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Telecommunications Forum (TELFOR)

作者： Alexandru Dinca Nicoleta Angelescu Loretta Ichim Trandafir-Liviu Serghei Dan Popescu Faculty of Automatic Control and Computer Science National University of Science and Technology Politehnica Bucharest Bucharest Romania Faculty of Electrical Engineering Electronics and Information Technology Valahia University of Targoviste Targoviste Romania

Timely pest detection and identification is critical as part of modern agriculture. Halyomorpha Halys is a prevalent pest with proven harmful impacts on numerous crops and agricultural regions. The paper proposes an efficient model to improve the detection of two invasive stink bugs: Halyomorpha halys and Nezara Viridula. Automatic detection of these two bugs is essential in various fields, such as precision agriculture and integrated pest management. The high performances obtained in the present study open new perspectives for the further development of insect pest detection systems and can serve as a basis for future modifications and improvements of these models.

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A Deep Learning Framework with Learning without Forgetting for Intelligent Surveillance in IoT-enabled Home Environments in Smart Cities

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2025年

作者： Dalal, Surjeet Dahiya, Neeraj Verma, Amit Faujdar, Neetu Rathee, Sarita Jaglan, Vivek Rani, Uma Le, Dac-Nhuong Department of Computer Science & Engineering Amity University Haryana Gurugram India Department of Computer Science & Engineering SRM University Sonipat Haryana Delhi-NCR India Department of Computer Science and Engineering Maharaja Agrasen University Baddi India Department of Computer Science & Applications GLA University UP Mathura India Department of Electronics and Communication Engineering School of Engineering and Technology JECRC University Rajasthan Jaipur303905 India Department of Computer Science & Engineering Amity University M.P. Gwalior India Department of Computer Science & Engineering K. R. Mangalam University Haryana Gurugram India Dean of Faculty of Information Technology Haiphong University Viet Nam

Background: Internet of Things (IoT) technology in smart urban homes has revolutionised sophisticated monitoring. This progress uses interconnected devices and systems to improve security, resource management, and resident safety. Smart cities use technology to improve efficiency, sustainability, and quality. Internet of Things-enabled intelligent monitoring technologies are key to this goal. Objectives: Intelligent monitoring in IoT-enabled homes in smart cities improves security, convenience, and quality of life from advanced technologies. Using live monitoring and risk identification tools to quickly discover and resolve security breaches and suspicious activity to protect citizens. Intelligent devices allow homeowners to remotely control lighting, security locks, and surveillance cameras. Using advanced technologies to regulate heating, cooling, and lighting based on occupancy and usage. Method: This study introduces a deep learning architecture that uses LwF (Learning without Forgetting) to keep patterns while absorbing new data. The authors use IoT devices to collect and analyse data in real-time for monitoring and surveillance. They use sophisticated data pre-processing to handle IoT devices' massive data. The authors train the deep learning model with historical and real-time data and cross-validation to ensure resilience. Result: The proposed model has been validated on two different Robloflow datasets of 7382 images. The proposed model gains an accuracy level of 98.27%. The proposed Yolo-LwF model outperforms both the original Yolo and LwF models in terms of detection speed and adaptive learning. Conclusion: By raising the bar for intelligent monitoring solutions in smart cities, the suggested system is ideal for real-time, adaptive surveillance in IoT-enabled households. By embracing adaptability and knowledge retention, authors envision heightened security and safety levels in urban settings. © 2024 Bentham Science Publishers.

关键词： Smart homes

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Comparison of classical machine learning and ensemble techniques in the context of dengue severity prediction

Comparison of classical machine learning and ensemble techni...

