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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是431-440 订阅

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IoT-Based Mental Health Monitoring System Using Machine Learning Stress Prediction Algorithm in Real-Time Application 7th

IoT-Based Mental Health Monitoring System Using Machine Lear...

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7th international conference on Big Data and Cloud Computing Challenges, ICBCC 2022

作者： Quadir, Md Abdul Bhardwaj, Saumya Verma, Nitika Sivaraman, Arun Kumar Tee, Kong Fah School of Computer Science and Engineering Vellore Institute of Technology Chennai India Digital Engineering Services Photon Inc. Chennai India Department of Civil and Environmental Engineering King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9789819910502

With the primary focus of healthcare technologies being on the physical health of a person, mental health issues sometimes go unattended. Stress, anxiety, and depression are becoming increasingly common problems in our community leading to serious heart-related problems such as high blood pressure, episodes of heart attack and can even lead to chronic illness. Prediction of stress or depression at an earlier stage can prevent serious consequences as sometimes patients suffering from mental illness are not aware of the severity of their condition or do not keep up with counseling for a longer period of time. In this context this paper proposes a stress prediction method using machine learning to detect the development of stress or anxiety problems at an early stage. Our proposed method observes any changes in the human body under stress or depression by monitoring the ECG values and other physiological factors to predict any kind of possible stress or depression. the proposed model provided high accuracy of 98% in predicting stress. On detecting stress, appropriate actions such as informing the patient's guardian and doctor are taken. As compared with other models, our model outperforms the other state of the art models, making it a real-world predication model. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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Effect of Early Intervention on Students in a CS1 programming Course 7th

Effect of Early Intervention on Students in a CS1 Progra...

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7th international conference on Applied Informatics, ICAI 2024

作者： Llanos-Mosquera, Jose Miguel Quimbayo-Castro, Julian Andres Garcia-Perdomo, Edisney Alarcon-Lopez, Alvaro Hernan Faculty of Engineering Corporación Universitaria del Huila - CORHUILA Neiva Colombia

ISBN: (纸本)9783031751462

CS1 programming courses often exhibit low academic performance. One way to address this issue is by implementing early interventions for students. In higher education, various theories have contributed to the topic of intervention, one of which is Vygotsky’s zone of proximal development. However, there is no consensus in the results, and more studies are needed to evaluate early interventions in CS1 courses. the objective of this research is to examine the effect of an early intervention on students’ academic performance in a CS1 course. the study involved 49 students from a Logic programming course, with 24 in the experimental group and 25 in the control group. Two stages of the zone of proximal development were used, including group tutoring and the development of a programming reinforcement workshop. Additionally, the Motivated Strategies for Learning Questionnaire (MSLQ) was used to identify the learning and motivation strategies employed by students in a CS1 programming course. the quantitative results of the experimental group show a positive correlation between the percentage of attendance at group tutoring sessions and the student’s final grade. Furthermore, a positive correlation was identified between the percentage of submitted reinforcement exercises and the student’s final grade. In the control group, significant improvements were identified in four subscales of the selected learning and motivation strategies questionnaire, even though no intervention strategy was applied. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Students

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Research on Mining Association Rules for Classroom Concentration Based on Apriori Algorithm

Research on Mining Association Rules for Classroom Concentra...

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IEEE Information Technology and Mechatronics engineering conference (ITOEC)

作者： Jingqiu Bai Huafeng Kong Wenhan Hu Department of Information Engineering Wuhan Business University Hubei China Major in Data Science and Big Data Technology The Main Research Direction is the Computer Application

this paper studies the correlation between students' concentration in class and learning interest, emotional state and other influencing factors. By collecting students' classroom status data, a data set suitable for data mining is constructed. Based on the idea of Apriori algorithm, the Anaconda Navigator programming tool is used to mine the association rules of students' classroom concentration. through data mining based on Apriori algorithm, and the association rules between students' emotional state, learning interest and other factors and in-class test scores are output. the results of strong association rules show that the better students' emotional state, learning interest and other states are, the better their classroom concentration performance is. Mining the potential influencing factors of students' classroom concentration provides valuable reference theory for students to improve classroom concentration and teachers to improve classroom teaching effect, which is helpful for teachers and students to build a more efficient classroom together in the future.

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Trajectory Generation for Autonomous Surface Vessels Based on Bézier Curves

Trajectory Generation for Autonomous Surface Vessels Based o...

