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Democratization Of Custom, High Quality Large Language Models, Pablo Lopez 2024 DePaul University

Democratization Of Custom, High Quality Large Language Models, Pablo Lopez

College of Computing and Digital Media Dissertations

Large Language Models (LLMs) have shown exceptional performance in several natural language processing (NLP) tasks. Customizing LLMs boosts their performance in domain specific tasks but typically requires substantial resources and effort for training, such as supervised fine-tuning. This research proposes methods to achieve significant accuracy improvements given minimal resources, particularly focusing on open-ended question answering with a given piece of context. We utilize an LLM’s self-generated training data to fine-tune the LLM and partial fine-tuning with on-demand GPU to reduce practitioner training costs. The research shows that these methods give significant performance gains in a Retrieval Augmented Generation (RAG) based …


The Impact Of Model Variations On The Robustness Of Deep Learning Models In Adversarial Settings, Firuz Juraev, Mohammed Abuhamad, Simon S. Woo, George K. Thiruvathukal, Tamer Abuhmed 2024 Sungkyunkwan University

The Impact Of Model Variations On The Robustness Of Deep Learning Models In Adversarial Settings, Firuz Juraev, Mohammed Abuhamad, Simon S. Woo, George K. Thiruvathukal, Tamer Abuhmed

Computer Science: Faculty Publications and Other Works

Rapid advancements of deep learning are accelerating adoption in a wide variety of applications, including safety-critical applications such as self-driving vehicles, drones, robots, and surveillance systems. These advancements include applying variations of sophisticated techniques that improve the performance of models. However, such models are not immune to adversarial manipulations, which can cause the system to misbehave and remain unnoticed by experts. The frequency of modifications to existing deep learning models necessitates thorough analysis to determine the impact on models’ robustness. In this work, we present an experimental evaluation of the effects of model modifications on deep learning model robustness using …


Ai-Driven Innovation And Development In Manufacturing: An Overview Of Trends, Issues, And Suggestions, Rongping MU, Jingjing GUO, Yuchen LI, Qiang LI, Chun JIANG, Ze FENG, Guowei DONG 2024 Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China

Ai-Driven Innovation And Development In Manufacturing: An Overview Of Trends, Issues, And Suggestions, Rongping Mu, Jingjing Guo, Yuchen Li, Qiang Li, Chun Jiang, Ze Feng, Guowei Dong

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence technology has become a key force in driving innovation and development in global manufacturing industries, and its application in production automation, intelligent management, and other areas has become an important trend for innovation and development of manufacturing in all countries. This study comprehensively analyzes the innovation and development trend driven by artificial intelligence in global manufacturing, outlines the policies and measures of major countries in promoting the innovation and development of the manufacturing industries driven by artificial intelligence. It also points out the current situation and problems of the manufacturing’s innovation and development driven by artificial intelligence in …


Insights From Darpa’S Program Funding Layout In Artificial Intelligence, Zheng SU, Ning HE, Qi HAN, Qi ZHANG, Xiaocheng JIANG 2024 Industry and Information Technology (Beijing) Industrial Development Research Institute Co., Beijing 100036, China; Industry Development and Promotion Center, Ministry of Industry and Information Technology of People’s Republic of China, Beijing 100036, China

Insights From Darpa’S Program Funding Layout In Artificial Intelligence, Zheng Su, Ning He, Qi Han, Qi Zhang, Xiaocheng Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence, as a disruptor in the new wave of technological revolution and industrial transformation, had already become a focal point of strategic planning for the U.S. Defense Advanced Research Projects Agency (DARPA) as early as the 1960s. To explore the patterns of DARPA’s project funding allocation in the field of artificial intelligence, this study conducts an in-depth analysis of the agency’s budget reports from fiscal years from 2015 to 2025. The study identifies the following characteristics of DARPA’s project funding framework in the field of artificial intelligence: (1) distinctive application orientation; (2) highly flexible funding system; and (3) close …


Developing Green Design, Leading Green And Low-Carbon Society, Yongxiang LU 2024 Chinese Academy of Sciences, Beijing 100864, China

Developing Green Design, Leading Green And Low-Carbon Society, Yongxiang Lu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Green design refers to a design principle and method that comprehensively considers energy and resource conservation, emission reduction, and environmental impact during the product manufacturing and operation process in the product design stage. It strives to reduce greenhouse gas emissions throughout the entire product lifecycle. In the era of information networks, green design is supported by big data, AI network collaborative design, network detection and monitoring, etc. It involves selecting energy-saving processes, green and low-carbon materials, and optimizing product geometry design and surface treatment to achieve efficient resource utilization and minimize waste. For example, selecting environmentally friendly materials through networked …


