Computer Sciences Commons^™

A Decentralized Digital Watermarking Framework For Secure And Auditable Video Data In Smart Vehicular Networks, Xinyun Liu, Ronghua Xu, Yu Chen

Michigan Tech Publications

Thanks to the rapid advancements in Connected and Automated Vehicles (CAVs) and vehicular communication technologies, the concept of the Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) and big data promotes the vision of an Intelligent Transportation System (ITS). An ITS is critical in enhancing road safety, traffic efficiency, and the overall driving experience by enabling a comprehensive data exchange platform. However, the open and dynamic nature of IoV networks brings significant performance and security challenges to IoV data acquisition, storage, and usage. To comprehensively tackle these challenges, this paper proposes a Decentralized Digital Watermarking framework for smart Vehicular …

What Do We Know About Hugging Face? A Systematic Literature Review And Quantitative Validation Of Qualitative Claims, Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Background: Collaborative Software Package Registries (SPRs) are an integral part of the software supply chain. Much engineering work synthesizes SPR package into applications. Prior research has examined SPRs for traditional software, such as NPM (JavaScript) and PyPI (Python). Pre-Trained Model (PTM) Registries are an emerging class of SPR of increasing importance, because they support the deep learning supply chain.
Aims: Recent empirical research has examined PTM registries in ways such as vulnerabilities, reuse processes, and evolution. However, no existing research synthesizes them to provide a systematic understanding of the current knowledge. Some of the existing research includes qualitative …

Interpreting The Biological Effects Of Protons As A Function Of Physical Quantity: Linear Energy Transfer Or Microdosimetric Lineal Energy Spectrum?, Fada Guan, Lawrence Bronk, Matthew Kerr, Yuting Li, Leslie A Braby, Mary Sobieski, Xiaochun Wang, Xiaodong Zhang, Clifford Stephan, David R Grosshans, Radhe Mohan

Faculty, Staff and Student Publications

The choice of appropriate physical quantities to characterize the biological effects of ionizing radiation has evolved over time coupled with advances in scientific understanding. The basic hypothesis in radiation dosimetry is that the energy deposited by ionizing radiation initiates all the consequences of exposure in a biological sample (e.g., DNA damage, reproductive cell death). Physical quantities defined to characterize energy deposition have included dose, a measure of the mean energy imparted per unit mass of the target, and linear energy transfer (LET), a measure of the mean energy deposition per unit distance that charged particles traverse in a medium. The …

Gas Chromatography-Mass Spectrometry (Gc-Ms), Computational Analysis, And In Vitro Effect Of Essential Oils From Two Aromatic Plants, Bubonium Graveolens And Launaea Arborescens Growing In Southwest Algeria Against Potato Cyst Nematodes, Souad Ziane, Chaouki Selles, Khaldun M. Al Azzam, Bounoua Nadia, Belal O. Al-Najjar, Ali Al-Samydai, Obada A. Sibai, El-Sayed Negim

Karbala International Journal of Modern Science

The study tested the nematicidal effects of essential oils from Bubonium graveolens and Launaea arborescens on the potato cyst nematode Globodera rostochiens. The chemical composition of the essential oils was analyzed using GC-MS. To determine the concentration that killed 50% of the nematode population (LC50), five concentrations of the essential oils were applied to the tested organisms. The effects of essential oils on the hatching of cyst nematode (Globodera rostochiensis sp.) eggs in vitro demonstrated a wide variety of effects ranging from no impact to mild, moderate, and strong effects, which increased dramatically with exposure duration and concentration. All the …

Broken Su(3) Description Of Energy Levels And Decay Properties In Gadolinium Isotopes (A=156-160), Fahmi Sh. Radhi, Amir Abdul Ameer Mohammed Ali Dr., Ali H. Al-Musawi

Karbala International Journal of Modern Science

This study presents an in-depth examination of the energy levels and decay properties of Gadolinium (Gd) isotopes with mass numbers (A=156-160), utilizing the Interacting Boson Model-1 (IBM-1) within a broken SU(3) symmetry framework. Through this approach, we systematically calculated and analyzed the energy spectra, B(E2) transition probabilities, quadrupole moments, and potential energy surface (PES) which provided valuable insights into the shape and collective behavior of nuclei, as well as the decay properties of the selected Gd isotopes. The broken SU(3) symmetries provide a good description to the isotopes under study. This comprehensive analysis enhances the understanding of the nuclear structure …