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Colombian Caribbean Conference (C3), IEEE

作者： Wilson Arrubla-Hoyos Zurisaddai Seveiche-Maury Khalid Saeed Jorge Eliecer Gómez Gómez Emiro De-La-Hoz-Franco Faculty of Engineering University of Sucre Sincelejo Colombia Faculty of Computer Science Bialystok University of Technology Bialystok Poland Faculty of Engineering University of Cordoba Monteria Colombia Department Computer Science and Electronics Corporación Universidad de la Costa Barranquilla Colombia

Dengue disease, spread by mosquitoes, affects a large part of the world's population. Early diagnosis is essential to avoid its severe impacts. This paper seeks to compare classical machine learning techniques with ensemble approaches in the early classification of dengue: Dengue without alarm signs (DNWS), Dengue with alarm signs (DWWS) and Severe Dengue (SD). A dataset available at https://***/ from the Colombian government with 53,814 records and 38 attributes is used. The data are processed in Google Colab using Pandas, Matplotlib and Numpy, while Scikit-learn is used for modeling. The results are supported by a detailed confusion matrix, revealing the actual performance of each model and highlighting the superiority of the ensemble approaches over classical techniques in early dengue classification. The Stacking method achieves an accuracy (Acc) of 88%, outperforming all other techniques employed. Among the classical techniques, Decision Tree (DT) achieved the best result with an Acc of 84%. In conclusion, when contrasting the performance of classical techniques and ensemble approaches in early dengue classification, it is highlighted that the latter demonstrate robustness in terms of quality metrics, such as accuracy, recall and F1-Score. This observation suggests that ensemble approaches have the potential to overcome the limitations associated with classical techniques, resulting in more robust and accurate achievements.

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Development of IoT Solution Prototype for Reliable and Sustainable Transport System in Uncertain Epidemiological Conditions 26

Development of IoT Solution Prototype for Reliable and Susta...

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26th International Scientific Conference Transport Means 2022

作者： Patlins, A. Bekeris, M. Riga Technical University Faculty of Electrical and Environmental Engineering Institute of Industrial Electronics and Electrical Engineering Kipsalas street 6A RigaLV-1048 Latvia Riga Technical University Faculty of Computer Science and Information Technology Kipsalas street 6A RigaLV-1048 Latvia

In the frame of current research authors has developed a prototype of the Internet of Things, which reflects the obtained measurement data, in real time. The resulting data provides a convenient opportunity to analyze the quality of air in public transport vehicles - humidity, level of CO2 and temperature. Developed also notifications component, records can be filtered from the selected database if the defined CO2, temperature or humidity measures are exceeded. Using developed prototype, experiments (measurements) were performed in public transport company's "Rīgas Satiksme" vehicles such as: trolley bus, tram and bus. The goal was to determine if air is being ventilated in public transport in a sufficient level, as well as to observe the temperature and humidity differences during the routes. Results of research are positive and authors can make assumption about the possibility to use such kind of IoT prototypes to make public transport system more reliable and sustainable also in uncertain epidemiological conditions. © 2022 Kaunas University of technology. All rights reserved.

关键词： Carbon dioxide

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Hospital Out Patient Visit Forecasting using Gated Recurrent Unit

Hospital Out Patient Visit Forecasting using Gated Recurrent...

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International Conference on Information Systems and computer Networks (ISCON)

作者： Krishna Thapa Arun K. Timalsina Faculty of Management Nepal College of Information Technology Pokhara University Kathmandu Nepal Department of Electronics and Computer Engineering Pulchowk Campus Institute of Engineering Tribhuvan University

Recently, people have become more interested in their healthcare and well-being, resulting in a significant increase in patient flow for healthcare providers. To provide quality care, hospitals must manage patient flow and resources effectively. Hospitals need to forecast daily patient flow in the Out Patient department to ensure they have enough resources to provide care to all patients, manage resources efficiently, reduce wait times, and improve patient satisfaction. This study is about optimizing patient visit forecasting using deep learning techniques on univariate time series data. The LSTM-based deep learning approach is a reliable module for forecasting such data, however, an enhanced version of LSTM called GRU produced even more effective results. The experimental data from a private hospital’s daily outpatient visits over the last 5 years verified that the GRU model achieved a higher accuracy of 92.42% before 1 minute 29 seconds compared to the LSTM model whose accuracy of 87.15% on an average time of 13minute 8 seconds.

