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Design and Implementation of a Low-Cost Virtual Rifle Shooting Simulator for the Peruvian Army Military School 5

Design and Implementation of a Low-Cost Virtual Rifle Shooti...

引用

5th International conference on Electrical, Communication and computer engineering, ICECCE 2024

作者： Rondón Gómez, Luis Alonso Alarcón, Piero Arce, Diego Army Scientific and Technological Research Center Ejercito del Perú Lima Peru Pontificia Universidad Católica Del Perú Department of Engineering Lima Peru

ISBN: (纸本)9798331529437

Training personnel in the use of weapons is crucial for military effectiveness, but traditional methods require significant investments in firearms and ammunition. This challenge is particularly evident in developing countries, where military budgets are constrained. To address this, virtual rifle shooting simulators offer a cost-effective solution for enhancing military training. This paper presents the design and implementation of a low-cost virtual rifle shooting simulator for the Peruvian Army Military School. The system integrates a light automatic rifle equipped with a laser system and a computer vision-based detection mechanism for accurate shot analysis in various training environments. Additionally, an electrical recoil simulation system enhances the realism of the training experience. The proposed system was validated through shot detection and laser signal recognition tests, demonstrating high accuracy in different lighting conditions. The entire prototype was developed at a cost of USD 1,100, significantly reducing the expenses associated with traditional training methods while maintaining performance standards. This research contributes to the development of affordable and portable military training simulators, enabling broader access to advanced training technologies. © 2024 IEEE.

关键词： Budget control

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Machine Learning Based Crop Recommendation System

Machine Learning Based Crop Recommendation System

引用

2024 International conference on Advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Deo, Arpit Bandhu, Kailash Chandra Litoriya, Ratnesh Gupta, Abhay Chelawat, Purvi Gohade, Purvi Medi-Caps University Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

In a country where conventional farming methods are still widely used and often result in small yields and little profit for farmers, our goal is to increase crop yields by presenting a range of farming techniques through a recommendation system for intelligent farming. This system uses a scientific method to forecast the best crops depending on a number of important factors, such as the nutrients in the soil. It pinpoints nutritional deficits in the soil for particular crops. Our system, which is implemented as a website, makes use of crop dataset that include parameters for temperature, rainfall, pH, and humidity. It then applies a variety of ML algorithms to make accurate and efficient crop recommendations, achieving impressive metrics such as accuracy of 96.08%, precision of 93 %, and recall of 45%. © 2024 IEEE.

关键词： Crop Fertilizer Nitrogen Potasium Rainfall Recommendation

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Classification of Fluid Filled Abnormalities In Retinal Optical Coherence Tomography Images Using Chicken Swarm Optimized Deep Learning Classifier

Classification of Fluid Filled Abnormalities In Retinal Opti...

引用

2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Smida, Jamel Bose, Anandh Sam Chandra Al Jarallah, Nasser Smida, Amor Koushaji, Ghaith Al Mareefa University College of Applied Science Saudi Arabia Saveetha Engineering College Department of Biomedical Engg. Chennai India Majmaah University College of Applied Medical Sciences Saudi Arabia

ISBN: (纸本)9798350322972

Optical Coherence Tomography is a noncontact, non-invasive imaging regarded as the best diagnostic approach when compared to other imaging techniques. It provides convenience along with high resolution and is an indispensable tool utilized for the retinal disease diagnosis in clinical practice. Among retinal diseases, the vision loss is very common caused because of deficit or excess of fluid within the retinal layers. High risk for vision loss occurs due to such damages or deformations in the layers of retina. To tackle this, a deep learning approach is opted for diagnosing fluid filled abnormalities in retinal OCT images. The input image is enhanced by means of CLAHE approach and the retinal layer is segmented for the extraction and selection of relevant features. Gabor filter is adopted for the feature extraction and the selected features are further classified by RNN classifier whose parameters are trained by CSO approach. The utilized RNN provides dynamic system modelling and real-time big data classification. The proposed CSO efficiently trains the RNN parameters with increased accuracy and less time *** NEH OCT image dataset is used in MATLAB to validate the proposed approach. The obtained results demonstrate the efficacy of the proposed approach with an accuracy of 95% and reduced processing time of 545.4s. © 2023 IEEE.

关键词： Optical tomography

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An IoT-Based Sustainable Automation System for the Garments Industry in Bangladesh 3

An IoT-Based Sustainable Automation System for the Garments ...