Skin Microbiome: Current Target For Cosmeceuticals, Priyanka Kakkar, Neeraj Wadhwa

Karbala International Journal of Modern Science

Skin acts as a barrier to the external environment and perform various functions like maintaining internal homeostasis, sensations to touch based stimuli, vitamin D production and defence against foreign pathogens, prevent dehydration. Skin has its own diverse microbiota like bacteria, virus, fungi that is collectively called as skin microbiome. Skin microbiome balance is disturbed (condition called dysbiosis) by both internal and external factors which lead to skin problems like acne, psoriasis, dandruff. It is important to maintain the healthy skin ecosystem. Cosmeceuticals i.e., combination of cosmetic and pharmaceuticals, is a recent trend in the skin care industry where we add …

Next-Generation Block Ciphers: Achieving Superior Memory Efficiency And Cryptographic Robustness For Iot Devices, Saadia Aziz, Ijaz Ali Shoukat, Mohsin Iftikhar, Mohsin Murtaza, Abdulmajeed M. Alenezi, Cheng-Chi Lee, Imran Taj

All Works

Traditional cryptographic methods often need complex designs that require substantial memory and battery power, rendering them unsuitable for small handheld devices. As the prevalence of these devices continues to rise, there is a pressing need to develop smart, memory-efficient cryptographic protocols that provide both high speed and robust security. Current solutions, primarily dependent on dynamic permutations, fall short in terms of encryption and decryption speeds, the cryptographic strength, and the memory efficiency. Consequently, the evolution of lightweight cryptographic algorithms incorporating randomised substitution properties is imperative to meet the stringent security demands of handheld devices effectively. In this paper, we present …

Enhancing Scenario-Oriented Technology Foresight On Information Technology For Public Governance, Kaihua Chen, Shuo Wang, Chao Zhang, Jie Yang, Xiaoguang Yang, Lei Guo, Yue Hao

Bulletin of Chinese Academy of Sciences (Chinese Version)

To effectively adapt to the reshaping of public governance concepts, models, and tools driven by the new generation of information technologies represented by artificial intelligence, it is essential to take practical application scenarios as the entry point. Implementing periodic technology foresight on public governance information technologies can promote the integrated development of governance and digital technologies. This is an urgent task for both the public governance and information technology domains. Foresight for information technologies supporting public governance must be oriented toward the demands of complex data-driven and intelligent governance scenarios. It should focus on guiding technological directions with social value, …

Key Technology Foresight And Policy Recommendation For Information Technology Enabling Smart Justice, Yirong Wu, Shuo Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Fair justice is the last line of defense for maintaining social fairness and justice, and promoting the construction of smart justice is an important means to improve the efficiency and fairness of judicial work. Currently, China’s smart judiciary is in a critical stage of upgrading its intelligence in areas such as investigation, trial, supervision, and judicial execution, empowered by information technology. The application of information technology in national governance faces order dilemmas and security risks, with the establishment of corresponding laws and regulations demonstrating noticeable lag. Designating to meet the demand of information technology supporting the construction of smart justice …

Empowering Modernization Of National Emergency Management With New Generation Of Information Technology: Technology Foresight And Policy Recommendations Based On Typical Scenarios, Haibo Zhang, Xinyu Dai, Yi Peng, Yi Liu, Xue Lin, Yongjian Zhu, Wu Chen, Zhen Wu, Xinyue Qin, Depei Qian, Jian Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the context of the new round of scientific and technological revolution, how to grasp the historical opportunity of supporting the development of the “overall safety and emergency response framework” with the NGIT, and promoting the transformation of the public safety governance to emphasis on prevention, is a pressing issue to be studied. This study focuses on five typical scenarios in emergency management, drawing on multiple rounds of expert interviews and questionnaire surveys to identify a list of critical technologies, analyze future development trends and constraints, and provide references for advancing relevant technological research and development. The study further emphasizes …

Challenges, Countermeasures, And Forward-Looking Technologies For Cyber Society Governance From System Security Perspective, Hongbin Pei, Jingxin Hai, Pinghui Wang, Xiaohong Guan

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the rapid development and widespread application of artificial intelligence and information technologies, the cyber society has evolved into a new form featuring human-machine integration, mass interaction, and intelligent interconnection. While transforming human life and production, it has also brought security risks such as cyberattacks, privacy breaches, online rumors, and information cocoons, posing serious challenges to social order. Cyber society governance has thus become a key component of national governance modernization. This study proposes the STC governance paradigm from a system security perspective, covering three key dimensions: security (cyber infrastructure security), trustworthiness (credibility of cyber entity identities), and controllability (content …

