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Applying augmented reality (QR-code) in English language classroom 15

Applying augmented reality (QR-code) in English language cla...

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15th international conference on Emerging Ubiquitous systems and Pervasive networks / 14th international conference on Current and Future Trends of Information and communication Technologies in Healthcare, EUSPN/ICth 2024

作者： Tukhtabayeva, Assel Kenzhebekova, Altynay Utemuratova, Alima Amanbekova, Nurganym Naubay, Balgat Tuzelbayeva, Diana Kazakh Ablaikhan University of International Relations and World Languages 200 Muratbayev str. AlmatyA05A2K5 Kazakhstan International Information Technology University 34/1 Manas str. AlmatyA15M0F0 Kazakhstan

the article describes the possibilities of QR codes as augmented reality technologies for creating a modern educational environment, that ensures individualization, differentiation and visibility of learning. Applying QR codes for language teaching is the example of successful incorporation of a mobile technology, which allows educators to draw on the motivational value of technology while using tools that are fit for the purpose of effective instruction. the object of this study is the application of QR codes in the English language classroom as a tool for enhancing student engagement and facilitating learning through interactivity Students see QR codes everywhere outside the classroom, which makes them fascinated at the prospect of using this technology in their own classroom. Similarly, teachers are eager to adopt new technologies that are easy to use and efficient in educational process. this article aims at familiarizing participants with this very practical and efficient mobile tool, first providing theoretical background explaining what QR codes are and how the use of QR codes enhances classroom instruction. this discussion will be followed by a hands-on training session where the participants will be guided through the steps of creating URLs and QR codes for classroom use. In addition, the author will share practical ideas on how these codes can be used in various ways including sample assignments and projects. © 2024 the Authors.

关键词： Educational technology

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Analysis and Design of a Helical Leaky-Wave Antenna for Satellite communications 14

Analysis and Design of a Helical Leaky-Wave Antenna for Sate...

引用

14th international conference on communications, COMM 2022

作者： Aloman, Alexandru Poveda-Garcia, Miguel Grecu, Ionut-Valentin Druta, Nicusor Nicolaescu, Ioan Military Technical Academy 'Ferdinand i' Department of Electronic Systems and Military Equipment Bucharest Romania Technical University of Cartagena Department of Communication and Information Technology Cartagena Spain

ISBN: (纸本)9781665494854

A leaky-wave (LW) feeder for non-parabolic reflectors is presented in this paper. It is based on a coaxial line with a helical periodic slot along it to achieve circular polarization and optimum reflector illumination. Full-wave simulation results show the high flexibility to control the radiation from the LW feeder by changing the slot width and periodicity. the design process, based on an in-house CAD tool to efficiently obtain the dimensions of the LW feeder given the desired radiation performance, is also presented. the obtained scanning range of the LW feeder from-90° to 10°, by changing the slot periodicity in the Ku-band at 11.85 GHz, shows the capability to adapt to different reflectors' shape. Efficiencies up to 90% are reported for the LW feeder, making this proposal very suitable for space applications. © 2022 IEEE.

关键词： Reflection

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Performance and Efficiency Analysis for Lithium-ion Battery Using State of Charge Method 14

Performance and Efficiency Analysis for Lithium-ion Battery ...

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14th IEEE international conference on Computational Intelligence and communication networks, CICN 2022

作者： Udeze, Walter Musa, Sarhan M. Prairie View A&m University Department of Electrical and Computer Engineering Prairie ViewTX United States

ISBN: (纸本)9781665487719

Companies throughout the world are making an innovative switch from oil and gas to renewable energy sources, such as wind and solar power. As the world transitions to renewable energy, the demand for electric vehicles (EVs) has increased significantly. EVs mainly use Lithium-ion batteries because of their durability and efficiency. However, as the number of Lithium-ion batteries increases with the goal of reduction of emission and low energy cost, it comes with a major drawback of safety which affects efficiency. To address these challenges, this study investigates ways on how to improve the storage management system in an EV. In this research, different Lithium-ion battery states of an EV were monitored to effectively improve the battery management system (BMS). Two different drive cycles, federal test procedure (FTP) 75 and wide-open throttle (WOT) simulation time of 2474 seconds are used to obtain the results. the implementation of State of charge (SOC) technique has been applied to evaluate the energy remaining in the battery as well as the aging effects/dynamic load. the results obtained show a rate that gradually slows down in a linear manner. In addition, EVs have a less likely chance of experiencing power loss due to a very sophisticated gear system and it is very similar to a hybrid electric vehicle or internal combustion engine. © 2022 IEEE.

