Computer Sciences Commons^™

Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng

Journal of System Simulation

Abstract: The advancement of artificial intelligence technology has significantly enhanced the utilization of mobile robots in various fields such as industry, aerospace, and agriculture. The autonomous obstacle avoidance capability of these robots is crucial to the safety and efficiency of their operations in diverse settings. Path planning, a key technology in obstacle avoidance, plays an essential role in the overall performance of these systems. This paper presents a comprehensive review of path planning technology for mobile robots, categorizing the algorithms into global planning and local obstacle avoidance according to their operational requirements. Specific focus is given to the global planning …

Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai

Journal of System Simulation

Abstract: Given the need for intelligent emergency control and management of airport crowds, a smart control scheme for airport crowds based on digital twin is proposed. The scheme constructs an integrated crowd control system framework with four dimensions, including digital layer, modeling layer, functional layer, and application layer. It discusses and demonstrates the application effect of five important application modules. By using a data-driven crowd simulation model and intelligent optimization algorithm, the proposed scheme realizes the dynamic prediction and control optimization of the airport crowd status. The scheme can effectively improve the efficiency and intelligence level of airport crowd control …

Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang

Journal of System Simulation

Abstract: The rapid development of the drone industry has promoted the opening of low-altitude, forming a wave of ultra-low-altitude air transportation in cities sweeping over the world. However, the existing trajectory planning algorithms do not consider the division method and operating rules of the ultra-low-altitude airspace. They are not suitable for the collaborative trajectory planning of multiple UAVs in the urban ultra-low-altitude air transportation scenario, which may restrict the development of the ultra-low-altitude air transportation industry. This paper explores a multi-UAV collaborative trajectory planning method for urban ultra-low-altitude air transportation scenario based on the airspace flight altitude layer architecture. Specifically, …

Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang

Journal of System Simulation

Abstract: A multi-view depth estimation algorithm based on adaptive space feature enhancement (ASFE) is presented to improve the multi-view depth estimation accuracy. A multi-scale feature extraction module composed of an improved feature pyramid network (FPN) and ASFE is designed. This module obtains multi-scale feature maps with global context-aware information and coordinate information. The residual learning network is used to optimize the depth map to prevent the problem of blurred reconstructed edges in multiple convolution operations. The proposed algorithm constructs a focal loss function through the idea of classification to enhance the prediction ability of the network model. The experimental results …

Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin

Journal of System Simulation

Abstract: To solve the problem of poor real-time and accuracy of process manufacturing monitoring, this paper proposes a visual monitoring system architecture of digital twin workshop based on production factor data, production process, and multi-process equipment entity object amid the rapid development of digital twin technology and increasingly close integration with the manufacturing industry. Twin modeling is conducted on multi-process coupling production line entity objects from multiple dimensions such as element, state, and operation logic. Based on key technologies of data collection and transmission of OPC UA (OLE for process control unified archiecture) unified architecture and real-time drive of the …

Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang

Journal of System Simulation

Abstract: For the characteristics of multi-variety, large-scale and mixed-flow production of reentrant manufacturing systems, the reentrant hybrid flow shop scheduling problem with batch processors (BPRHFSP) is constructed, and an improved multi-objective mayfly algorithm (MOMA) is proposed for BPRHFSP. Firstly, decoding rules for single-piece processing stage and batch-processing stage are proposed. Then, a reverse learning initialization strategy based on logistic chaotic mapping is designed to improve the quality of the initial solution of the algorithm, also an improved mayfly mating strategy is designed to improve the local search ability of MOMA. Finally, a VND-based mayfly movement strategy is designed based on …

Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang

Journal of System Simulation

Abstract: High density of population leads to high possibility of cross-infection. It is necessary to focus on campus epidemic prevention and control. Basing on existing studies in macroscopic or microscopic view, this paper proposed a multi-scale means to analyze a short-term evolution of Corona virus disease 2019 (COVID-19) on campus and estimated the efficiency of prevention strategies. Macroscopic model was based on the susceptible-exposed-infections-recovered(SEIR) model, which exported the time curve of the number of asymptomatic patients and symptomatic patients. Microscopic model combined discrete event simulation modeling and agent-based modeling to simulate the behavior of campus students and the state evolution …

Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu

Journal of System Simulation

Abstract: The traditional ant colony algorithm has many problems in convergence and diversity when solving the traveling salesman problem (TSP). Therefore, this paper proposes a heterogeneous multi-ant colony algorithm that combines the competitive interaction strategy and the eliminating-reconstructing mechanism (CEACO) to overcome these shortcomings. Firstly, the algorithm uses a competitive interaction strategy, which adjusts the interaction period adaptively according to the Hamming distance of different groups in different periods. Competition coefficients are adopted to differentiate matching interaction objects for interaction. The matched objects interact with each other through the optimal solution and pheromone matrix. This mechanism achieves a balance between …

Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong

Journal of System Simulation

Abstract: Due to the strong nonlinearity, multi-stage coupling, and the small number of labeled samples in complex industrial processes, it is difficult for traditional global soft sensor models to accurately describe the whole process. Therefore, a multi-model soft sensor modeling method under the helptraining strategy is proposed. This method uses a fuzzy C-means (FMC) clustering algorithm to mine similar samples in the sample set and build several sub-models. By introducing the help-training strategy, a collaborative training framework based on main and auxiliary learners is formed, and a confidence evaluation mechanism is designed to eliminate error samples and expand the modeling …

Bioprocess Engineering And Intelligent Biomanufacturing, Guan Wang, Yingping Zhuang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the era of rapid development of synthetic biology, biomanufacturing, as a bridge between life sciences and engineering technologies, is gradually demonstrating its extraordinary potential to reshape industrial landscapes. However, challenges such as production efficiency, cost control, and process monitoring still hinder the smooth transition from laboratory innovations to industrial-scale implementation. Intelligent biomanufacturing has emerged as a new form of productive force, offering innovative solutions to these problems. This study reviews the latest advances in bioprocess engineering and intelligent biomanufacturing, focusing on three key technological systems: intelligent sensing, intelligent analysis, and intelligent control. Intelligent sensing technology acts as the “eyes” …

Artificial Intelligence Driven Information Technology System Restructuring And Reconstruction—Review Of Information Science & Technology In China: A Roadmap To 2050, Xuehai Hong

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Information Science & Technology in China: A Roadmap to 2050 and Information Technology: Accelerating the Integration of Human Machine Things have predicted the long-term development of China’s information technology field. This study reviews the development and changes in the field of information technology in the past 15 years, and compares them with the initial predictions, pointing out that some important judgments made at the beginning were in line with expectations. In recent years, the global development of information technology has entered a slow period, while the rapid evolution of the new generation of artificial intelligence will bring new opportunities …

Ai Helps To Establish A New Paradigm For Scientific Research, Weinan E

Bulletin of Chinese Academy of Sciences (Chinese Version)

The main purpose of scientific research is to discover fundamental principles and solve practical problems. Although tremendous progress has been made on both fronts, the lack of effective tools and efficient organizational structure still stands as the main bottleneck for scientific progress. The rapid development of artificial intelligence (AI) offers a new possibility. In recent years, deep learning has had an impressive performance, both in helping to solve fundamental scientific problems and in improving the effectiveness of scientific research tools. A new set of infrastructure is emerging, leading us to a new paradigm, the“Android paradigm”, for doing scientific research.

Computing System For Simulation Intelligence, Guangming Tan, Weile Jia, Zhan Wang, Guojun Yuan, En Shao, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study refers computer simulation in scientific research to as scientific simulation. Based on its narrow and broad definitions, this study divides scientific simulation into three stages: numerical computation, simulation intelligence, and science brain. Now, scientific simulation is entering the era of simulation intelligence, i. e., driven by scientific big data and artificial intelligence technology, scientific simulation is shifting from traditional numerical simulation to simulation integrated with artificial intelligence. In order to understand what the right computing system for simulation intelligence is, the design guidelines, basic methods, and key technical problems are discussed.

Digital Scientists And Parallel Sciences: The Origin And Goal Of Ai For Science And Science For Ai, Feiyue Wang, Yutong Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Based on recent development in foundation model, parallel intelligence, decentralized science (DeSci), and other artificial intelligence (AI) technologies, from AI for Science (AI4S) to Science for AI (S4AI), this study discusses parallel sciences and digital scientists, and their impact and significance in paradigm shift for research and development as well as Industry 5.0 and intelligent industry, which demonstrate that paradigm shift is emerging and accelerating, and we must be prepared.

