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检索条件"任意字段=24th International Conference on Control Systems and Computer Science, CSCS 2023"

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Algorithm for Solving the Navigation Problem for Ultra-Wideband Local Navigation System Based on the Extended Kalman Filter for Time of Arrival Architecture

Algorithm for Solving the Navigation Problem for Ultra-Wideb...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Alexander A. Chugunov Roman S. Kulikov Alexander P. Malyshev Nikita I. Petukhov Sergey V. Chernyh Stepan V. Orobchenko dept. of Radio Systems National Research University MPEI Moscow Russia

At the moment, for positioning objects in local navigation systems, the difference-range method of positioning is widely used. this approach does not require synchronization of time scales on the user and system sides, allows a larger number of simultaneously tracked objects, but has a lower accuracy than the ranging method. this paper presents a new approach to solving a navigation problem for ultra-wideband local navigation systems built on a pseudorange architecture. the algorithm is based on the use of an extended Kalman filter, which makes it possible to determine the location of an object with high accuracy. A feature of the algorithm is the ability to estimate the discrepancy between the time scales of the user and the system, followed by taking into account the obtained value to correct the calculated ranges. this approach will provide a number of advantages: work on a smaller number of control points, increase in accuracy, which allows you to maintain an acceptable quality of navigation when leaving the working area. the performance and quality of the proposed algorithm were tested using computer simulations.

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Inchworm-Gecko Inspired Robot with Adhesion State Detection and CPG control 7th

Inchworm-Gecko Inspired Robot with Adhesion State Detection ...

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7th international conference on Cognitive systems and Information Processing, ICCSIP 2022

作者： Zhang, Zijian Chu, Zhongyi Zhang, Bolun Cui, Jing School of Instrumental Science and Opto-Electronics Engineering Beihang University Beijing100191 China School of Mechanical Engineering and Applied Electronics Beijing University of Technology Beijing101100 China

ISBN: (纸本)9789819906161

Although many climbing robots have been developed, working stably on complex surface in narrow space still remains a challenge. In this work, we present a miniature inchworm-gecko inspired robot (IGIR) which can achieve climbing and sensing adhesion state on different kinds of surface including flat and porous surfaces. Inspired by the inchworm’s locomotion and gecko’s adhesion mechanism, we conduct the overall system design of IGIR by using servos and connecting rods to form a motion module, the negative pressure driven gecko adhesion feet as the adhesive module, and the micro three-axis force sensor as the sensing module. Facing the problem of stable adhesion perception of climbing robots, the adhesion state detection of IGIR is realized through the sensing module and detection strategy. A novel CPG control model is established to realize the periodic gait of IGIR, and the adaptive adjustment is completed by combining the adhesion state detection information. Finally, a prototype of IGIR is made. Experiments of the prototype verify the feasibility of the proposed adhesion state detection and CPG control model of IGIR. the maximum moving speed of IGIR is 24 cm/min. Over all, this paper shows the combination of adhesion detection and gait planning for climbing robot, and provides a new way to the research of climbing robot stable locomotion. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Adhesion

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Extended HD-MAABE Scheme Supporting Delegation and Revocation for Cloud-based Organizational Data Sharing 6th

Extended HD-MAABE Scheme Supporting Delegation and Revocatio...

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6th international conference on Innovative Computing and Communication, ICICC 2023

作者： Gupta, Reetu Kanungo, Priyesh Dagdee, Nirmal School of Computer Science and Information Technology DAVV Indore India Shivajirao Kadam Institute of Technology & Management Indore India

ISBN: (纸本)9789819933143

Cloud computing facilitates data exchange and outsourcing. Any business or organization may exchange data for societal and individual benefit. Organizations lose control of their data when they upload files to the cloud. As a method of restricting access to data in a cloud setting, attribute-based encryption (ABE) has gained popularity. However, current ABE schemes have some limitations. First, contemporary ABE techniques are incapable of depicting the real-world situations of corporate data exchange, particularly when the companies are hierarchically structured. Second, they have scalability constraints when it comes to key management. third, it is necessary to streamline the revocation methods in order to accommodate hierarchical data sharing. In this paper, we extend our multi-authority scheme HD-MAABE, by incorporating a delegation service between the root master authorities and the domain master authorities, allowing for greater security and scalability. Using mediation server and keeping an attribute revocation list on the cloud server makes the revocation procedure simple. the scheme supports the LSSS policy structure’s adaptability. Proof of security is based on q-parallel BDHE security assumptions. We show that the proposed method is secure as well as computationally and functionally efficient through the use of cost analysis, feature comparison and security analysis. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Access control

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the Impact of Recommendation System Provided Based on Online Learning Readiness in the MOOC Environment

The Impact of Recommendation System Provided Based on Online...