关键词： Battery management systems

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UQU GIS-based Navigation System 14

UQU GIS-based Navigation System

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14th IEEE international conference on Computational Intelligence and communication networks, CICN 2022

作者： Obaidi, Shoaib Shahzad Tarmissi, Khalid Shalan, Atef Alotaibi, Saud S. College of Computer Science and Information System Computer Science Department Makkah Saudi Arabia College of Engineering and Computing Engineering Department Georgia United States

ISBN: (纸本)9781665487719

Umm al Qura University is one of the largest universities in the kingdom of Saudi Arabia, having more than one hundred thousand students. the university is situated in a suburb area of Makkah city;around 10 km away from the residential areas, and because of its geographic location, most of the people who are either students, professors, staff, workers, or even visitors enter the university compound daily for different purposes;like studying, teaching, working or perhaps just for a tour, and they all get into the university using vehicles. So, because of the vast area of the university which embeds tens of faculty buildings, scientific and technical research centers, and many other facilities, many students and visitors cannot reach their desired locations at an appropriate time. the problem gets doubled in the first few days of the university startup, and that's because of freshmen students' enrollment. To solve this problem, an online navigation system is built to help people find their destinations quickly. the platform acts as an outdoor kind of navigation system that shows the routes for buildings based on the user's search input or selection, then relatively the system will show the exact vehicle routes to the predefined appropriate parking lot, with a pedestrian path stretching to the destination and some statistical information about the buildings along with some panoramic photos of the classes are shown on the right side of the map. © 2022 IEEE.

关键词： Geographic information systems

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the Effect of Human Blockage on the Performance of RIS aided Sub-thz communication System 14

The Effect of Human Blockage on The Performance of RIS aided...

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14th IEEE international conference on Computational Intelligence and communication networks, CICN 2022

作者： Nor, Ahmed M. Fratu, Octavian Halunga, Simona University Politehnica of Bucharest Telecommunications Department Bucharest Romania Aswan University Electrical Engineering Department Aswan Egypt

ISBN: (纸本)9781665487719

5G and beyond networks have been the main focus of wireless communication society nowadays. One candidate of these networks is the usage of sub-terahertz (sub-thz) band. However, it suffers badly due to blockage whether it causes by objects or human bodies. Reflecting intelligent surfaces (RISs) is used to eliminate the effect of blockage by implementing it as an assistant to sub-thz access points (APs). In which, RISs can provide alternative line of sight (LOS) links between transmitter (TX) and receiver (RX), when the main TX-RX link is blocked. By optimal placement of RISs, they succussed in solving blockage due to static objects. But, human bodies blockage, which cannot be known and is difficult to be predicted, is still under question to model its effect on the system. In this paper, the effect of human blockage is studied under realistic scenarios in 150 thz band, where the link blockage is assumed to occur for both the direct (LOS) TX-RX link and the alternative TX-RIS-RX links. Furthermore, a trustable human blockage model, Geometrical Empirical model, is considered to describe human obstacles. In addition, we present the effect of RX height on the blockage occurrence. In our simulation results, we study the impact of blockage on the performance of RIS aided sub-thz communication system in terms of the spectral efficiency and outage probability. © 2022 IEEE.

关键词： 5G mobile communication systems

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A Competition-Based Clustering Algorithm in Ultra-Dense Network 11

A Competition-Based Clustering Algorithm in Ultra-Dense Netw...

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2023 IEEE 11th international conference on Information, communication and networks, ICICN 2023

作者： Liang, Yanxia Zhao, Zhiheng Liu, Xin Zhao, Meng Zhao, Songlin Xi'An University of Posts and Telecommunications Dept. Shaanxi Key Laboratory of Information Communication Network and Security Xi'an China Xi'An Eurasia University Dept. School of Information Engineering Xi'an China

ISBN: (纸本)9798350314014

Ultra-dense network (UDN) is the key technology to meet the future trend of network densification. In order to solve the serious interference problem between users in UDN, a competition-based clustering algorithm is proposed. Two competition rules are introduced: the reserve user selection rule, which alternatively selects the user with the least interference with the last user to join the competing cluster as the reserve user;and the competition winning rule, which minimises the sum of the interference between the reserve user and the competing cluster. Based on the above rules the rest of the users are continuously divided into the participating competing clusters. Simulation results show that the algorithm is more effective in improving system throughput compared to other algorithms, especially for edge users. © 2023 IEEE.

关键词： Clustering algorithms

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OSNR Monitoring Using Mean and Variance Values of Signal Amplitude Combination with DNNs 14

OSNR Monitoring Using Mean and Variance Values of Signal Amp...

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14th IEEE international conference on Advanced Infocomm Technology (ICAIT)

作者： Lu, He Wu, Guangzhe Li, Bozhong Yang, Yue Huang, Chao Long, Han Wu, Jianjun Duan, Mingxiong State Grid Informat & Telecommun Brand Beijing Peoples R China Accelink Technol Co Ltd Wuhan Peoples R China State Key Lab Opt Commun Technol & Networks Wuhan Peoples R China

ISBN: (数字)9781665471565

ISBN: (纸本)9781665471565

Optical Signal-to-Noise Ratio (OSNR) is one of the most important parameters in the physical layer of optical fiber communication system. It can directly reflect the operation and signal transmission state of the system. In order to ensure the reliability and stability of optical fiber communication system, an OSNR monitoring method using the mean and variance value in different regions of the received signal amplitude combination with deep neural networks is demonstrated. the OSNR-depended features are obtained by calculating the mean and variance value in different regions of the amplitude histogram firstly. then, the OSNR depended specific features are extracted and corresponding OSNR value is estimated utilizing the DNN. the back-to-back simulation results show that the OSNR of 28-GBaud polarization multiplexing (PDM) QPSK, PDM-16QAM and PDM-32QAM signals can be accurately monitored within the OSNR range of 8 similar to 21dB, 12 similar to 25dB and 18 similar to 36dB, respectively. At the same time, the long-distance transmission results show that this method is robust to fiber nonlinearity.