关键词： Deep learning Hospitals Computational modeling Time series analysis Logic gates Data models computer networks

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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Electronic engineering (ICEEM), International Conference on

作者： Mahmoud Elshabrawy Marwa M. Eid Abdelaziz A. Abdelhamid El-Sayed M. El-Kenawy Abdelhameed Ibrahim Dept. of Communications & Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Dep. of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Engineering and Control Systems Dept. Faculty of Engineering University Mansoura Egypt

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models.

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The Gm System for the use of AGMR System 4

The Gm System for the use of AGMR System

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Verma, Aditya Al-Jawahry, Hassan M. Alsailawi, H.A. Kirubanantham, P. Sherineliyas Saadoun, Osama Nazim Manalmoradkarim Zaidan, Doaa Talib Department of Cse Graphic Era Hill University Uttarakhand Dehradun248007 India Graphic Era Deemed to Be University Uttarakhand Dehradun248007 India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq University of Kerbala College of Medicine Department of Chemistry and Biochemistry Kerbala56001 Iraq Srm Institute of Science and Technology School of Computing College of Engineering and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur SRM Nagar Chennai India Hindustan Institute of Technology and Science Department of Computer Applications India Al-kunooze University College Law Department Basra Iraq National University of Science and Technology College of Pharmacy DhiQar64001 Iraq Kut University College Department of Laser and Optical Electronics Engineering Al Kut Iraq

ISBN: (纸本)9798350360165

Due to its ability to navigate crop fields with ease, mobile robots have become more important in the agricultural industry. This study discusses a number of important topics related to agricultural robot navigation, including mapping, localization, route planning, obstacle detection, and controlled guidance. With laser-based weeding tools installed, the suggested Guiding Manager aims to maximize tracking performance of mobile autonomous robots. Integrating spiral, lateral, and linear speed controls, the system can accommodate a variety of trajectories, including curves and straight lines, that are seen in agricultural settings. To confirm the performance of the controllers under various conditions, such as loose soil, stones, and humidity, a thorough field test is conducted on a tracked mobile platform. With the Lateral Controller, the average angular error is around -0.005 rad, and the average absolute lateral error is approximately 0.09 m. In contrast, the average absolute lateral error and angular inaccuracy displayed by the Spiral Controller are 0.15 m and 0.013 rad, respectively. The system guarantes the safe and accurate implementation of robotic tasks in agriculture, as shown by its ±0.009 rad angular precision and ±0.015 m horizontal accuracy. © 2024 IEEE.

关键词： Agricultural robots

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SWIPT-enabled Cell-free Millimeter-wave MIMO with Multiple IRSs

SWIPT-enabled Cell-free Millimeter-wave MIMO with Multiple I...

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IEEE Globecom Workshops

作者： Tan Do-Duy Nguyen Thi Thanh Van Nguyen Cong Luong Dusit Niyato Faculty of Electrical and Electronics Engineering Ho Chi Minh City University of Technology and Education Vietnam Faculty of Electrical and Electronic Engineering PHENIKAA University Hanoi Vietnam Faculty of Computer Science PHENIKAA University Hanoi Vietnam School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we investigate a simultaneous wireless information and power transfer (SWIPT)-enabled cell-free millimeter-wave multiple-input multiple-output (MIMO) system. Therein, multiple base stations (BSs) serve multiple users by using the SWIPT based on power-splitting (PS) protocol. To further improve the system throughput and harvested energy, multiple intelligent reflecting surfaces (IRSs) are deployed. We formulate an optimization problem that aims to optimize the beamformers of the BSs, phase shifts of the IRSs, and PS factors at users to maximize the minimum energy efficiency of the users. The max-min energy efficiency optimization problem is computationally intractable, and we propose an alternating descent algorithm to solve it with low computational complexity. Simulation results demonstrate the effectiveness of the proposed algorithm.