Challenges And Recommendations For Building Open Source Innovation Ecosystem For Large-Models In China, Xin WEN, Chao ZHANG, Rui GUO, Kaihua CHEN, Ze FENG, Qigang ZHU 2024 Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China

Challenges And Recommendations For Building Open Source Innovation Ecosystem For Large-Models In China, Xin Wen, Chao Zhang, Rui Guo, Kaihua Chen, Ze Feng, Qigang Zhu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Addressing the current technological development issues that constrain the development of China’s large-scale model industry is needed to promote the continuous prosperity and development of the industry and enhance its international competitiveness. The study analyzes the significance of the open-source innovation ecosystem for the development of large-scale models in China. Based on reviewing the international experience of constructing the open-source innovation ecosystem, it further dissects the problems and challenges faced by the construction of the open-source innovation ecosystem for large-scale models in China and puts forward targeted suggestions. The study finds that the open-source innovation ecosystem for large-scale models in …


Research And Practice Of Digital Institute And Its System Framework, Jianjun YU, Yue WANG, Kongmin WANG, Zhuomin SHI 2024 Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China

Research And Practice Of Digital Institute And Its System Framework, Jianjun Yu, Yue Wang, Kongmin Wang, Zhuomin Shi

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the era of the digital economy, digital scientific research and digital government are both crucial components, serving as application scenarios enabled by new information technologies. Currently, the new generation of information technologies, especially artificial intelligence and big data, is instrumental in modernizing governance at scientific research institutions within Chinese Academy of Sciences (CAS). They notably drive paradigm shifts in scientific activities and accelerate the digital transformation of these institutions. The digital system formed by the digital transformation of management processes in scientific activities at research institutes is defined as the digital institute. This study analyzes the impact of digital …


Research And Implications Of The Us Clean Energy Strategy, Lanchun LI, Qing LIU, Wei CHEN, Yun TANG, Jun CHEN 2024 Wuhan Library, Chinese Academy of Sciences, Wuhan 430071, China; Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China

Research And Implications Of The Us Clean Energy Strategy, Lanchun Li, Qing Liu, Wei Chen, Yun Tang, Jun Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the world enters a new period of carbon neutrality, the US government is actively building a clean energy innovation ecosystem through both internal and external measures. Systematically tracking and in-depth analysis of the intent, structure, approach, and other characteristics of the new phase of the US clean energy strategy is of practical significance to Chinese energy revolution. The US focuses on the strategic objectives of science and technology innovation, energy security, and infrastructure, and has constructed an innovation ecology characterized by technology lists, planning blueprints, full-chain research, and innovative subjects from the perspective of whole-government coordination, cross-institutional decision-making, deep …


Technology Governance And Governance Technology: From Perspective Of Regulatory Research On Blockchain Digital Assets, Yikai WU, Guoan LI 2024 School of Law, Xiamen University, Xiamen 361005, China

Technology Governance And Governance Technology: From Perspective Of Regulatory Research On Blockchain Digital Assets, Yikai Wu, Guoan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Outline of the 14th Five-Year Plan takes blockchain as one of the key industries of the digital economy, and a number of ministries and commissions have also made clear deployments to accelerate the innovative application of blockchain, promote the digital transformation of the industry, and promote the high-quality development of the economy and society in the policy documents related to the informatization of the industry. The regulation and governance of blockchain digital assets cannot be separated from the understanding and analysis of blockchain technology itself, and observing the development mechanism of blockchain digital assets from the scientific and technological …


Interventional Radiology's Exploration Into Artificial Intelligence, Raymond Nguyen 2024 University of San Francisco

Interventional Radiology's Exploration Into Artificial Intelligence, Raymond Nguyen

Master's Projects and Capstones

Background: Artificial intelligence (AI) has become more prominent in our daily lives in recent years. This includes various aspects of healthcare. Interventional radiology (IR) is one of these specialties that has taken strides in understanding how AI can be leveraged for patient care. This literature review aims to understand what areas will be most impacted by AI in IR and how it will influence both the patient and interventional radiologist.

Methods: Twenty-six publications from 2019-2024 were selected from PubMed and Scopus. Publications were sourced through a combination of keywords, subject headings (MeSH terms), and citation searching.