关键词： OSNR monitoring Deep Neural networks (DNN) coherent optical fiber communication Polarization Division Multiplexing (PDM)

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MCORANFed: communication Efficient Federated Learning in Open RAN 14

MCORANFed: Communication Efficient Federated Learning in Ope...

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14th IFIP Wireless and Mobile Networking conference (WMNC) - Artificial Intelligence and networks of the Future

作者： Singh, Amardip Kumar Nguyen, Kim Khoa Synchromedia Lab Ecole Technol Superieure Montreal PQ Canada

ISBN: (数字)9783903176522

ISBN: (纸本)9783903176522

To bring network intelligence closer to the end devices, Open Radio Access networks (O-RAN) specifies a disaggregated and vendor agnostic framework of hierarchical processing units. Although this framework can be useful for certain use cases of 50 smart services, no standardised method to train Machine Learning (ML) models has been defined. Recently. Federated Learning (FL) has emerged as a promising solution for training in disaggregated systems. Unfortunately, the stringent deadline of O-RAN control loops and fluctuating network bandwidth poses challenges for FL Implementation. In this paper, we tackle this problem by proposing an accelerated gradient descent method to expedite the FL convergence, and a compression operator to reduce the communication cost. We formulate a joint optimization problem to select the participating local trainers in each global round of FL and allocate the resources to these trainers while minimizing the overall learning time and resource costs. We design an FL algorithm (MCORANFed) which adheres to the deadline of O-RAN control loops. Extensive experimental results show that MCORANFed outperforms state-of-the-art FL methods such as MFL, FedAvg, and FedProx in terms of its convergence and objective costs.

关键词： Federated Learning O-RAN 5G Resource Allocation RAN Intelligent Controller Network Slicing RIC

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Satellite Network Handover Scheme Based on Improved Deep Reinforcement Learning in Smart Grid systems 14th

Satellite Network Handover Scheme Based on Improved Deep Rei...

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14th international conference on Computer Engineering and networks, CENet 2024

作者： Wang, Ben Zhu, Xiaojuan Gao, Jianxin Xu, Qi Yang, Yang Beijing FibrLink Communications Co. Ltd. Beijing 100071 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9789819649624

Low Earth Orbit (LEO) satellites provide wide coverage and low-latency communication services, serving as an important supplement to ground communication systems. Due to the limited service time of individual LEO satellites, efficient handover strategies between LEO satellites are crucial to maintain continuous and reliable communication. this paper considers service time, channel quality, communication capacity, and satellite network load balancing to construct an optimization model for satellite handover strategies. To address this challenge, an improved deep reinforcement learning algorithm is applied. Simulation experiments demonstrate that this algorithm effectively reduces the number of handovers and handover failures while enhancing the load balancing of the satellite network. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Handover Reinforcement learning Satellites

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An Efficient Algorithm for Plant Disease Detection Using Deep Convolutional networks 14

An Efficient Algorithm for Plant Disease Detection Using Dee...

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14th IEEE international conference on Computational Intelligence and communication networks, CICN 2022

作者： Nayar, Pratibha Chhibber, Shivank Dubey, Ashwani Kumar Amity School of Engineering and Technology Amity University Uttar Pradesh Dept of Electronics & Communication Engineering Uttar Pradesh Noida India

ISBN: (纸本)9781665487719

Plant diseases and pests are important factors in determining crop yield and quality. Plant diseases are not only a threat to food security on a global scale but can also have devastating consequences for farmers whose livelihood depend on healthy crops. the detection of plant diseases is of fundamental importance in practical agricultural production. It controls the growth and health of the plant and ensures the regular operation and successful harvest of agricultural plantations. the disease affecting the plants is determined by factors such as the climate. this paper examines an alternative approach to developing a disease detection model supported by leaf classification using deep convolutional networks. Growth in computer vision present a scope to broaden and boost the practice of precision crop protection and expand the market for computer vision applications in precision agriculture, a completely unique form of training and therefore the technique used allows for quick and direct implementation of the system in practice. the database used in this paper consists of 77,000 images of healthy and infected plant leaves. We were able to train a CNN model for classifying plant diseases that is, they are present or not, and then another model was trained with YOLOv7 to detect the disease. the trained classification model achieved an accuracy of 99.5% and the detection model was able to achieve mAP, precision, recall of 0.65, 0.59and 0.65 respectively. © 2022 IEEE.

关键词： Convolutional neural networks

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