraduate research. The authors present a Data Steward Framework, which serves as a guide for undergraduate researchers, the graduate students who mentor them, postdocs, …

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An Intelligent Sdn-Enabled Framework For Real-Time Ipv6 Ip Spoofing Detection And Prevention, Navaneethan C. Arjuman, Ahmad Fikri Sharudin, Zar Chi Hlaing, Supriyanto Praptodiyono Oct 2026

An Intelligent Sdn-Enabled Framework For Real-Time Ipv6 Ip Spoofing Detection And Prevention, Navaneethan C. Arjuman, Ahmad Fikri Sharudin, Zar Chi Hlaing, Supriyanto Praptodiyono

Journal of Informatics and Web Engineering

With the increase in the adoption of Internet Protocol version 6 (IPv6), the issue of Internet Protocol (IP) spoofing has remained a significant risk that damages the integrity of networks. Although some countermeasures, like Secure Neighbor Discovery (SEND) and Router Advertisement (RA) Guard, are available, these solutions are complex to deploy, consume high resources, and can be bypassed by advanced attacks. This paper provides a critical review of the available IPv6 spoofing prevention methods and proposes an enhanced multi-layered framework that uses improved ingress and egress filtering, Artificial Intelligence (AI)-based anomaly detection, and Software-Defined Networking (SDN) to automatically mitigate threats …

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Mask-Resilient Multi-Biometric Authentication For Healthcare, Caleb Yeo, Siew-Chin Chong, Kian-Ming Lim, Lee-Ying Chong Oct 2026

Mask-Resilient Multi-Biometric Authentication For Healthcare, Caleb Yeo, Siew-Chin Chong, Kian-Ming Lim, Lee-Ying Chong

Journal of Informatics and Web Engineering

The fast integration of digital healthcare platforms, including telemedicine and electronic health records, has created a significant need for secure, contactless authentication methods. Traditional login methods such as passwords and PINs are increasingly insufficient for ensuring the security of sensitive patient data. This paper presents a robust, lightweight Healthcare Authentication System that five biometric modules to address major challenges in facial recognition: spoofing attacks, liveness detection, and facial occlusion due to mask-wearing. The system leverages RetinaFace for face detection, a MobileNetV2 model for mask classification, a lightweight CNN for blink-based liveness verification, and MiniFASNet for spoof detection. For identity matching, …

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