Ai For Technology: Applied Practices And Future Perspectives Of Technological Intelligence In High Tech Areas, Yunji Chen, Qi Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the core of the fifth research paradigm, AI for Science has been widely used in multiple research fields of natural sciences and high technologies. In contrast to that the application of AI in natural sciences mainly focuses on discovering new theories, principles, and laws, the application of AI in high technologies mainly focuses on creating new plans, tools, and products, in order to resolve concrete problems in related fields. This study first summarizes the typical characteristics and scientific problems of the application of AI in high technologies, i.e., AI for Technology, and then introduces a successful case study of …

Large Model-Driven, Human-Computer Collaborative Robotic Ai-Chemist Cloud Facility, Yuanyuan Chong, Shuo Feng, Song Wang, Jun Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

At present, chemical science is facing unprecedented opportunities and challenges due to the technological changes brought by artificial intelligence. In order to promote the paradigm shift in chemical research, this study proposes the construction plan of the robotic AI-chemist cloud facility. This system realizes a new paradigm of scientific research by collecting multi-channel data to build a database, developing large scientific models enhanced by chemical knowledge, constructing clusters of robotic facilities, and building an intelligent management decision system, which will dramatically improve the efficiency of scientific research and solve scientific problems in terminal applications. This infrastructure is expected to change …

A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of biotechnology and information technology has brought life sciences into a new era of data explosion. The traditional life science research paradigm struggles to reveal the fundamental rules of complex biological systems from rapidly growing biological big data. As artificial intelligence continues to achieve disruptive breakthroughs in life science, a new paradigm driven by AI is emerging. This study delves into typical examples of life science research driven by AI, proposes the concept and key elements of the new life science research paradigm, elaborates on the cutting-edge of life science research under this new paradigm, and discusses …

Ai For Science: Ai Enabled Scientific Facility Transforms Fundamental Research, Xiaokang Yang, Yanyan Xu, Lu Chen, Yunbo Wang, Yue Gao, Jidong Tian, Kai Yu, Yaohui Jin, Hong Mei

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, artificial intelligence (AI) has achieved numerous disruptive breakthroughs in frontier scientific and technological fields, such as AlphaFold2 for protein structure prediction, intelligent control of nuclear fusion, and drug design for COVID-19. These achievements indicate that AI for Science is becoming a new paradigm in research. To achieve fundamental scientific innovation and major technological breakthroughs in the era of intelligence, two core issues should be addressed: 1) how to harness the generality and creativity of the new-generation of AI, especially generative AI and large language models (LLMs), to promote the formation of new paradigms; 2) how to empower …

Strategic Research On Information Technology Promoting National Governance Modernization—Review On The S70th Xiangshan Science Conferences, Chao Zhang, Weiyu Duan, Kaihua Chen, Xiaoguang Yang, Yuntao Long

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study systematically summarizes the reports and speeches of the S70th Xiangshan Science Conferences on the theme of “Strategic Research on Information Technology Promoting the National Governance Modernization” and summarizes the consensus of the conference in the following three aspects. (1) Important progress and achievements have been made in the four typical areas, i.e., smart justice, internet governance, data governance, and emergency management. (2) Using information technology to promote the modernization of national governance is confronted with unprecedented opportunities and challenges. And (3) it is necessary to take a series of effective measures to promote information technology to facilitate the …

Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang

Journal of System Simulation

Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …

A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong

Journal of System Simulation

Abstract: Existing simulation methods for aircraft type identification mainly focus on a single sensor and a single target. They do not consider the joint acquisition of aircraft parameters by various sensor devices such as optoelectronics, radar, and electronic detection in real scenarios, leading to the simple simulation scenarios. This paper proposes a simulation platform based on multi-source sensors. Specifically, the platform includes an infrared image simulator that uses a cycleGAN network to generate infrared images of the aircraft, a flight simulator that adopts the three-degree-of-freedom flight control method to generate the movement trajectory of the aircraft, a radar simulator, that …

Genome-Wide Profiling Of Novel Conserved Zea Mays Micrornas Along With Their Key Biological, Molecular And Cellular Targets And Validation Using An Rt-Pcr Platform, Abdul Baqi, Sami Ullah, Muhammad Ayub, Muhammad Zafar Saleem, Ghulam Mustafa Khan, Asad Ullah

Karbala International Journal of Modern Science

MicroRNAs (miRNAs), which are typically non-coding RNAs that start off as endogenous molecules and regulate post-transcriptional levels of gene expression by mRNA degradation or translational repression. They are 18–26 nucleotides long, evolutionarily conserved and essential for predicting novel miRNAs in a variety of plants. Maize (Zea mays) is a significant food and forage crop in the globe today. In the present study, many maize miRNAs have been found to be associated with both plant development and responses to stress. In this study, 66 unique conserved maize miRNAs from 65 different miRNA families were predicted using several genomics-based methods …

The Role Of Cu (0-0.03) And Zn (0.02) Substitution On The Structural, Optical And Magnetic Properties Of Mgo Nanoparticles, S. Naseem Shah, Atif Dawar, Yasmeen Bibi, Abid Ali, M. Asif Siddiqui

