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Parts-of-Speech Tagger in Assamese Using LSTM and Bi-LSTM 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2023

作者： Phukan, Rituraj Baruah, Nomi Sarma, Shikhar Kr. Konwar, Darpanjit Dibrugarh University Dibrugarh786004 India Gauhati University Guwahati781014 India

ISBN: (数字)9789819995240

ISBN: (纸本)9789819995233

Parts-of-speech (POS) tagging is considered one of the most challenging fields in natural language processing (NLP). The objective of this research is to develop a POS tagger for the Assamese language. Due to the scarcity of digital linguistic resources, Assamese lacks high-performing POS taggers. To fill this gap, long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM) are explored in the proposed research to develop a POS tagger using an Assamese POS corpus. It is important to note that this experiment faced difficulties in understanding and managing natural language for computational linguistics, which was also anticipated. The Assamese corpus considered in this research comprises around 50,000 words. At the initial stage, while examining the first few sets of data, which are about 20,000 words, it was noticed that the taggers yielded satisfactory results. Based on the result derived, the Assamese corpus size has been enhanced to 50,000 words and better performance is noted in terms of accuracy rate, precision, recall, and F1-score. As a result, an accuracy of 91.20% is achieved for LSTM and 91.72% for Bi-LSTM. Concerned with substantial research from the NLP perspective for the Assamese language and for comparative purposes, a comparison between existing POS taggers in the Assamese language and the proposed work is also presented. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Long short-term memory

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Development of Automated Essay Scoring System Using DeBERTa as a Transformer-Based Language Model 1

引用

7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Susanto, Hansel Santoso Gunawan, Alexander Agung Fikri Hasani, Muhammad School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031548208

ISBN: (纸本)9783031548192

Giving an essay assignment is an important task every educational institution holds for measuring students’ understanding and ability. Teachers have a significant role in this task because they are the one who assesses the assignment. Over time, the number of students will increase too. This makes doing a manual correction become more complicated. Some downsides are taking too much time, being less objective, and many more. In the past few years, the problem of automated essay scoring has become popular. But this problem still has a big problem which makes automated essay scoring still not as good as human assessment, especially in detecting the main idea of an essay, cohesion, and coherence. The large language model (LLM) has become popular in the past few years. Some examples are transformer-based models such as BERT, RoBERTa, and DeBERTa. In this research, we implement those three models as our base layer, in which we compare the value of Quadratic Weighted Kappa (QWK) as the metric of accuracy. In conclusion, the DeBERTa-based model has the best value of QWK compared to the other two. We also implement a system using Python, that can retrieve an essay and will run the model to do the scoring automatically. We also suggest fur- ther research references that can use different datasets other than the ASAP-AES dataset for the research or try to use the GPT-based language model as the base layer model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Python

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Matched Filter and Kirsch’s Template Based Approach for Retinal Vessel Segmentation 1

引用

2nd International Conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2023

作者： Dash, Sonali Kaur, Kanwarpreet Bathla, Gaurav CSED Chandigarh University Mohali Gharuan India ECED Chandigarh University Mohali Gharuan India

ISBN: (数字)9789819995219

ISBN: (纸本)9789819995202

The analysis of retinal images plays an instrumental role in diagnosing Diabetic Retinopathy. This progressive disease can cause blindness which can be inhibited with earlier detection. A robust approach is presented in this paper for blood vessel segmentation by integrating a matched filter with Kirsch’s template with hysteresis thresholding. The proposed approach involved three steps: preprocessing, blood vessel extraction, and post-processing for vessel extraction. This approach achieved more accurate results than the original Kirsch’s template for specificity, sensitivity, and accuracy on the DRIVE dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blood

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Development of Intelligent Image Recognition Software Module for Sound Glasses 1

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International Scientific Conference on Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East, AFE 2022

作者： Staroverova, Natalia Shustrova, Marina Kazan National Research Technological University 68 Karl Marx Street Tatarstan Kazan420015 Russia

ISBN: (数字)9783031379789

ISBN: (纸本)9783031379772

The article describes the development of software for sound glasses. Such devices have high relevance for people with severe visual impairment. A review of wearable devices that improve user recognition of objects around the world was carried out. The process of developing an intelligent software module for recognizing urban infrastructure objects is described. The features of the software module and its architecture are described. The process and results of developing and testing a neural network for image recognition and the algorithm for identifying the color of traffic lights are also given in the article. The software module is a component of the device "sound glasses," the use of which will allow people with visual disabilities to receive information about the events taking place and the environment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Computer vision