引用

3rd International conference on Emerging Frontiers in Electrical and Electronic Technologies, ICEFEET 2023

作者： Ahmed, Khandakar Rabbi Salam, Towfika Rabbu, Mohammad Mahmudul Haque, F.M. Hasan, Nazmul Miraz, Shafiun Rana, Md. Masud Mansur, Maliha Tabassum, Humayra Shayer, Khandokar Shadman Miyan Research Institute International University of Business Agriculture and Technology Dhaka Bangladesh Dept. of Mechatronics Engineering Rajshahi6204 Bangladesh International University of Business Agriculture and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Computer Science & Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Varendra University Dept. of Computer Science and Engineering Rajshahi Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Ahsanullah University of Science & Technology-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350307399

The Readymade Garments sector accelerates Bangladesh's development. The 'Made in Bangladesh' brand has also helped to boost Bangladesh's reputation and brand recognition on a global scale. Despite its limited resources, the country has maintained a 6% annual GDP growth rate while attaining extraordinary social and human development. On the other hand, the phrase 'Internet of Things' (IoT) refers to a broad concept that can be summarized as an ecosystem of intelligent gadgets equipped with networks, sensors, and processing tools. IoT is a new technological platform that enables the many objects in our environment to connect via sensors and the Internet to improve our quality of life. Manufacturing and the industrial sector, agriculture, the health sector, smart cities, security, and emergency services, to name a few. IoT implementation in the garment sector would open a new door to growth in production and worker safety. Implementing home automation and safety systems in the garment sector will help in production and ensure the safety of the workers. The suggested IoT -based sustainable automation system for the Bangladeshi garments sector is efficient, eco-friendly, secure, reliable, and user-friendly. The system's user-friendly interface makes it straightforward to use and manage. The Bangladeshi garments industry's IoT -based sustainable automation system is a comprehensive and integrated solution that addresses the industry's primary difficulties and provides a sustainable and viable future. © 2023 IEEE.

关键词： Internet of things

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Implicit Modeling Network of Human Critical Points based on Attention Mechanism 7

Implicit Modeling Network of Human Critical Points based on ...

引用

7th IEEE Information Technology and mechatronics engineering conference, ITOEC 2023

作者： Su, Xiaodong Chen, Xu Zhao, Jiayuan Zhang, Fengchun Xu, Hongyan Harbin University of Commerce College of Computer and Information Engineering Harbin China Key Laboratory of Electronic Commerce and Information Processing Harbin China

ISBN: (纸本)9798350334197

Human pose estimation tasks require the use of visual cues and anatomical relationships between joints to locate key points, but convolutional neural network-based approaches have difficulty focusing on remote contextual cues and modeling the dependencies between distant joints. In this paper, we propose an implicit modeling method based on an attention mechanism to implicitly model the constraint relationships between key points by computing feature correlations between joints through multi-stage iterations. To address the problem that the network may weaken the invisible key points during training, a focal loss function is used to make the network more focused on complex key points. The experimental results show that the implicit modeling network can improve the performance of the human posture estimation network, and the algorithm with the HRNet network as the backbone network can improve the performance of the human posture estimation network in the MPII dataset, the benchmark dataset for human posture estimation, compared with the original network. The accuracy of the algorithm with HRNet network as the backbone was improved by 1.7% compared to the original network. © 2023 IEEE.

关键词： Convolutional neural networks

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A technique of internal relative transmission delay measurement and positioning error correction for GNSS pseudo-satellite systems 7

A technique of internal relative transmission delay measurem...

引用

7th IEEE Information Technology and mechatronics engineering conference, ITOEC 2023

作者： Liang, Yuexian Zhao, Li Cheng, Yao Li, Chunhui Guilin University of Electronic Technology School of Computer Science and Engineering Guilin China Guilin University of Electronic Technology Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin China

ISBN: (纸本)9798350334197

Internal transmission delay is one of the inherent system parameters of pseudo-satellite transmitters, and it is also one of the factors affecting the positioning service accuracy of pseudo-satellite systems. Aiming at the influence of the internal delay inconsistency deviation caused by the inconsistent components characteristics of different pseudo-satellites, a method of relative delay mensuration and compensating inside the pseudo-satellite transmitter is proposed. According to the structural characteristics of pseudo-satellite transmitter and receiver, a transmission delay measurement model is established, the total transmission delay of the pseudo-satellite transceiver system is measured by high-precision instruments, and the relative internal transmission delay between other pseudo-satellites is obtained by difference method based on one of the pseudo-satellites. Starting from the carrier phase observation equation, the positioning correction model based on single-difference carrier phase is established, and the measured value is converted into the delay compensation factor in the positioning algorithm model for positioning solution. Through the comparative analysis of the experimental results of the positioning solution before and after correction, the method can improve the positioning accuracy effectively, and the feasibility of the method is verified. © 2023 IEEE.

关键词： Error correction

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A framework for An Intelligent Agro-Climate Decision Support System for Small-scale farmers in Swayimane

A framework for An Intelligent Agro-Climate Decision Support...