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Design and Performance Analysis of a 38 GHz Microstrip Patch Antenna with Slits Loading for 5G Millimeter-Wave Communications

Design and Performance Analysis of a 38 GHz Microstrip Patch...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Mohammed A. M. Ali AbdulGuddoos S. A. Gaid Mamoon M. Saeed Rashid A. Saeed Dept. of Communications & Computer Faculty of Engineering & Information Technology Taiz University Taiz Yemen Dept. of Communications & Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Sana'a Yemen Dept. of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia

In this paper, we present a compact, rectangular microstrip patch antenna with small rectangular slits designed for 5G wireless applications in the 38GHz band. The antenna is built on a Roger RT duroid 5880 substrate with a relative permittivity of 2.2, a height of 0.381 mm, and a loss tangent of 0.0009. The microstrip line technique is utilized for power feeding to the radiating patch. To enhance the antenna's performance, three slits are incorporated into the front side of the radiating patch. The design, simulations, and optimizations are conducted using the High-Frequency Structure Simulator (HFSS), while computer Simulation technology (CST) is used for validating the HFSS results. The antenna has a compact overall size of 6.12 × 6 × 0.381 mm 3 . Moreover, the proposed antenna exhibits impressive characteristics, including a resonance frequency of 38.67 GHz, a reflection coefficient (S11) of - 47.82 dB, and an impedance bandwidth of 2.35 GHz (37.45 GHz - 39.8 GHz). In addition, the antenna's gain varies from 7.84 dBi at the lower frequency of the operational band to 7.9 dBi at the higher frequency, with a maximum gain of 8.037 dBi at the resonance frequency. Likewise, the radiation efficiency is above 99% across the operational band. The results obtained from both simulators are in a good agreement and surpass those of many previously published antennas, indicating that the proposed antenna is a promising solution for 5G wireless communication applications.

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Compact Dual-Band Printed MIMO Antenna with Very Low Mutual Coupling for WLAN, Wi-MAX, Sub-6 GHz 5G and X-Band Satellite Communication Applications

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Progress In Electromagnetics Research C 2021年 117卷 99-114页

作者： Babu, Kommanaboyina V. Das, Sudipta Lakrit, Soufian Patel, Shobhit K. Madhav, Boddapati T. P. Medkour, Hicham Department of Electronics and Communication Engineering Vasireddy Venkatadri Institute of Technology Guntur India Department of Electronics and Communication Engineering IMPS College of Engineering and Technology W.B India Mathematics and Information Systems Laboratory EST of Nador Mohammed First University Oujda Morocco Departmnt of Electronics and Communication Engineering Marwadi University Gujarat Rajkot India Computer Engineering Department Marwadi University Gujarat Rajkot India Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation AP Guntur India Department of Electronics Faculty of Technology Ferhat Abbas University Setif 1 Setif19000 Algeria

In this paper, a dual-band modified multiple-input-multiple-output (MIMO) antenna with high isolation is presented and discussed. The proposed compact structure (35×25 mm2) consists of two monopole elements and defected ground planes to obtain high impedance bandwidth. Two elliptical-shaped patches are placed orthogonal to each other to obtain high isolation, and a neutralization slit is integrated into the ground plane of each element to further improve the isolation between the elements. The measurement results of the proposed structure show satisfactory agreement with the simulation results. The measured bandwidths are 47.05% (2.6–4.2 GHz) and 64.72% (5.11–10 GHz) at S11 ≤ 10 dB which covers bandwidth requirements of WiMAX (3.4–3.6 GHz, 5.25–5.85 GHz), sub 6 GHz 5G band (3.4–3.8 GHz), WLAN (5.15–5.35 GHz, 5.725–5.825 GHz), and X band satellite communication systems (7.25–8.39 GHz). The designed antenna offers a peak gain of about 9.0 dBi and radiation efficiency of about 92%. The measured minimum isolation is greater than 27.3 dB across the dual band with a maximum value of 73.4 dB. The envelope correlation coefficient (ECC) is below 0.0035, channel capacity loss less than 0.37 bits/s/Hz, and peak diversity gain about 10 dBi. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Satellite communication systems

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