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Information Technology (ACIT)

作者： Dina Fitria Murad Mohamad Toha Hendra Mayatopani Meta Amalya Dewi Riyan Leandros Silvia Ayunda Murad Yaya Heryadi Bambang Dwi Wijanarko Information Systems Department Binus Online Learning Bina Nusantara University Jakarta Indonesia Universitas Terbuka Jakarta Indonesia Department of Information System Pradita University Tangerang Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia

MOOCs are one of the developments or impacts of e-learning or online learning. Massive Open Online Course (MOOC) is one of the choices for students to increase their knowledge through non-formal channels. Our research aims to determine the level of readiness of students regarding MOOC learning and opportunities for utilizing recommendation systems in students' decision-making regarding selecting MOOCs that suit their interests and needs. We conducted a survey regarding the constraints and needs of learner readiness through 5 aspects, namely 1) technical aspect, (2) social aspect, (3) communication aspect, (4) lecture readiness aspect, and (5) online discussion. the results of this research show that the main challenges that MOOC participants may face in a MOOC environment are Technical Aspects (28.25%), Social Aspects (21.47%), and Communication Aspects (18.93%). Meanwhile, the greatest strength of online learning in the MOOC environment is the social aspect (21%), the most influential and continued with technical and other aspects. Meanwhile, the lecture readiness aspect is quite good, and the online discussion aspect is the biggest aspect that influences the success of MOOC learning. Other results of this research indicate the importance of a recommendation system for MOOC students to make it easier for students to choose the right MOOC according to their interests and needs.

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Decision Support System for Color control of Polymer Products Based on Fuzzy Models 24

Decision Support System for Color Control of Polymer Product...

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24th international conference on Soft Computing and Measurements, SCM 2021

作者： Chistyakova, Tamara B. Makaruk, Roman V. Tedtoev, Azamat Ch. Saint-Petersburg State Institute of Technology Department of Computer-Aided Design and Control Systems Saint Petersburg Russia

ISBN: (纸本)9781665439749

the structure of the decision support system for controlling the color characteristics of polymer products based on fuzzy models is presented, the application of which will reduce the amount of scrap in production, reduce the size of production costs, as well as reduce the degree of environmental pollution. the observed system includes a module for evaluating color characteristics from fuzzy models, which makes the system hybrid, using both deterministic and fuzzy models in work, which allows you to more efficiently and qualitatively cope with the task of analyzing the color characteristics of polymer productions. © 2021 IEEE.

关键词： Polymer films

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Data-Model Intergrowth Makes Better Time Series Prediction 4th

Data-Model Intergrowth Makes Better Time Series Prediction

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Proceedings of the 4th international conference on Neural Computing for Advanced Applications, NCAA 2023

作者： Chen, Lixian Liu, Hongda Sun, Chongqi Wang, Yi Hu, Yongheng College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9789819958467

In common prediction problems, the open-loop prediction framework is popular because of its fast prediction process and easy implementation. However, time series prediction is a special prediction problem because of the temporal nature of the time series, in which missing values are not only the target of the time series prediction, but also the flexible decision variables in the training sets of the prediction model, which indirectly control the predicted values, allowing the prediction process to be considered as a closed loop. this paper proves that the closed-loop prediction framework performs better on prediction accuracy than the open-loop framework. In this paper, the missing value prediction of the time series is modeled as a special optimization problem, in which the missing values and prediction models are decision variables constraining each other. the prediction models keep being trained on the training set containing the predicted values through iteration. the objective function is the virtual accuracy of the target dimension prediction model. When the objective function reaches its minimum, the best missing values and prediction models are given, which can solve any time series prediction problem. therefore, the method is a general closed-loop prediction framework for time series prediction. In the experiment, 5 typical machine learning models in the closed-loop framework perform better than ones in the open-loop framework on 4 datasets with different frequency characteristics. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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WHAT USERS WANT: A NATURAL LANGUAGE PROCESSING APPROACH TO DISCOVER USERS' NEEDS FROM ONLINE REVIEWS 24

WHAT USERS WANT: A NATURAL LANGUAGE PROCESSING APPROACH TO D...

