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Universal Five-Axis RTCP Adaptive Dispensing Interpolation System Based on Dual NURBS

Universal Five-Axis RTCP Adaptive Dispensing Interpolation S...

引用

Mechatronics and Robotics Engineering (ICMRE), international conference on

作者： Yichong Lin Di Li Minghao Cheng School of Mechanical & Automotive Engineering South China University of Technology Guangzhou China

this paper proposed a five-axis RTCP adaptive dispensing interpolation algorithm based on dual NURBS curves, to meet the requirement for high dispensing efficiency in the electronic industry. A universal RTCP transformation algorithm is used to transform the programming trajectory to the machine tool control point trajectory for five-axis machines with different configurations. the machine tool control point trajectory and the dispenser head trajectory are fitted by dual NURBS curves separately. the predictor-corrector method solves the curve position parameter at the corresponding time. the corresponding position relationship between the dual curves is determined according to the parameter synchronization relationship, which solves the adaptively adjusted dispensing frequency. A dispensing processing experiment is designed, and results show that the algorithm in this paper can achieve shorter processing time than dual NURBS equidistant dispensing under process constraints.

关键词： Surface reconstruction Interpolation Heuristic algorithms programming Prediction algorithms Magnetic heads Trajectory

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Two-Dimensional Grid-Free Algorithm for Separation of Underwater Acoustic Raypath

Two-Dimensional Grid-Free Algorithm for Separation of Underw...

引用

IEEE international conference on Signal and Image Processing (ICSIP)

作者： Fengyan Zhong Zhichen Li Chao Yang The Laboratory of Image Science and Technology Southeast University Nanjing China

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

In this paper, a high resolution raypath separation algorithm is proposed in the context of ocean acoustic tomography. By exploiting atomic norm theory, signals were sparsely represented in a two-dimensional continuous space of angle and delay, and a convex semidefinite programming (SDP) model with atomic norm constraints is established. the dual SDP problem of this model is derived from the perspective of dual norms. the proposed algorithm does not require grid division of the estimation domain, thus eliminating the grid mismatch problem. Experimental results show that, compared to the two-dimensional conventional compressive beamforming, the presented approach improves separation accuracy.

关键词： Image coding Accuracy Semidefinite programming Array signal processing Oceans Tomography Delays

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Research on a Strapdown Inertial Navigation Algorithm Based on Unmanned Driving

Research on a Strapdown Inertial Navigation Algorithm Based ...

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Automation, Control and Robotics Engineering (CACRE), international conference on

作者： Yuan Yue Zongping Yang Institute of Intelligent Manufacturing and Automobile Chongqing Transportation Vocational College Chongqing China

ISBN: (数字)9798350350302

ISBN: (纸本)9798350350319

Strapdown inertial navigation can be applied to intelligent connected vehicles due to its simple and small size, low cost, high short-term accuracy, and strong stability. the efficiency and reliability of its system depend on the calculation algorithm of strapdown inertial navigation. therefore, this article designs a strapdown inertial navigation algorithm that uses MATLAB programming to calculate the navigation parameters of the carrier, such as attitude, velocity, and position. the dual sample algorithm is used to dynamically compensate for attitude and velocity. Based on vehicle test data and comparison of test results, it is concluded that the algorithm proposed in this article has certain theoretical significance and practical value.

关键词： Accuracy Costs Connected vehicles Automation Heuristic algorithms Inertial navigation programming

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Predicting Academic Grades of Students in Computer programming Using Classification Algorithms

Predicting Academic Grades of Students in Computer Programmi...

引用

international conference on Advanced Computing and Communication Systems (ICACCS)

作者： C P Pavan Kumar Hota V. Asanambigai D. Lakshmi Department of CSE Annamalai University Tamilnadu India School of Computing Science and Engineering (SCSE) VIT Bhopal University Madhya Pradesh India

In computer science education, teaching and learning programming is difficult. Understanding and coding programmes are regarded as extremely difficult in computer science education. this is because practical ability is valued more than theoretical knowledge. According to research, students with metacognitive management skills outperform lower-performing students in programming. the more difficult the programming task, the more important it is for the programmer to have metacognitive control skills. the cognitive processes involved in learning computer programming necessitate the development of metacognitive skills in the novice programmer. this study’s main objective is to predict computer programming students’ academic grades using classification algorithms. the predictive analysis used 151 records that were gathered and used. three methods are considered in order to find the best classifier: Rule Based Classification, Decision Tree Classification, and Nave Bayesian Classification. the confusion matrix, common metrics like precision, recall, ROC curve, kappa statistics, mean absolute error, root mean squared error, relative absolute error, and root relative squared error are all used to assess how well each classifier classified the dataset. Conclusion: With 95% accuracy, the ID3 classifier outperformed the other six predictive models.