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Secure and Energy Efficient Routing in VANETs Using Nature Inspired Hybrid Optimization 1

引用

1st International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2023

作者： Kaur, Gurjot Kakkar, Deepti Dr. B.R. Ambedkar National Institute of Technology Jalandhar India

ISBN: (数字)9789819981298

ISBN: (纸本)9789819981281

Ensuring security in Vehicular Ad-hoc networks (VANETs) has emerged as the prominent requisite prior to its deployment. Due to their open ended dynamic nature, VANETs are prone to multiple security attacks that can be mitigated using lightweight security solutions based on trust models. There is a trade-off between accuracy and delay in making a decision via trust based models. In a scenario, where the behavior of the node can be estimated by its performance in the network, artificial intelligence models have proved to be most promising in terms of accuracy and fast decision making with appropriate adaptation to the environment. Thus, in this study, we propose the combination of two nature inspired algorithms, Remora optimization and Aquila optimization to select an optimal routing path based on higher trust, higher energy efficiency and lesser delay. The performance of the hybrid combination of the proposed algorithm is compared with the individual algorithm which shows a significant improvement in overall network efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Vehicular ad hoc networks

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Skeleton Detection Using MediaPipe as a Tool for Musculoskeletal Disorders Analysis 1

引用

7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Böhm, Josef Chen, Taotao Štícha, Karel Kohout, Jan Mareš, Jan Faculty of Electrical Engineering and Informatics University of Pardubice Studentská 95 Pardubice 2532 10 Czech Republic Department of Mathematics Informatics and Cybernetics University of Chemistry and Technology in Prague Technická 1905/5 Praha 6166 28 Czech Republic

ISBN: (数字)9783031535499

ISBN: (纸本)9783031535482

Skeleton detection, also known as human pose estimation (HPE), is becoming more and more popular as it can be applied in a range of applications such as game entertainment, human-machine interaction, VR-based projects, medical rehabilitation, etc. Thanks to the booming development of deep learning, HPE solutions can be implemented using deep learning methods which require standard 2D RGB images or video sequences as input. That is, technology nowadays is making HPE solutions more and more lightweight and fast which is possible to run on mobile devices for the daily use of skeleton detection. This article covers a brief survey of current deep learning-based human pose estimation approaches in the first place. Then, a lightweight deep learning model – MediaPipe – will be illustrated from all the perspectives of its structure, working flow, strengths & weaknesses and the more concerned compatibility in platforms and programming languages. As a result, a multi-platform application for collecting movement data from patients suffering from musculoskeletal diseases relying on MediaPipe is introduced. Finally, there is a summary of achievements and obstacles of application development, which is significant as it can be a signpost for teams who are doing or about to do an application based on the MediaPipe library. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Diseases

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IoT-Based Smart Irrigation System in Aquaponics Using Ensemble Machine Learning 1

引用

6th International Conference on Soft Computing and Signal Processing, ICSCSP 2023

作者： Singh, Aishani Bajaj, Dhruv Safa, M. Arulmurugan, A. John, A. Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chennai India Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9789819984510

ISBN: (纸本)9789819984503

Aquaponics is a sustainable farming method that combines aquaculture and hydroponics to grow plants and fish in a closed-loop system. In this research paper, an irrigation system based on aquaponics is proposed, which uses real-time sensor data from the fish tank and crop soil to improve the efficiency of the system. The system is designed to make informed decisions about crop irrigation needs by visualizing the data for analytics. The study compares the accuracy of three classification algorithms, KNN, Naive Bayes, and ANN, to decide when to irrigate the soil based on real-time sensor data. The proposed irrigation system includes two sets of sensors, one for the fish tank and the other for the crop soil, which is processed by an Arduino board and sent to Adafruit’s cloud platform for visualization and analytics. This cloud-based platform allows easy access to real-time data, enabling efficient monitoring and control of the irrigation system. Additionally, the study visualizes the results obtained from using regular water and lake water in the aquaponics system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Hydroponics