引用

2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Thothela, Naledi Portia Markus, Elisha Masinde, Muthoni Abu-Mahfouz, Adnan Central University of Technology Department of Information Technology Bloemfontein South Africa Central University of Technology Department of Electrical Engineering Bloemfontein South Africa Council for Science and Industrial Research Department Industrial Research Pretoria South Africa

ISBN: (纸本)9798350322972

Machine Learning (ML) is fast becoming a technology of choice with enormous potential to transform small-scale agriculture, particularly in helping farmers make informed decisions about crop choices. On the other hand, there is evidence that small-scale farmers face several challenges, such as lack of access to market information, poor soil quality, and inadequate farming techniques. ML technology can be used to provide real-time information on weather patterns, soil quality, and other factors that affect crop growth and yields. By providing this information, ML can help farmers choose the right crops to plant and optimize their yields. In this paper, the authors report on the use of AI to select the appropriate crop to plant, which resulted in crop choices that are 99% accurate. This was achieved by collecting climatic and edaphic data, and using different multi-class classification algorithms to train the dataset. The results of the different algorithms were compared and contrasted using different metrics to determine the best fit for the development a framework for prediction of crop suitability at pre-planting stage. The resulting framework utilizes ML as well as observed Indigenous Knowledge (IK) to synthesize edaphic and climatic factors to support decision management for small-scale farmers. © 2023 IEEE.

关键词： Crops

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Implementation of Data science Techniques in the ACM Computing Classification System

Implementation of Data Science Techniques in the ACM Computi...

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2022 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2022

作者： Tomé, Paulo School of Technology and Management Computer Science Department Viseu Portugal

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In 2012, ACM defined a Computing Classification System (CCS), which substitutes an older version developed in 1998. This CCS relies on a semantic vocabulary as the single source of categories and concepts that reflect the state of the art of the computing discipline. This paper shows the application to the CCS of two Data science techniques used for classification tasks: Naive Bayes (NB) and Convolutional Neural Network (CNN). The project comprises two tasks: developing a framework with the general roles and data structure and applying NB and CNN to CCS classification. After the adjustment of some model parameters, the results are promising. The classification with NB provides an accuracy of 74%, while the accuracy with CNN was 72%. © 2022 IEEE.

关键词： Convolutional neural networks

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Optimizing the Tobacco Leaf Quality Assessment System via Grey Relational and Circle Ill-Condition Index Analysis 24

Optimizing the Tobacco Leaf Quality Assessment System via Gr...

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7th International conference on Information Management and Management science, IMMS 2024

作者： Cheng, Xijie Feng, Weiqing Pang, Su Hu, Gang Cai, Shimin College of Management Science Chengdu University of Technology China Faculty of Computer Science & Information Technology Universiti Malaya Malaysia Sichuan Tobacco Company Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China China

ISBN: (纸本)9798400716997

Traditional methods for assessing tobacco leaf quality rely heavily on experience and subjective judgment, resulting in inefficiency, and a lack of accuracy and reproducibility. To address these challenges, there is an urgent need for a tobacco leaf quality assessment system capable of assessing various aspects of leaf quality in a systematic and quantitative manner. In this paper, we quantitatively analyze the tobacco leaf quality assessment system for Sichuan tobacco, specifically focusing on the Yunyan 87 variety. In further, we employ Grey Relational Analysis and Circle Ill-Condition Index Analysis for indicator selection and optimization. Through quantitative analysis, key indicators that significantly impact the assessment results and exhibit low information redundancy are retained, and weights are reallocated based on correlation analysis. The optimized system retains four core indicators: Oil Content, Delicacy, Total Nicotine, and Sugar-to-Nicotine Ratio, significantly enhancing the scientific rigor and practical utility of the assessment process. This optimized assessment tool provides a scientific basis for quality control in Sichuan tobacco production, ultimately enhancing production efficiency and product quality. © 2024 ACM.

关键词： Quality control

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Utilizing a Standards-Based Toolchain to Model and Execute Quantum Workflows 24th

Utilizing a Standards-Based Toolchain to Model and Execute Q...

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24th International conference Web engineering (ICWE)

作者： Beisel, Martin Alvarado-Valiente, Jaime Barzen, Johanna Leymann, Frank Romero-Alvarez, Javier Stiliadou, Lavinia Weder, Benjamin Univ Stuttgart Inst Architecture Applicat Syst Stuttgart Germany Univ Extremadura Quercus Software Engn Grp Badajoz Spain

ISBN: (纸本)9783031623615;9783031623622

The increasing availability of quantum devices via the cloud led to a multitude of commercial and scientific tools for developing quantum applications. However, since quantum applications are typically hybrid, comprising both quantum and classical parts, these tools are very heterogeneous. Therefore, combining them within a single application is complicated by incompatible programming languages, data formats, and interfaces. Hence, to enable the development of portable and interoperable quantum applications a standards-based toolchain is required. In this demonstration, we present a holistic toolchain for developing quantum applications utilizing well-established standards for defining workflows, deployment topologies, application interfaces, and provenance data. To demonstrate the practical feasibility of our toolchain, we showcase it for two use cases from the cryptography and machine learning domains.

关键词： Quantum Computing Quantum Software engineering Hybrid Quantum Applications SoC Workflow Technology

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