Accelerating The Development Of Ai-Driven Knowledge Innovation System, Innovation Paradigm Research Group, Chinese Academy Of Sciences

Bulletin of Chinese Academy of Sciences (Chinese Version)

The world is undergoing a paradigm shift in full-chain innovation driven by AI-powered scientific research, which will give rise to a completely new knowledge innovation system. This profound and comprehensive transformation presents a critical opportunity for China to build an independent knowledge innovation system and a major historical chance to accelerate its development into a science and technology powerhouse. The deep impact of this change stems from AI’s ability to reshape the epistemology and methodology of knowledge innovation, accelerating the iteration of scientific theories and the deep restructuring of knowledge systems. This shift is making the structure of knowledge more …

Key Technology Selection And Countermeasures To Promote Full Lifecycle Data Governance, Yuyao Feng, Hongyun Zhang, Pengfei Wang, Jianping Li, Zongben Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, the digital economy, driven by data as a critical element, has developed rapidly. Nevertheless, China’s progress in data factorization and valorization is still at a preliminary stage. The data governance system remains underdeveloped, with numerous challenges and technical issues arising in the full lifecycle governance of data, including supply, circulation, application, and security protection. Against this backdrop, this study analyzes the primary technical bottlenecks encountered during the modernization of China’s data governance framework. By employing bibliometric analysis, patent data analysis, Delphi surveys, and expert opinions, a critical technology list to support the modernization of data governance in …

Review Of Current Trends In Information Technology Concerning Phonetic Similarity”, Zaid Rajih Mohammed, Ahmed H. Aliwy

Al-Bahir

With the increasing availability of textual information in various languages via the Internet in homes and companies through Internet and intranet services, there is an urgent need for the technologies and tools necessary to process this information, phonetic representation, and voice interaction. For example voice to voice machine translation need to phonetic mapping and similarity among the languages especially for names and foreign words. This one example of the importance of phonetic mapping and similarity. This article aims to describe, in detail, the recent surge in interest and advancements in phonetic similarity (PS), phonetic representation, and phonetic mapping researches. PS …

The Evolution Of Community Engagement Strategies In The Context Of Advancements In Artificial Intelligence Technologies, Erika Grodzki, Stefanie Powers, Gary Carlin, Hung Chum Kao

Faculty and Staff Publications & Presentations

As the AI landscape continues to evolve, the need for communities to nurture, inform, and challenge these technologies becomes paramount. This panel addresses the importance of traditional and AI driven strategies in terms of community engagement. Four case studies are reviewed to show how AI technologies are being implemented in communities. While AI offers numerous benefits, it is important not to overlook the value of human interaction in building and maintaining thriving community engagement. AI cannot replicate emotional intelligence and authentic relationship building - critical components of community engagement.

Maritime Behaviour Anomaly Detection With Seasonal Context, Travis Rybicki, Martin Masek, Chiou Peng Lam

Research outputs 2022 to 2026

Monitoring maritime traffic has become an important task for ensuring the safety of vessels, as well as the goods, and persons that they may be transporting. An active area of research is the modelling of expected normal vessel behaviour so as to detect subsequent anomalies in new data. Anomalies indicate that a vessel is not behaving in an expected manner and their detection can be flagged for further investigation to identify whether the vessel needs assistance or intervention. An important factor for some vessels in determining normal behaviour is seasonal context. However, current approaches typically do not incorporate seasonality into …

Personalized Learning Path Problem Variations: Computational Complexity And Ai Approaches, Sean A. Mochocki, Mark Reith, Brett J. Borghetti, Gilbert L. Peterson, John Jasper, Laurence D. Merkle

Faculty Publications

E-learning courses often suffer from high dropout rates and low student satisfaction. One way to address this issue is to use personalized learning paths (PLPs), which are sequences of learning materials that meet the individual needs of students. However, creating PLPs is difficult and often involves combining knowledge graphs (KGs), student profiles, and learning materials. Researchers typically assume that the problem of creating PLPs belong to the nondeterministic polynomial (NP)-hard class of computational problems. However, previous research in this field has neither defined the different variations of the PLP problem nor formally established their computational complexity. Without clear definitions of …

Road Signs Detection Using Ssd Mobilenetv2, Zahraa Salah Dhaif, Nidhal K. El Abbadi

Karbala International Journal of Modern Science

One of the most critical challenges for self-driving vehicles is accurately identifying traffic signs, which are essential for self-navigation and decision-making. Systems for the detection and recognition of road signs play a crucial role in this process by providing vital information for the vehicle's decision-making. This study proposes an approach for road sign identification and recognition utilising the TensorFlow Object Detection API and the SSD MobileNet V2 FPN Lite model.

