Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (17307)
- Computer Engineering (13035)
- Artificial Intelligence and Robotics (11148)
- Databases and Information Systems (7250)
- Numerical Analysis and Scientific Computing (6662)
-
- Electrical and Computer Engineering (5273)
- Social and Behavioral Sciences (4827)
- Operations Research, Systems Engineering and Industrial Engineering (4777)
- Information Security (4669)
- Software Engineering (4315)
- Systems Science (3919)
- Business (2514)
- Mathematics (2384)
- Graphics and Human Computer Interfaces (2371)
- Theory and Algorithms (2151)
- Education (2099)
- Life Sciences (2075)
- Programming Languages and Compilers (1844)
- Medicine and Health Sciences (1803)
- Other Computer Sciences (1793)
- OS and Networks (1760)
- Arts and Humanities (1456)
- Communication (1446)
- Law (1175)
- Data Science (1157)
- Applied Mathematics (1134)
- Statistics and Probability (1061)
- Bioinformatics (986)
- Institution
-
- Singapore Management University (9003)
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Wright State University (2694)
- Purdue University (2077)
-
- Old Dominion University (1996)
- Missouri University of Science and Technology (1938)
- University of Nebraska - Lincoln (1739)
- Edith Cowan University (1285)
- Air Force Institute of Technology (1277)
- University of Texas at El Paso (1174)
- Kennesaw State University (1161)
- Dartmouth College (1104)
- San Jose State University (1053)
- City University of New York (CUNY) (956)
- Embry-Riddle Aeronautical University (950)
- Washington University in St. Louis (830)
- Brigham Young University (823)
- Technological University Dublin (816)
- California Polytechnic State University, San Luis Obispo (788)
- Zayed University (677)
- University of Texas at Arlington (666)
- University for Business and Technology in Kosovo (637)
- Portland State University (625)
- Chulalongkorn University (618)
- Nova Southeastern University (577)
- New Jersey Institute of Technology (571)
- Syracuse University (532)
- University of Nebraska at Omaha (497)
- University of Central Florida (490)
- Keyword
-
- Machine learning (1665)
- Artificial intelligence (1020)
- Deep learning (1003)
- Machine Learning (761)
- Computer Science (712)
-
- Security (648)
- Cybersecurity (558)
- Artificial Intelligence (484)
- Deep Learning (434)
- Computer science (412)
- Privacy (410)
- Simulation (391)
- Technical Reports (390)
- UTEP Computer Science Department (389)
- Classification (375)
- Algorithms (357)
- Optimization (352)
- Computer vision (349)
- Neural networks (345)
- Data mining (337)
- AI (301)
- Natural language processing (293)
- Department of Computer Science and Engineering (291)
- Engineering (269)
- Education (268)
- Reinforcement learning (259)
- Blockchain (255)
- Cloud computing (255)
- College for Professional Studies (253)
- Software engineering (252)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8458)
- Journal of System Simulation (3880)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Theses and Dissertations (2733)
- Department of Computer Science Technical Reports (1721)
-
- Computer Science & Engineering Syllabi (1312)
- Computer Science Faculty Publications (928)
- Computer Science Faculty Research & Creative Works (919)
- Departmental Technical Reports (CS) (914)
- Master's Projects (859)
- Computer Science Technical Reports (772)
- The R Journal (708)
- All Computer Science and Engineering Research (683)
- All Works (675)
- Faculty Publications (663)
- C-Day Computing Showcase (653)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (618)
- Dissertations (568)
- Electronic Theses and Dissertations (567)
- Kno.e.sis Publications (542)
- Journal of Digital Forensics, Security and Law (536)
- CCAC Theses and Dissertations (512)
- Walden Dissertations and Doctoral Studies (469)
- Computer Science Faculty Publications and Presentations (404)
- Theses (403)
- USF Tampa Graduate Theses and Dissertations (378)
- Neutrosophic Systems with Applications (375)
- Computer Science and Engineering Theses - Archive (365)
- Computer Science: Faculty Publications (364)
- Browse all Theses and Dissertations (359)
- Publication Type
Articles 5671 - 5700 of 63035
Full-Text Articles in Computer Sciences
Research On Digital Twin Simulation Method Of Industrial Robot Integrated With Reinforcement Learning, Tianyue Miao, Lu Wang, Jiaxiao He, Nenggang Xie
Research On Digital Twin Simulation Method Of Industrial Robot Integrated With Reinforcement Learning, Tianyue Miao, Lu Wang, Jiaxiao He, Nenggang Xie
Journal of System Simulation
Abstract: In response to the lack of comprehensive functionality and limited application scenarios in the current field of industrial robot digital twin systems, which results in low versatility, a method for constructing a digital twin system for industrial robots with high versatility is proposed. A four-dimensional system architecture for the digital twin is designed, and the components and functions of the four-dimensional system are analyzed, based on the system level planning of the four-dimensional system, the concept of integrating reinforcement learning into the virtual replacement of real concept is defined. By constructing a multi-attribute virtual model and using TCP communication …