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24th international conference on Engineering Design, ICED 2023

作者： Spada, Irene Barandoni, Simone Giordano, Vito Chiarello, Filippo Fantoni, Gualtiero Martini, Antonella School of Engineering Department of Information Engineering University of Pisa Italy Department of Computer Science University of Pisa Italy School of Engineering Department of Energy Systems Land and Construction Engineering University of Pisa Italy School of Engineering Department of Civil and Industrial Engineering University of Pisa Italy B4DS - Business Engineering for Data Science Lab University of Pisa Italy

Digital media are a means to deliver products and services, but also a channel to interact with consumers and a source of information on users' preferences. Data shared by customers on the web, the User-Generated Content (UGC), can give entrepreneurs a detailed perspective of the market. this work examines an application of Natural Language Processing techniques on UGC to discover insights on users' opinions. We collected more than 13.000 reviews of software from digital stores and review website to gather information on the customers' perspective and their response to a given marketing strategy in two case studies on digital product's launch. the objective is to give support to two Italian companies in the process of business model development through data-driven evidence. We aim to discover who are the users and which are their needs using a lexicon-based approach to mine unstructured text. the results provide qualitative and quantitative descriptions of the market segments. We propose a method to examine UGC and to explore customers' behavior on social media. the findings helped managers for the development of their business model, enhancing an informed decision-making process. © the Author(s), 2023. Published by Cambridge University Press.

关键词： Digital storage

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Software Module for Determining Parameters of a Bipolar Transistor SPICE-Model Using Static Volt-Ampere Characteristics

Software Module for Determining Parameters of a Bipolar Tran...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Timur I. Tretyakov Ilya I. Nikolayev Anastasiya A. Drozdova dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics (TUSUR) Tomsk Russia

A software module was developed to calculate the main parameters of the SPICE-model of a bipolar transistor based on its static volt-ampere characteristics. this software module is based on the Gummel-Poon model. To build a SPICE-model of bipolar transistors, its functionality includes graphic representation of static volt-ampere characteristics, as well as calculation and output of basic parameters of the Gummel- Poon model (saturation current, non-ideality coefficient in forward connection, base current amplification factor in forward connection, forward Earlie voltage, base resistance and collector resistance). the advantages of the developed software module are: the ability to obtain the basic parameters to build a SPICE-model of bipolar transistors with a minimum set of input data; convenient data input; graphical display of volt-ampere characteristics of the studied bipolar transistor. the disadvantages include a significant error in the calculation of saturation current, base resistance and collector resistance, but it does not have a significant impact on the characteristics of the SPICE-model. We propose a way to automate measurements of static volt-ampere characteristics of bipolar transistors using a simple device built on field-effect transistors, controlled by a microcontroller.

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Optimizing Road Safety through Intelligent Congestion Management

Optimizing Road Safety through Intelligent Congestion Manage...

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Information Technology (ACIT)

作者： Ghassan Samara Alaa Elhilo Mahmoud Rajallah Asassfeh MohammadNoor Injadat Mais Haj Qasem Raed Alazaidah Mohammad Aljaidi Nabeel Al-Milli Adnan A Hnaif Faculty of Information Technology Zarqa University Zarqa Jordan Faculty of Science and IT Al-Zaytoonah University of Jordan Amman Jordan

Intelligent transportation systems offer a promising avenue for enhancing road safety by facilitating communication between vehicles and infrastructure. this communication can significantly reduce road fatalities. Addressing congestion resulting from wireless communication between vehicles and infrastructure is a critical aspect of road safety. this paper focuses on effectively controlling this congestion while ensuring constant awareness in vehicles. the proposed technique involves determining an optimal transmission rate based on the current channel conditions, striking a balance between message awareness and congestion. this is achieved using a reinforcement learning and Markov decision process-based machine learning algorithm. Simulation results demonstrate the superiority of applying machine learning algorithms over traditional congestion control strategies. Additionally, future studies should consider incorporating other characteristics such as packet delay and packet loss for a comprehensive analysis.

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Decentralized Multi-Agent Reinforcement Learning Exploration with Inter-Agent Communication-Based Action Space

Decentralized Multi-Agent Reinforcement Learning Exploration...

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international conference on control, Automation and systems ( ICCAS)

作者： Gabriele Calzolari Vidya Sumathy Christoforos Kanellakis George Nikolakopoulos Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

A new challenging area of research in autonomous systems focuses on the collaborative multi-agent exploration of unknown environments where a reliable communication infrastructure among the robotic platforms is absent. Factors like the proximity between agents, the characteristics of the network nodes, and environmental conditions can significantly impact data transmission in real-world applications. We present a novel decentralized collaborative architecture based on multi-agent reinforcement learning to address this challenge. In this framework, homogeneous agents autonomously decide to communicate or not, that is whether to share locally collected maps with other agents in the same communication networks or to navigate and explore the environment further. the agents’ policies are trained using the heterogeneous-agent proximal policy optimization (HAPPO) algorithm and through a novel reward function that balances inter-agent communication and exploratory behaviors. the proposed architecture enhances mapping efficiency and robustness while minimizing inter-agent redundant data transmission. Finally, this paper demonstrates the advantages of the investigated approach compared to a strategy that does not incentivize communicative behaviors.

关键词： Navigation Refining Collaboration Reinforcement learning Robustness Real-time systems Space exploration Data communication Robots Optimization

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