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international conference on Transportation Information and Safety (ICTIS)

作者： Fan Yang Yaping Zhu Jialun Liu Ran Chen Qimao Teng State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China National Engineering Research Center for Water Transport Safety Wuhan China Wuhan Zhongyuan Electronics Group Co. Ltd Wuhan China Academician Workstation of China COSCO Shipping Corporation Limited Shanghai China

Autonomous surface vessels have attracted significant attention from scholars in the shipping and marine community in recent years. Researchers have focused on methods that consider the dynamics of the vessel to develop effective trajectory generation strategies for these vessels. Efficient trajectory generation is indispensable, but conventional path planning algorithms based on search and sampling are less applicable. To plan trajectories exclusively in the flat output space, we utilize the differential flatness property. In this paper, we use the basic artificial potential field method for front-end trajectory search and present a method for generating feasible trajectories for these vessels using piecewise Bézier curves. By incorporating Bernstein polynomial basis functions and optimizing the cost function with necessary constraints, we convert the problem into a typical convex quadratic programming format. Finally, we evaluate the efficacy of the method by conducting numerical simulation experiments.

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Optimization of ship command and dispatch in the waters between the three gorges dams based on GP algorithm

Optimization of ship command and dispatch in the waters betw...

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international conference on Transportation Information and Safety (ICTIS)

作者： Qing Liu Zhuofeng Tang Zhe Cong Lei Wang School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China Guangdong Inland Waterway Port and Maritime Industry Research Co Wuhan China

At present, the backlog of ships passing through the three Gorges has become the norm, and the difference between the passing capacity of the three Gorges-Gezhouba locks and the passing capacity of the waters between the two dams has led to a reduction in the efficiency of ship navigation through the locks and an increase in the difficulty of control. In view of the above problems, this paper constructs an optimization model for the control and command of formation ship groups under the existing ship navigation rules, taking into account the safety distance to be maintained between ship groups, the continuity of navigation and other realistic constraints, with the objective of minimizing the imbalance between navigation time and delay time. Based on the characteristics that the ship navigation process is similar to the processing operation in the production plant, a heuristic scheduling rule set and Genetic programming (GP) algorithm are established for the solution. the research results show that the method of determining the navigation order of vessel groups by generating composite dispatching rules (CDR) with GP algorithm can reduce the navigation time of vessels crossing the gate in the waters between two dams and effectively improve the fairness of scheduling, while meeting the requirements of vessel navigation rules and safety.

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Revolutionizing the Driving Experience : Enhancing Safety and Comfort Using ADAS

Revolutionizing the Driving Experience : Enhancing Safety an...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Aditya Kelkar Digvijay Jondhale Rugved Borade Ishan Juneja Yuvraj Haran Rajendra G. Pawar School of Computer Engineering & Technology MIT World Peace University Pune Maharashtra Department of Computer Science Engineering MIT School of Computing MIT Art Design and Technology University Pune India

Advanced Driver Assistance Systems, or ADAS for short, are a group of technologies intended to help drivers operate their automobiles more safely and effectively. these systems often employ sensors, cameras, and other gadgets to keep an eye on the surroundings of the car and give the driver alerts or help in a multitude of circumstances, like lane departure, accident avoidance, and parking. Modern vehicles are increasingly utilizing ADAS technologies, which are regarded as an important first step towards completely autonomous vehicles.

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Auxiliary CNN for Graspability Modeling with 3D Point Clouds and Images for Robotic Grasping 7th

Auxiliary CNN for Graspability Modeling with 3D Point Clouds...

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7th international conference on Computer Vision and Image Processing, CVIP 2022

作者： Varun, Priyanka Behera, Laxmidhar Sandhan, Tushar Electrical Engineering IIT Kanpur U.P. Kanpur India Electrical Engineering IIT Mandi Himachal Pradesh Mandi India

ISBN: (纸本)9783031314162

Automatic object grasping is a challenging problem and has numerous applications in various fields. Currently, researchers have developed models that use only 3D point cloud data which is not sufficient to capture a complete grasping ability (graspability), because many visual features related to objects are missing in the 3D points. So here we propose an auxiliary convolutional neural network pipeline (CNN) for graspability modeling via simultaneously using visual information from RGBD images and 3D point clouds. For training the auxiliary CNN, we have created new dataset where the most graspable object has been placed in class 5, whereas the least graspable object has been placed in class 1. Our graspability modeling includes, 12 object features, where 9 are extracted from elliptic Fourier descriptors, the other 3 features are Euclidian distance from the centroid, compactness of an object and category of an object. We have thoroughly evaluated our proposed approach by incorporating it into state-of-the-art grasping method Graspnet [8], which has further improved the overall average grasp precision. Additionally, we performed an ablation study on various network elements and loss functions (cross entropy, mean square loss) for obtaining the best accuracy and graspability scores. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Convolutional neural networks

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Efficient Compiler Option Tuning: Exploiting Objective Interdependencies for Enhanced Performance

Efficient Compiler Option Tuning: Exploiting Objective Inter...