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Journal of System Simulation
Abstract: A multi-objective gait optimization method based on virtual prototype is proposed to address the difficulty of balancing personalisation and performance in gait planning for bipedal robots. A scale prototype of a planar underactuated biped robot is created according to the body structure of Chinese people, and an identification approach is used to determine the robot's exact inertial parameters. A virtual prototype of the robot is created, and three optimization goals—speed, energy use, and stability are developed. Using the enhanced NSGA-II algorithm, the Pareto optimal solution set for the robot multi-objective gait planning issue is produced. Numerous gaits that conform …
Intersection Braking Guidance For Trams Based On Lineside Signs, Wencong Tong, Jing Teng, Junxian Li, Xing Yao, Zhongjie Zhang
Intersection Braking Guidance For Trams Based On Lineside Signs, Wencong Tong, Jing Teng, Junxian Li, Xing Yao, Zhongjie Zhang
Journal of System Simulation
Abstract: Trams need to brake frequently due to signal control and safety speed limits at intersections. Due to the inaccuracy of distance judgment, tram drivers tend to reserve extra braking distance at intersections, resulting in lower braking coefficients and a decrease in speed. An intersection braking guidance method using lineside signs is proposed for trams to reduce braking distance redundancy and improve running speed. Drivers are guided to brake with the shortest possible distance by marking the initial braking position and speed of trams with fixed lineside signs. A tram driving simulation system was developed based on a vehicle dynamics …
Noise-Enhanced Network Science, Reyhaneh Abdolazimi
Noise-Enhanced Network Science, Reyhaneh Abdolazimi
Dissertations - ALL
Graphs are a versatile and powerful data structure used to model complex relationships in diverse domains such as social networks, biological systems, and transportation networks. In graphs, entities are represented by nodes, and interactions or relationships between them are represented by edges. For example, in the World Wide Web, web pages are considered vertices, and if there is a link from one page to another page on the web, there will be a directed edge between those pages in its graph data structure. These structures allow us to analyze and solve important problems like community detection (identifying closely related clusters …
Architecture And Key Technologies Of New Research Informatization Infrastructure Platform Under The Fifth Research Paradigm, Fangyu Liao, Yang Wang, Rongqiang Cao, Bo Zhang, Zhenyu Li, Huajin Wang, Xin Chen, Dong Li, Yangang Wang, Xin Wei
Architecture And Key Technologies Of New Research Informatization Infrastructure Platform Under The Fifth Research Paradigm, Fangyu Liao, Yang Wang, Rongqiang Cao, Bo Zhang, Zhenyu Li, Huajin Wang, Xin Chen, Dong Li, Yangang Wang, Xin Wei
Bulletin of Chinese Academy of Sciences (Chinese Version)
The basic platform of research informatization is an indispensable pedestal for modern scientific research and an important manifestation of national scientific and technological innovation capability. As the research paradigm continues to evolve, the architecture and technologies of research informatization infrastructure platform are bound to evolve as well. The new research paradigm brings unique demands and challenges to the algorithmic computility, network transmission capacity, and data storage and management. Consequently, it is an urgent requirement for research informatization infrastructure platform to make technological breakthroughs in the areas of intelligent computility, large-scale data storage and high throughput read/write, cross-network software and hardware …
Five Key Issues And Governance Strategies In Integration Of China’S National Computing Power, Tao Hong, Le Cheng
Five Key Issues And Governance Strategies In Integration Of China’S National Computing Power, Tao Hong, Le Cheng
Bulletin of Chinese Academy of Sciences (Chinese Version)
Computing power, as a core element of artificial intelligence, has not received sufficient research and attention compared to data and algorithms, and has become the short board of China in international artificial intelligence competition. In fact, the integrated construction of the arithmetic system is not only an inherent requirement for the development of the digital industry, but also a regular guide for the growth of the digital economy, and a core driver for the transformation of the digital society. Although it has always secured endorsement by national policy, the relevant legal norms and actual layout are still insufficient, and the …
A Clustering-Based Location Allocation Method For Delivery Sites Under Epidemic Situations, Yaqiong Zhou, Junqi Chen, Weishi Li, Sihang Qiu, Rusheng Ju
A Clustering-Based Location Allocation Method For Delivery Sites Under Epidemic Situations, Yaqiong Zhou, Junqi Chen, Weishi Li, Sihang Qiu, Rusheng Ju
Journal of System Simulation