In this proposal, we combine the efficiency and accuracy of SSD with the lightweight architecture of MobileNet to achieve excellent performance in object detection benchmarks while maintaining a small model …

Artificial Intelligence And Machine Learning In Ocular Oncology, Retinoblastoma (Armor): Experience With A Multiracial Cohort, Vijitha S. Vempuluru, Rajiv Viriyala, Virinchi Ayyagari, Komal Bakal, Patanjali Bhamidipati, Krishna Krishore Dhara, Sandor R. Ferenczy, Carol L. Shields, Swathi Kaliki

Wills Eye Hospital Papers

Background: The color variation in fundus images from differences in melanin concentrations across races can affect the accuracy of artificial intelligence and machine learning (AI/ML) models. Hence, we studied the performance of our AI model (with proven efficacy in an Asian-Indian cohort) in a multiracial cohort for detecting and classifying intraocular RB (iRB). Methods: Retrospective observational study. Results: Of 210 eyes, 153 (73%) belonged to White, 37 (18%) to African American, 9 (4%) to Asian, 6 (3%) to Hispanic races, based on the U.S. Office of Management and Budget's Statistical Policy Directive No.15 and 5 (2%) had no reported race. …

Tackling Selfish Clients In Federated Learning, Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a distributed machine learning paradigm facilitating participants to collaboratively train a model without revealing their local data. However, when FL is deployed into the wild, some intelligent clients can deliberately deviate from the standard training process to make the global model inclined toward their local model, thereby prioritizing their local data distribution. We refer to this novel category of misbehaving clients as selfish. in this paper, we propose a Robust aggregation strategy for the FL server to mitigate the effect of Selfishness (in short RFL-Self). RFL-Self incorporates an innovative method to recover (or estimate) the true …

Enhanced Lithological Mapping In Arid Crystalline Regions Using Explainable Ai And Multi-Spectral Remote Sensing Data, Hesham Morgan, Ali Elgendy, Amir Said, Mostafa Hashem, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Lithological classification is essential for understanding the spatial distribution of rocks, especially in arid crystalline areas. Artificial intelligence (AI) recent advancements with multi-spectral satellite imagery have been utilized to enhance lithological mapping in these areas. Here we employed different AI models namely, Support Vector Machine (SVM), Random Forest Classification (RFC), Logistic Regression, XGBoost, and K-nearest neighbors (KNN) for lithological mapping. This was followed by the application of explainable AI (XAI) for lithological discrimination (LD) which is still not widely explored. Based on the highest accuracy and F1 score of the previously mentioned models, RFC model outperformed all of them, and …

Tradeoffs Of Generalization, Kyra M. Abrams, Peter T. Darch

I-GUIDE Forum

Models used in geospatial data science are often built and optimized for a specific local context, such as a particular location at a point in time. However, upon publication, these models may be generalized beyond this context, reused in research simulating or predicting other times and places. Without sufficient information or documentation, bias embedded in these models can in turn result in bias in the reuser’s research outputs. Drawing on a long-term qualitative case study of aging dams researchers and developers of models used by these researchers, we find significant documentation gaps. We combine a literature-based genealogy with interviews with …

An Introduction To The Time-Independent Schrödinger Equation And Methods To Solve It, Vu Giang, Alex Gnech

OUR Journal: ODU Undergraduate Research Journal

The Time-Independent Schrödinger Equation is a linear elliptic PDE that describes quantum-mechanical systems. Its significance in the science of submicroscopic phenomena, particularly quantum mechanics, is as central as Newton’s laws of motion are to classical mechanics. This study uses various methods, including novel neural networks and finite difference schemes, to solve the one-dimensional two-body equation.

A Plugin-Based Unreal Engine Adapter For Hla-Based Distributed Simulation, Mei Yang, Peng Wang

Journal of System Simulation

Abstract: With the wide application of game engine-based simulation in transportation, military and other fields, the demand for interoperability between game engine and traditional simulations is becoming increasingly strong. For the HLA-based integration of Unreal Engine and the traditional simulations, a plugin-based Unreal Engine adapter for distributed simulation is designed, which enables the rapid development of Unreal Engine federate and the efficient integration. The simulation shows the feasibility of the plugin-based Unreal Engine adapter.