关键词： Measurement Decision making Predictive models Prediction algorithms Classification algorithms Computer science education Numerical models

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Designing Transient Stability Controllers for Power Systems via Sum-of-Squares programming

Designing Transient Stability Controllers for Power Systems ...

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IEEE international conference on Power and Power and Renewable Energy (ICPRE)

作者： Yingjie Qin Yu Liu Deyang Chen Xinwei Wang Lu Miao Wei Fan Zengjie Chen Yuhan Zhang Jiemin Liao Electric Dispatching and Control Center Guangdong Power Grid Corporation Guangzhou China School of Electric Power Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Traditional stability controllers are constructed based on the equilibrium points of power systems and fail to meet the performance criteria under large disturbances. In this paper, an algorithm has been proposed to design transient stability controllers for power system using Sum-of-squares (SOS) programming which is a powerful technique able to answer many analysis questions for nonlinear systems. Since the SOS programming only deals with polynomial systems, first we recast the power system model into polynomial form. then we derive the algorithm from the Lyapunov theory to search for stability controllers of power systems, by introducing the so-called target region and expanding the estimated stability region. the effectiveness of our algorithm is demonstrated on the IEEE 3-machine-9-bus power system.

关键词： Renewable energy sources Stability criteria Power system stability programming Polynomials Power electronics Closed loop systems Transient analysis Nonlinear systems thermal stability

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Joint international Master in Smart Systems Integrated Solutions 9

Joint International Master in Smart Systems Integrated Solut...

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IEEE 9th Electronics System-Integration Technology conference (ESTC)

作者： Aasmundtveit, Knut E. Wang, Changhai Rencz, Marta Paulasto-Krockel, Mervi Imenes, Kristin Desmulliez, Marc P. Y. Ender, Ferenc Vuorinen, Vesa Univ South Eastern Norway Dept Microsyst Borre Norway Heriot Watt Univ Inst Sensors Signals & Syst Edinburgh Midlothian Scotland Budapest Univ Technol & Econ Dept Elect Devices Budapest Hungary Aalto Univ Dept Elect Engn & Automat Helsinki Finland Univ South Eastern Norway Dept Microsyst Borre Norway

ISBN: (数字)9781665489478

ISBN: (纸本)9781665489478

the Joint international Master in Smart Systems Integrated Solutions (SSIs) will graduate engineers for the current and future industry of Smart Systems, to serve in all society sectors such as healthcare, environment protection, transport, energy and security. three universities in three European countries have joined forces to deliver SSIs: Aalto University (Helsinki, Finland), University of South-Eastern Norway (USN), and Budapest University of Technology and Economics (BME) (Hungary). SSIs uses the complementarity of the three universities, in terms of staff expertise as well as laboratory facilities, thus giving a more holistic approach to Smart Systems than any of the individual universities could give. Smart Systems Integration is covered both as "physical integration" (packaging) and "functional integration" (MEMS and IC co-design, System Level Design). the programme collaborates closely with industry, in particular for guest lectures, company visits, internships and master projects. SSIs builds on the Joint international Master in Smart Systems Integration (SSI), which has been running since 2013 with Heriot-Watt University (Edinburgh, Scotland) co-ordinating a consortium including USN and BME. SSIs students lives at least one semester in each of the three host countries. this gives them cross-cultural experience making them very suitable for an international working environment. the performance of the students in the programme is excellent, and the employment rate of graduates is very high.

关键词： Joint master degree Industry collaboration in education Smart Systems Integration Microsystem technology Erasmus Mundus

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Large Language Models and Adversarial Reinforcement Learning to Automate PLCs programming: A Preliminary Investigation

Large Language Models and Adversarial Reinforcement Learning...

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international conference on Control, Decision and Information Technologies (CoDIT)

作者： Abderrahmane Boudribila Mohamed-Amine Chadi Abdelouahed Tajer Zakaria Boulghasoul Cadi Ayyad University National School of Applied Sciences Systems Engineering Applications Laboratory Marrakech Morocco Faculty of Sciences Semlalia Informatics Systems Engineering Laboratory Cadi Ayyad University Marrakech Morocco

the manual programming of Programmable Logic Controllers (PLCs) is a time-consuming and error-prone task, particularly for complex systems. Researchers have proposed various techniques, such as the modular, decentralized, hierarchical, and distributed approaches, which all fall under the Supervisory Control theory (SCT) whose main goal is to generate a supervisor that ensures that the controller's behavior satisfies the specifications. While these techniques have demonstrated efficiency in systems of low complexity, high-complexity systems and probabilistic ones remain a major challenge. In this paper, we propose a novel pipeline that relies solely on Artificial Intelligence (AI)-techniques, namely, Reinforcement Learning (RL) and Natural Language Processing (NLP) techniques, including Named Entity Recognition (NER) and Large Language Models (LLMs). As a preliminary result, we demonstrate the potential of the proposed pipeline using the recent ChatGPT model by making a sample dataset in this context and generating Structured Text code from specifications presented in a natural language format. Finally, we outline future directions toward a fully automated AI-based PLC programming tool.