Abstract: To address the poor performance of commonly used intelligent optimization algorithms in solving location problems—specifically regarding effectiveness, efficiency, and stability—this study proposes a novel location allocation method for the delivery sites to deliver daily necessities during epidemic quarantines. After establishing the optimization objectives and constraints, we developed a relevant mathematical model based on the collected data and utilized traditional intelligent optimization algorithms to obtain Pareto optimal solutions. Building on the characteristics of these Pareto front solutions, we introduced an improved clustering algorithm and conducted simulation experiments using data from Changchun City. The results demonstrate that the proposed algorithm outperforms …
Research On Verification Method Of Motor Startups In Nuclear Power Plants Based On Topology Recognition, Baozhu Li, Weijie Dong, Chao Chen
Research On Verification Method Of Motor Startups In Nuclear Power Plants Based On Topology Recognition, Baozhu Li, Weijie Dong, Chao Chen
Journal of System Simulation
Abstract: There are many motors in operation or on standby in nuclear power plants, and the startup of group motors will have a great impact on the voltage of the emergency bus. At present, there is no special or inexpensive software to solve this problem, and the experience of engineers is not accurate enough. Therefore, this paper developed a method and system for the startup calculation of group motors in nuclear power plants and proposed an automatic generation method of circuit topology in nuclear power plants. Each component in the topology was given its unique number, and the component class …
Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao
Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao
Journal of System Simulation
Abstract: The development process of complex equipment involves multi-stage business processes, multi-level product architecture, and multi-disciplinary physical processes. The relationship between its system model and various disciplinary models is extremely complicated. In the modeling and integration process, extensive customized development is needed to realize model integration and interoperability in different business scenarios. Meanwhile, the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios. To improve the efficiency of system modeling and integration in complex business scenarios, a system modeling and integration method was proposed. This method took …
Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang
Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang
Journal of System Simulation
Abstract: When a communication network is partially disabled or disrupted, an UAV is plunged into a "low-resource environment" and must rely on local hardware resources. This situation imposes constraints on computing power, storage capacity, and energy availability. To address the need for command intent recognition in such environments, a semi-physical simulation system for UAV in emergency rescue operations has been designed and implemented. Based on the low resource airborne hardware in the loop, the system simulates UAV command intention recognition and mission planning through GIS+BIM 3D environment modeling task scenarios. A new lightweight algorithm for intent recognition has been proposed, …
Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li
Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li
Journal of System Simulation
Abstract: Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route, a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed. In the process of swarm flight, the UAV obtains the reference route information of the current moment according to its own position, and obtains the predicted trajectory of its neighbors through local information interaction. When encountering obstacles, the adaptive obstacle avoidance radius and field of view topology method are combined to effectively solve the problem that the internal safety distance cannot be maintained and …
A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng
A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng
Journal of System Simulation
Abstract: The complexity of the system is mainly reflected in the numerous components and extremely complex interactions. Combined with the current trend of artificial intelligence development, this paper analyzes and considers the changes in thinking mode brought by simulation discipline research, and forms an understanding of the connotation and research scope of simulation intelligence. A new pattern for complex system simulation research is proposed: "simulation intelligence based generating decisions (SIGD)". In the SIGD pattern, the similar principles, modeling methods, and decision-guiding modes in simulation disciplines are different from those in traditional simulation. Under the guidance of this concept, a connection-oriented …
Development Of A Climbing Performance Analysis Tool Using Computer Vision, Guy Ludford
Development Of A Climbing Performance Analysis Tool Using Computer Vision, Guy Ludford
The Plymouth Student Scientist