Karbala International Journal of Modern Science

The co-precipitation method was employed to prepared Cu (0-0.03) and Zn (0.02) dual doped MgO nanoparticles. The secondary phases of CuO and Cu₂O were observed along with the cubical phase of MgO. The doping induced effect was noticed for the crystallite size variations (14.39-19.89 nm). The morphological transformation from spherical to rice-like shape were observed. The estimated values of optical bandgap (4.66-4.45 eV) were well correlated with the crystallite size and dopant concentrations. The ferromagnetic ordering was observed at room temperature and the enchantment in the coercivity (142.27 Oe) with Zn (0.02) doping was noticed. Such type of …

Semi-Decentralized Inference In Heterogeneous Graph Neural Networks For Traffic Demand Forecasting: An Edge-Computing Approach, Mahmoud Nazzal, Abdallah Khreishah, Joyoung Lee, Shaahin Angizi, Ala Al-Fuqaha, Mohsen Guizani

Machine Learning Faculty Publications

Prediction of taxi service demand and supply is essential for improving customer experience and provider's profit. Recently, graph neural networks (GNNs), modeling city areas as nodes in a transportation graph, have been shown efficient for this application as they utilize both local node features and the graph structure in the prediction. Still, further improvement can be achieved by either simultaneously exploiting different types of nodes/edges in the graphs or enlarging the scale of the transportation graph. However, both alternatives are challenged by the scalability of GNNs. An immediate remedy to the scalability challenge is to decentralize the GNN operation. In …

Locally Tight Programs, Jorge Fandinno, Vladimir Lifschitz, Nathan Temple

Computer Science Faculty Publications

Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis of answer set programming. We show that the tightness condition in this theorem can be replaced by a less restrictive “local tightness” requirement. From this fact we conclude that the proof assistant ANTHEM-P2P can be used to verify equivalence between locally tight …

Locally Tight Programs, Jorge Fandinno, Vladimir Lifschitz, Nathan Temple

Computer Science Faculty Publications

Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis of answer set programming. We show that the tightness condition in this theorem can be replaced by a less restrictive “local tightness” requirement. From this fact we conclude that the proof assistant ANTHEM-P2P can be used to verify equivalence between locally tight …

Ai-Enhanced Detection Of Clinically Relevant Structural And Functional Anomalies In Mri: Traversing The Landscape Of Conventional To Explainable Approaches, Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri

Publications and Research

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of …

Determining Critical Nodes In Optimal Cost Attacks On Networked Infrastructures, Ishfaq Ahmad, Addison Clark, Muhammad Ali, Hansheng Lei, David Ferris, Alex Aved

Informatics and Engineering Systems Faculty Publications

A wide range of critical infrastructures are connected via wide area networks as well as the Internet-of-Thing (IoT). Apart from natural disasters, these infrastructures, providing services such as electricity, water, gas, and Internet, are vulnerable to terrorist attacks. Clearly, damages to these infrastructures can have dire consequences on economics, health services, security and safety, and various business sectors. An infrastructure network can be represented as a directed graph in which nodes and edges denote operation entities and dependencies between entities, respectively. A knowledgeable attacker who plans to harm the system would aim to use the minimum amount of effort, cost, …

Enabling The Clinical Application Of Artificial Intelligence In Genomics: A Perspective Of The Amia Genomics And Translational Bioinformatics Workgroup, Nephi A Walton, Radha Nagarajan, Chen Wang, Murat Sincan, Robert R Freimuth, David B Everman, Derek C Walton, Scott P Mcgrath, Dominick J Lemas, Panayiotis V Benos, Alexander V Alekseyenko, Qianqian Song, Ece Gamsiz Uzun, Casey Overby Taylor, Alper Uzun, Thomas Nate Person, Nadav Rappoport, Zhongming Zhao, Marc S Williams

Faculty, Staff and Student Publications

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space.

PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members.

CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of …

Neutrosophic Statistical Analysis Of Temperatures Of Cities In The Southeastern Anatolia Region Of Turkey, Hacer Şengül Kandemir, Nazlım Deniz Aral, Murat Karakaş, Mikail Et

Neutrosophic Systems with Applications

In the paper, neutrosophic statistical analysis of temperature data of different cities in the southeastern Anatolia region of Turkey is given. The neutrosophic mean and neutrosophic coefficient of variation are computed using the temperature data. From the analysis, it is concluded that the temperatures of Mardin and Şanlıurfa cities are more consistent than the other cities in Turkey. In addition, the neutrosophic results are compared with results under classical statistics. Based on the comparative study, it can be concluded that neutrosophic statistical results are more adequate, flexible, and more informative than classical statistics.