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Modeling and Characterization of the Air Transport System Using System Dynamics 1

引用

7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Aseev, N.A. Kushnikov, V.A. Rezchikov, A.F. Bogomolov, A.S. Ivashchenko, V.A. Selyutin, A.D. Polyakov, M.S. Dnekeshev, A. Dranko, O.I. Baryschnikova, E.S. Stepanovskaya, I.A. Federal State Budgetary Institution Federal Research Centre «Saratov Scientific Centre of the Russian Academy of Sciences» 24 Rabochaya Street Saratov410028 Russia Saratov State University 83 Astrakhanskaya Street Saratov410012 Russia V. A. Trapeznikov Institute Of Control Sciences of RAS 65 Profsouznaya Street Moscow117997 Russia Zhangir Khan West Kazakhstan Agrarian Technical University 51 Zhangir Khan Street Uralsk090009 Kazakhstan

ISBN: (数字)9783031548130

ISBN: (纸本)9783031548123

A mathematical model of the air transport system, built using a system-dynamic approach, is proposed. With the help of the model, it is possible to improve the management of aviation transport systems according to the criterion of flight safety. When conducting experiments with the model, it is possible to predict the characteristics of the system and use the predictions when making decisions during control. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Forecasting

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Artificial Intelligence for Fault Diagnosis of Induction Motors in Manufacturing (Monitoring 4.0) 1

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International Conference on Advanced Intelligent systems for Sustainable Development, AI2SD 2023

作者： Ait Mellal, Ismail Lahbabi, Salma Dahi, Khalid Hassan II University Casablanca Morocco Benguerir Morocco Casablanca Central School Complex Systems and Interactions Research Center Ville Verte Côté Latéral Est à la forêt Boukoura Casablanca Morocco

ISBN: (数字)9783031543180

ISBN: (纸本)9783031543173

In many industrial sectors, the proper functioning of the production chain is a major issue to ensure better competitiveness in the market, so productivity gains are a major concern for companies. For this, a set of industrial performance indicators allow an optimization of the systems, namely: reliability, maintainability, safety and risk control. Nowadays, system diagnostics, which has been strongly developed in the industrial world, represents one of the most important tools to obtain a better productivity gain and to avoid unavoidable material and/or physical damages. And in this context and for several decades, scientific research and technologies have been launched worldwide to develop and improve diagnostic methods. A number of innovative companies have started to implement IoT by exploiting smart connected devices in their factories (this is called smart factories or Industry 4.0). Therefore, this research project will introduce an intelligent system into an Industry 4.0 production environment. The proposed work is based on artificial intelligence applied to the diagnostic methods of three-phase Induction machines for the early detection of defects that may appear in these machines. The use of this type of electrical machine, mainly due to their simplicity of construction, their low cost of purchase and manufacture, their robustness, we find them in all industrial areas. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Signal processing

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Study of Power Optimization Algorithms for Secure Communication with Untrusted AF Relays 1

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World Conference on Information systems for Business Management, ISBM 2023

作者： Shemi, P.M. Sabu, M.K. Department of Electronics MES College Marampally Aluva India Department of Computer Applications Cochin University of Science and Technology Kochi India

ISBN: (数字)9789819983469

ISBN: (纸本)9789819983452

This paper compares various power optimization algorithms for secure transmission in an amplify-and-forward (AF) network with multiple untrusted relay nodes and an external eavesdropper. In order to prevent the untrusted nodes from intercepting the source message and to achieve a positive secrecy rate, source-based-jamming (SBJ) is used. The optimization algorithms employed for secrecy rate maximization include the Nelder–Mead, Broyden–Fletcher–Goldfarb–Shanno, and Conjugate-Gradient methods. The performance of the untrusted relay is compared to the worst-case situation, in which it is assumed that all nodes cooperate with each other. The two-dimensional exhaustive search, derivative test, and equal power allocation (EPA) approaches are used as performance comparison benchmark systems. The analysis is done for symmetric and asymmetric relay positions and with different numbers of untrusted nodes. The complexity of the optimization algorithms has also been derived. Numerical results reveal that the optimal technique for secrecy rate maximization depends on the position of the selected relay. Also, there exists a trade-off between the complexity and convergence of the algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Jamming

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