Indoor bouldering, a rapidly growing sport in the UK and globally, has seen a significant rise in participation, paralleled by an increase in the use of fitness apps and wearable trackers. Despite this growth, tracking and recording metrics for indoor climbing remains a challenge. This paper proposes an automated tool utilising computer vision and a gym-wide camera system to collect data on routes climbed and attempts made, without the need for manual logging. This tool aims to provide climbers with detailed performance analysis and support climbing gyms in optimising route setting and member engagement. Initial market research and discussions with …
Enhancing Graph Neural Networks By Editing Graphs, Jiayu Li
Enhancing Graph Neural Networks By Editing Graphs, Jiayu Li
Dissertations - ALL
Graphs are pervasive in both the natural world and various domains of science and engineering. Numerous advanced classifiers, such as Graph Neural Networks (GNNs), have been developed to perform node classification on these graphs. However, as graphs become denser with an increasing number of edges, GNNs often suffer from suboptimal generalization performance due to the presence of task-irrelevant connections. These redundant connections can introduce noise, consume excessive computational resources, and degrade performance. Identifying and preserving critical connections in large-scale graphs, while pruning unnecessary ones, is crucial for enhancing the efficiency and accuracy of GNNs in node classification, particularly for GCNs. …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
McKelvey School of Engineering Graduate Student Theses & Dissertations
Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …
Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang
Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang
Journal of System Simulation
Abstract: Integrated with the actual situation of power grid and the growth of new energy, a multiobjective model for optimal scheduling of the integrated energy system(IES) is established based on the analysis of the energy-flow relationship of the IES and taking into account the priority of energy utilization and the load demand response in terms of the mismatch between the distributed energy sources and the loads, the net benefit of the unit cost of the IES, and the load response degree. Combined with the equipment and the environmental benefits system, a priority constraint for energy utilization has been established for …
Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang
Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang
Journal of System Simulation
Abstract: To solve the problem of unstable performance and inefficient training process of low-quality data conditions at the initial stage of online deployment of air conditioner scheduling, we propose a migration-imitation learning-based air conditioning scheduling strategy simulation method. Reinforcement learning methods are used to generate building operation strategies. A standard building simulation model serves as the source domain, upon which migration learning is applied. An imitation learning loss function is incorporated into the intelligent loss function to enhance algorithm performance. The results indicate that, compared with the non-use of migration learning, the proposed method can improve the operational efficiency by …
Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia
Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia
Journal of System Simulation
Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …
Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa
Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa
Dissertations - ALL
Deep neural networks are extensively applied to real-world tasks. In many cases, the data feeding these tasks are human generated content, which emphasizes the criticality of privacy and data protection. The diverse modalities of this user data provide fertile ground for 3rd parties to monetize a user’s data. This work considers two such modalities: user speech when interacting with smart speaker voice assistants (VAs) and images shared with online service providers. In these cases, the user would like to support some form of machine learning (ML) inference without allowing others. A user interacting with a smart speaker would like the …
Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng
Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng
Journal of System Simulation
Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …
Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan
Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan
Journal of System Simulation
Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
McKelvey School of Engineering Graduate Student Theses & Dissertations
Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …
A Confidence-Based Knowledge Integration Framework For Cross-Domain Table Question Answering, Yuankai Fan, Tonghui Ren, Can Huang, Beini Zheng, Yinan Jing, Zhenying He, Jinbao Li, Jianxin Li
A Confidence-Based Knowledge Integration Framework For Cross-Domain Table Question Answering, Yuankai Fan, Tonghui Ren, Can Huang, Beini Zheng, Yinan Jing, Zhenying He, Jinbao Li, Jianxin Li
Research outputs 2022 to 2026