Results: This literature review …


Parametric Identification Of Ship Maneuvering Motion Response Model Based On Square Root Cubature Kalman Filtering, Qinghao Li, Junsheng Ren, Yan Hua 2024 Nautical Dynamic Simulation and Control Key Laboratory, Dalian Maritime University, Dalian 116026, China

Parametric Identification Of Ship Maneuvering Motion Response Model Based On Square Root Cubature Kalman Filtering, Qinghao Li, Junsheng Ren, Yan Hua

Journal of System Simulation

Abstract: The system identification algorithm, based on the square root cubature Kalman filter (SRCKF) is proposed to address issues such as low accuracy, poor robustness, and weak generalization ability encountered by the extended Kalman filter (EKF) algorithm in parameters identification of ship maneuvering motion models. This algorithm, within the framework of CKF, replaces the original covariance matrix with its root mean square and utilizes triangular decomposition for prediction and update to enhance identification stability. The EKF is used as a comparison algorithm to identify the parameters of the second-order nonlinear response model of a ship with rudder angles that comply …


A Method Based On Deep Learning For Assisting Sins/Dvl Integrated Navigation, Xinghong Kuang, Aowei Huang 2024 College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China

A Method Based On Deep Learning For Assisting Sins/Dvl Integrated Navigation, Xinghong Kuang, Aowei Huang

Journal of System Simulation

Abstract: The navigation and positioning accuracy of an Autonomous Underwater Vehicle (AUV) affects the efficiency of the AUV to a certain extent, and since GNSS cannot be used underwater, the integrated navigation system of Strapdown Inertial Navigation System/ Doppler Velocity Log (SINS/DVL) has been widely favored. However, DVL will fail in some cases, and if DVL is isolated directly, the system will become a pure inertial navigation system, which seriously affects the accuracy of navigation and positioning. In order to cope with the situation that DVL is missing in some beams, a DLinear-Informer assisted integrated navigation algorithm is proposed. Through …


Dynamic Data Driven Simulation: An Overview, Xu Xie, Xiaogang Qiu, Yizheng Bao, Kai Xu 2024 College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Dynamic Data Driven Simulation: An Overview, Xu Xie, Xiaogang Qiu, Yizheng Bao, Kai Xu

Journal of System Simulation

Abstract: Dynamic data driven simulation is a simulation paradigm which integrates simulation and data together. This paradigm continuously feeds real-time data into the simulation, enabling the simulation be dynamically adjusted by the data, which thus improves the simulation-based estimation and prediction capability. Due to this integration, the dynamic data driven simulation can estimate system states and predict future state evolution more accurately. This paper reviews the origins and basic concept of dynamic data driven simulation, and introduces several simulation paradigms originated from the idea of "integrating models with data", and identifies the linkages and differences among them. The particle filterbased …


Research On Digital Twins Technology In Cyberspace Security, Qiankun Ren, Xinli Xiong, Jingju Liu, Qian Yao 2024 College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China; Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation, Hefei 230037, China

Research On Digital Twins Technology In Cyberspace Security, Qiankun Ren, Xinli Xiong, Jingju Liu, Qian Yao

Journal of System Simulation

Abstract: Combined with digital twins and cyber-space modeling and simulation, the network digital twins (NDT) technology with in-deep research can enable the development of diverse techniques of cyber security. The basic concept and research history of NDT are summarized, and a taxonomy is proposed to survey applications of NDT. A cyber security-oriented network digital twin model (CyS-NDT) is concluded through the literature. The relationship between the internal security problem of NDT and the method of enabling network security technology is discussed to prospect further challenges and opportunities.


Hybrid Evolutionary Multi-Objective Optimization Algorithm For Vehicle Routing Problem With Simultaneous Delivery And Pickup, Wenqiang Zhang, Xiaomeng Wang, Xiaoxiao Zhang, Guohui Zhang 2024 Henan University of Technology, Zhengzhou 450001, China

Hybrid Evolutionary Multi-Objective Optimization Algorithm For Vehicle Routing Problem With Simultaneous Delivery And Pickup, Wenqiang Zhang, Xiaomeng Wang, Xiaoxiao Zhang, Guohui Zhang

Journal of System Simulation

Abstract: In order to provide reasonable and effective decision support for logistics enterprises in vehicle distribution route planning, a hybrid evolutionary multi-objective optimization algorithm combining a multi-region mixed-sampling strategy for global search and a local search based on individual route sequence differences is proposed for the problem. A reasonable mathematical model is constructed and the global search strategy is used to make the population individuals to converge quickly to the Pareto front from multiple directions, and the local search strategy is employed to guide the poorly performing individuals in the population to evolve towards the direction of better performing individuals, …


Research On Virtual Simulation Testing Technology For Intelligent Navigation Collision Avoidance Decision-Making And Planning, Jialun Liu, Fan Yang, Lingli Xie, Shijie Li, Tengfei Wang 2024 Hubei Longzhong Laboratory, Wuhan University of Technology Xiangyang Demonstration Zone, Xiangyang 441000, China; State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China; Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