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Advanced Algorithms and Control engineering (ICAACE), international conference on

作者： An Shao College of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

the process of managing numerous optimization options in a compiler like GCC, aimed at achieving various runtime performance goals such as file size, compilation time, and execution time, is quite challenging. Existing methods, both meta-heuristic and data-driven, often overlook the crucial interdependencies among these objectives, leading to suboptimal performance in optimization algorithms. Our research introduces a cost-effective approach that not only recognizes but also effectively exploits these interdependencies for more efficient compiler option tuning. this approach involves sequentially developing three Gaussian process surrogate models, each tailored to a specific optimization goal but closely interlinked to ensure a comprehensive optimization strategy. Additionally, we utilize a clustering-based selection mechanism that leverages the connections and diversity within the Pareto set. Our evaluation with GCC and the cBench benchmark suite demonstrates superior performance in Pareto front diversity compared to current methods, highlighting the importance of considering objective interdependencies in optimization algorithm efficiency.

关键词： Runtime Control engineering Metaheuristics Process control Gaussian processes Benchmark testing Linear programming

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A Novel IoT Framework and Device Architecture for Efficient Smart city Implementation

A Novel IoT Framework and Device Architecture for Efficient ...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Sheetalrani R Kawale KDV Prasad D Palanikkumar P. Arockia Mary A.Yasmine Begum Dankan Gowda V Department of Computer Science Karnataka State Akkamahadevi Women's University Vijayapura Karnataka India Symbiosis Institute of Business Management (SIBM) Symbiosis International (Deemed University) (SIU) Hyderabad Telangana India Department of CSE Dr NGP Institute of Technology Coimbatore Tamilnadu India Department of Information Technology V.S.B. Engineering College Karur Tamilnadu India Department of Electronics and Instrumentation Engneering Mohan Babu University (Erst while Sree Vidyanikethan Engineering College) Andhra Pradesh India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka India

Internet of things (IoT) apps will provide fast and effortless management of smart cities. this networked service management is dependent on the Internet Service Provider (ISP). this framework reduces physical human interaction in banking, railway counters, water and power counters, and so on. the IoT based applications makes the smart cities more sustainable. Recently, the Indian government is more focused and supportive towards building a reliable IoT based framework for developing innovative products, and businesses that rely mostly on cyberspace. this study discusses about the advantages, disadvantages and future possibilities of smart cities. the importance of the Internet of things (IoT) in the development of India's smart cities, as well as how widespread adoption may swiftly disrupt people's everyday routines are also discussed.

关键词： Smart cities Web and internet services programming Market research Rail transportation Internet of things Security

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Graph Based Systematic Synthesis Procedure of gm-C Filter

Graph Based Systematic Synthesis Procedure of gm-C Filter

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Mousumi Bhanja Anirban Ganguly Smita Rani Parija Department of Electronics and Telecommunication Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India Dept. of Electrical and Electronics Engineering Bharat Institute of Engineering and Technology Hyderabad India Department of Electronics and Tele-Communication Engineering C V Raman Global University Bhubaneswar India

Real world signals, being analog by nature requires analog signal processing. But unfortunately analog domain still lacks of good research on analog EDA tool. therefore, developing systematic synthesis methodology is a major research topic still to be addressed and improved to cope up with the recent technological advancements in VLSI. In this background, a graph has been employed to represent synthesis methodology for linear analog filters in a systematic way. Nodes of bipartite graph represents some basic first order mathematical functions; those are connected through weighted edges (with relation operator). Traversal of the graph with defined traversal rules gives different subgraphs implementing different types/order of filters. the graph has been optimized with some defined set of rules. Optimized graph has been converted into a multifunctional filter structure, which realizes all types of filters by programming the connections among the building blocks. this systematic synthesis approach supports reusability and programmability in hardware, when implemented in gm-C. Filter response is verified through SPICE simulation.

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