Research On Sequential Design Methods For Satellite Combat Simulation Tests, Yanlin Wang, Zhijun Cheng, Zichen Wang, Jian Zhong

Journal of System Simulation

Abstract: Aiming at the problem that satellite monitoring mission simulation tests cannot take into account the number of sample points and model accuracy in the complex test space, a hybrid sequential test design method for satellite simulation tests based on sample density and local nonlinearity is proposed. Voronoi division is used to describe the density of discrete point distribution, and the nonlinearity is measured with the help of Taylor expansion and sample point neighborhood gradient information. The two are combined to calculate the hybrid metrics, and the sample points are ranked and new ones are added until the stopping criterion …

Improving Nsga-Iii Algorithm For Solving High-Dimensional Many-Objective Green Flexible Job Shop Scheduling Problem, Yigang Xu, Yong Chen, Chen Wang, Yunxian Peng

Journal of System Simulation

Abstract: Aiming at the poor initial solution quality and low local search efficiency of NSGA-III in solving the many-objective flexible job shop scheduling model, an improved NSGA-III (NSGA-III-TV) is proposed. Based on MSOS encoding, the different mixed initialization strategies are adopted for OS and MS chromosomes to improve the quality of initial solutions. Based on the critical path, an improved N6 neighborhood structure is used for neighborhood search, which effectively reduce the completion time and reducing search randomness. Three effective mutation operators are employed to expand the search space and improve the convergence capability in the later stages. Test results …

Multi-Objective Energy-Efficient No-Wait Flow Shop Scheduling Based On Hybrid Discrete State Transition Algorithm, Cong Wang, Jiaying Yu, Hongli Zhang

Journal of System Simulation

Abstract: A hybrid discrete state transition algorithm (HDSTA) is designed to solve the energyefficient no-wait flow shop scheduling problem (EENWFSP) minimizing makespan and total energy consumption. According to the characteristics of the problem, the coding method of job sequence and speed matrix is designed, and the heuristic algorithm is used to obtain the high-quality initial solution. According to the properties of EENWFSP, solving and allocating four discrete operators. The swap, shift and symmetry operators are embedded in secondary state transition are used for job sequence optimization, and the substitute operators are used for machine speed optimization. The speed substitute strategy …

Adaptive Recognition Method Of Capability Boundary Parameters For Unmanned Autonomous Systems, Jinwen Li, Peng Wang, Youmei Pan, Xinyao Hui

Journal of System Simulation

Abstract: To effectively cope with the dimension curse in simulation testing and reduce the number of simulations times needed in the traditional full-space parameter traversal, it is necessary to obtain specific simulation data to accurately reflect the modeling characteristics of the test data to obtain the informative and representative samples of the original data with a smaller number of simulations. A digital simulation test model for adaptive recognition ;/of capability boundary parameters for UAS is proposed. The model is initially constructed with a good point set with a multi-weight structure; In combination with an adaptive kernel function boundary point recognition, …

Operational Effectiveness Analysis Method Based On Spherical Fibonacci Lattice, Weiran Guo, Jiahao Zhou, Xiang Huang, Xin Zhao

Journal of System Simulation

Abstract: An operational effectiveness modeling and computing method based on spherical Fibonacci lattice is proposed to address the low simulation accuracy and computational efficiency of large-scale sampling for traditional latitude and longitude grids. The formal description of operational effectiveness in command information systems and the generation method of spherical Fibonacci grid points are provided. A command information systems capability analysis framework is constructed, which focuses on ensuring the continuous mission support and uses the responsibility area of combat tasks as a reference. Through a top-down system design approach, a layered and decoupled combat effectiveness computing framework is proposed which studies …

Ground Robot Relocation Method Based On Uav Point Cloud Map, Hongzhi Huang, Kai Yan, Changfeng Liu, Jianwen Wang, Bin Luo

Journal of System Simulation

Abstract: In response to the challenge of relocalization in air-ground collaborative systems without the support of Global Navigation Satellite System (GNSS), and the associated issues of insufficient accuracy, a coarse-to-fine relocalization algorithm based on a three-dimensional point cloud map is proposed. The algorithm eliminates the influence of invalid point clouds from the sky and ground through index filtering, performs coarse localization by extracting global features from the point cloud and applying truncated least squares estimation, and then employs voxel-based iterative closest point (ICP) for precise optimization to obtain the more accurate localization results. A ground robot localization and autonomous navigation …