Recent advancements in TableQA leverage sequence-to-sequence (Seq2seq) deep learning models to accurately respond to natural language queries. These models achieve this by converting the queries into SQL queries, using information drawn from one or more tables. However, Seq2seq models often produce uncertain (low-confidence) predictions when distributing probability mass across multiple outputs during a decoding step, frequently yielding translation errors. To tackle this problem, we present CKIF, a confidence-based knowledge integration framework that uses a two-stage deep-learning-based ranking technique to mitigate the low-confidence problem commonly associated with Seq2seq models for TableQA. The core idea of CKIF is to introduce a flexible …
Gmr-4234 Evaluating Instance Segmentation Models On Histopathology Datasets, Sai Chandana Koganti
Gmr-4234 Evaluating Instance Segmentation Models On Histopathology Datasets, Sai Chandana Koganti
C-Day Computing Showcase
Instance segmentation is transforming digital pathology by enhancing the speed and accuracy of tissue sample analysis through advanced image processing techniques. Whole Slide Imaging (WSI) converts traditional microscope slides into high-resolution digital formats, enabling detailed examinations. This paper presents a brief experimental survey of instance segmentation models on two prominent histopathology datasets: PanNuke and NuCLS. Unlike previous surveys that merely describe deep learning models for general pathology images, we conduct experiments using state-of-the-art models including Mask R-CNN, Detectron2, YOLOv8, YOLOv9, and HoverNet on both datasets. Our study evaluates these models for both binary and multiclass instance segmentation tasks. The NuCLS …
Gpr-187 Deep Learning Models For Protein-Protein Binding Affinity Prediction, Lingtao Chen
Gpr-187 Deep Learning Models For Protein-Protein Binding Affinity Prediction, Lingtao Chen
C-Day Computing Showcase
Binding affinity (BA) prediction is important for drug discovery and protein engineering. It seeks to understand the interaction strength between proteins and their ligands (or proteins). This information assists in the design of proteins with enhanced or novel functions, as well as understanding the molecular mechanisms of drug action. This paper presents the development and comparative analysis of two deep learning models, a convolutional neural network (CNN) and a transformer model. Many variants of models in this research were developed using TensorFlow. One model that utilizes ProteinBERT was developed using PyTorch. The CNN model captures local sequence features effectively, while …
Gmr-196 Integrated Sentiment And Behavioral Analysis Of Online Product Reviews, Kiran Yepuri, Naveen Mahankali
Gmr-196 Integrated Sentiment And Behavioral Analysis Of Online Product Reviews, Kiran Yepuri, Naveen Mahankali
C-Day Computing Showcase
The "Integrated Sentiment and Behavioral Analysis of Online Product Reviews" project helps businesses gain actionable insights from Product reviews by combining sentiment and behavioral analysis using NLP models like VADER and BERT. This dual approach categorizes reviews as positive, neutral, or negative and identifies themes such as preferences and complaints through Named Entity Recognition and topic modeling. By capturing both the emotional tone and specific product feedback, this method highlights consumer likes and pain points, assisting in targeted improvements for product design and customer service. The project addresses challenges in analyzing complex expressions like sarcasm, providing a robust framework for …
Gpr-185 A Multimodal Approach To Quiz Generation: Leveraging Rag Models For Educational Assessments, Mourya Teja Kunuku
Gpr-185 A Multimodal Approach To Quiz Generation: Leveraging Rag Models For Educational Assessments, Mourya Teja Kunuku
C-Day Computing Showcase
Crafting quiz questions that effectively assess students’ understanding of lectures and course materials, such as textbooks, poses significant challenges. Recent AI-based quiz generation efforts have predominantly concentrated on static resources, like textbooks and slides, often overlooking the dynamic and interactive elements of live lectures—contextual cues, discussions, and interactions—that contribute to the learning experience. In this work, we propose a Retrieval-Augmented Generation (RAG) model that processes multimodal inputs by combining text, audio, and video to produce quizzes that capture a fuller context. Our method incorporates Whisper for audio transcription and utilizes a Large Vision-Language Model (LVLM) to extract essential visual data …
Uc-184 Onaccount A Web-Based Accounting Software, Manuel A Jackson, Russell E Steele, Grzegorz Loj, Zachary B Powell
Uc-184 Onaccount A Web-Based Accounting Software, Manuel A Jackson, Russell E Steele, Grzegorz Loj, Zachary B Powell
C-Day Computing Showcase
This project streamline and improve the efficiency of the whole accounting process, by using current best practices for user interaction engineering and current design practices. Our software should be able to provide secure, user-friendly, and accessible financial management solutions anywhere and everywhere through various devices including desktop and mobile. Allowing users to manage their accounts whenever it seems necessary while still maintaining a high level of security. The project is inspired by the various complexity and problems regarding the accounting process in the real world such as financial reporting, miscalculations, and data security; by streamlining this process and making it …