Research On Virtual Simulation Testing Technology For Intelligent Navigation Collision Avoidance Decision-Making And Planning, Jialun Liu, Fan Yang, Lingli Xie, Shijie Li, Tengfei Wang

Journal of System Simulation

Abstract: This paper studies virtual simulation testing technology for intelligent navigation collision avoidance decision-making and planning. The application requirements of intelligent navigation in cargo ships are introduced, and the current research status of collision avoidance decision-making strategies, path planning algorithms and decision-making planning testing technology are analyzed. For the intelligent navigation collision avoidance decision-making and planning capabilities of cargo ships, an intelligent navigation collision avoidance decision-making and planning algorithm is proposed based on the encounter situation division in the collision avoidance rules, combined with the quaternary ship field and Bezier curve interpolation theory. A simulation testing method for decision-making planning …


Digital Twin Method Of Stress Field Of Deep Submersible Spherical Shell Based On Simulation Database, Yu Cao, Jie Li, Fang Wang, Zhixiang Liu, Xueliang Wang 2024 Shanghai Ocean University, Shanghai 201306, China; State Key Laboratory of Industrial Equipment Structure Analysis of Dalian University of Technology, Dalian 116081, China

Digital Twin Method Of Stress Field Of Deep Submersible Spherical Shell Based On Simulation Database, Yu Cao, Jie Li, Fang Wang, Zhixiang Liu, Xueliang Wang

Journal of System Simulation

Abstract: This paper presents a method for predicting the stress field of deep diving spherical shells based on simulation databases and digital twin technology. By establishing simulation databases of stress field distribution of pressure-resistant spherical shells under different scales and loads, virtual sensing monitoring of stress states in other parts of the vessel is realized through finite sensor layout of pressureresistant shells on the submersible. Based on the DT(digital twin) technology, a three-level virtual structure layer is constructed. The Level-1 DT layer realizes the spatial mapping and cloud image display from the finite element simulation model to the digital model. …


Section Point Cloud Denoising Method Based On Enhanced Dbscan And Distance Consensus Evaluation, Chengpeng Ge, Dong Zhao, Rui Wang, Qinghua Ma 2024 School of Naval Architecture & Ocean Engineering, Jiangsu University of Science & Technology, Zhenjiang 212003, China

Section Point Cloud Denoising Method Based On Enhanced Dbscan And Distance Consensus Evaluation, Chengpeng Ge, Dong Zhao, Rui Wang, Qinghua Ma

Journal of System Simulation

Abstract: A denoising method based on the improved DBSCAN(density-based spatial clustering of applications with noise) algorithm is proposed to address the problem of removing noise points in point cloud data. The statistical filtering method is applied to pre-screen isolated outliers and remove largescale noise from the point cloud. The DBSCAN algorithm is optimized to reduce computational time complexity and achieve adaptive parameter adjustment, thereby dividing the point cloud into normal clusters, suspected clusters and abnormal clusters, and immediately removing abnormal clusters. Distance consensus assessment is applied, and suspect clusters are further evaluated. By calculating the distance between the suspected point …


High-Resolution Image Reconstruction Of Ect Region Of Interest Based On Finite Element Simulation, Lifeng Zhang, Da Chen 2024 Department of Automation, North China Electric Power University, Baoding 071003, China; Baoding Key Laboratory of State Detection and Optimization Regulation for Integrated Energy System, Baoding 071003, China

High-Resolution Image Reconstruction Of Ect Region Of Interest Based On Finite Element Simulation, Lifeng Zhang, Da Chen

Journal of System Simulation

Abstract: High-resolution image reconstruction of interest region is one of the research hotspots of electrical capacitance tomography (ECT) technology. The ECT model with uniform electrode distribution only has a high sensitivity coefficient at the boundary position of the reconstructed field and is not suitable for imaging regions of interest. In order to improve the sensitivity distribution in the region of interest and improve image resolution, a high-resolution image reconstruction method of ECT region of interest based on finite element simulation is proposed, and the electrode distribution is optimized according to the conformal transformation theory. Simulation experiments are conducted, and the …


Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan 2024 Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China

Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan

Journal of System Simulation

Abstract: To solve the problem of the poor search for optimal performance and obstacle avoidance ability of path planning algorithms in complex dynamic environments, a UAV dynamic path planning algorithm combined with dynamic window approach (UAV-DPPA-DWA) is proposed. In the UAVDPPA- DWA algorithm, a novel elliptic tangent graph algorithm based on the evaluation of offset degree and obstacle distance is proposed to obtain the optimal guidance path for the UAV in static environments. If the UAV detects moving obstacles, a localized obstacle avoidance trajectory will be generated using the dynamic window method with adaptive parameters. Otherwise, the UAV will continue …


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