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the W-CALCULUS: A Synchronous Framework for the Verified Modelling of Digital Signal Processing Algorithms 9

The W-CALCULUS: A Synchronous Framework for the Verified Mod...

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9th ACM SIGPLAN international Workshop on functional Art, Music, Modelling, and Design (FARM)

作者： Arias, Emilio Jesus Gallego Jouvelot, Pierre Ribstein, Sylvain Desblancs, Dorian Inria Paris Equipe R2 Paris France PSL Univ MINES ParisTech Paris France Ecole Normale Super Paris Saclay Paris France

ISBN: (纸本)9781450386135

We introduce the W-CALCULUS, an extension of the call-by-value lambda-calculus with synchronous semantics, designed to be flexible enough to capture different implementation forms of Digital Signal Processing algorithms, while permitting a direct embedding into the Coq proof assistant for mechanized formal verification. In particular, we are interested in the different implementations of classical DSP algorithms such as audio filters and resonators, and their associated high-level properties such as Linear Time-invariance. We describe the syntax and denotational semantics of the W-CALCULUS, providing a Coq implementation. As a first application of the mechanized semantics, we prove that every program expressed in a restricted syntactic subset of W is linear time-invariant, by means of a characterization of the property using logical relations. this first semantics, while convenient for mechanized reasoning, is still not useful in practice as it requires re-computation of previous steps. To improve on that, we develop an imperative version of the semantics that avoids recomputation of prior stream states. We empirically evaluate the performance of the imperative semantics using a staged interpreter written in OCaml, which, for an input program in W, produces a specialized OCaml program, which is then fed to the optimizing OCaml compiler. the approach provides a convenient path from the high-level semantical description to low-level efficient code.

关键词： Digital Signal Processing programming Language Semantics Synchronous programming Formal Verification Linear Time-invariance

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Weather Prediction in Agriculture Yields with Transformer Model 9th

Weather Prediction in Agriculture Yields with Transformer Mo...

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9th international conference on Computer Science and Computational Intelligence, ICCSCI 2024

作者： Arifin, Yulyani Sonata, Ilvico Maryani Gunawan, Elizabeth Paskahlia Computer Science Department Binus Graduate Program Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia

Agriculture has a lot of relations with SDG from United Nations especially in end hungers and sustainable agriculture. One of factor important in agriculture is weather. Weather prediction is very important in agriculture. Weather greatly influences agricultural yields and the types of crops to be planted. Weather predictions, especially temperature and humidity, can be done using time series data analysis. Current developments in deep learning enable more accurate predictions of temperature and humidity based on time series dataset. Some deep learning models can be used to predict data based on training using time series data. the deep programming models used include Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). the Transformer deep learning model, which was first introduced in 2017, is a sequence-to-sequence model which is very suitable for predicting time series data. this paper will explain temperature and humidity prediction using the Transformer deep learning model. Experimental results show that the Transformer model can predict temperature and humidity based on training results using a time series dataset. the accuracy obtained by the Transformer deep learning model is better compared to the LSTM deep learning model as indicated by lower MAE, MSE and RMSE values compared to the LSTM model. © 2024 the Authors.

关键词： Prediction models

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Optimizing the Process of Scenario-driven V2X Applications Testing

Optimizing the Process of Scenario-driven V2X Applications T...

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international conference on Computers, Communications, and Systems (ICCCS)

作者： Sali Moussa Junyan Ma School of Information Engineering Chang'an University Xi'an China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

this paper aims to optimize the V2X (Vehicle-to-Everything) application testing process by minimizing evaluation time and maximizing resource utilization in a given test field. Our contributions include (1) Development of the Maximization of Scenarios per Km for a Given Test Field (MSK-GTF) algorithm. this algorithm finds the optimal route to maximize the number of scenarios per distance, optimizing resource usage and evaluation time. (2) Introduction of the Optimal Route Search for given test case scenarios (ORS-GTCS) algorithm. ORS-GTCS identifies the optimal route, minimizing costs while fulfilling the required test scenarios. It employs mixed-integer linear programming for optimization.

关键词： Costs Roads Planning Mixed integer linear programming Resource management Vehicle-to-everything Optimization

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