Hygienic characteristic of the electromagnetic situation created by the electromagnetic radiation of the antennas of mobile base stations in Cherkasy region before and after the introduction of 4G technology

This work is part of our researches to study the distribution of electromagnetic radiation from mobile base stations in populated areas. The aim of this work was to study and analyze the electromagnetic situation before and after the introduction of fourth generation 4G technology at mobile base stations. We analyzed the maximum and average levels of electromagnetic radiation from mobile base stations located in Cherkasy region. The electromagnetic situation was studied both in urban areas and in rural areas. It was found that after the introduction of the fourth generation 4G technology at the mobile base stations, the levels of electromagnetic radiation in Cherkasy region increased significantly. The median of maximum levels of electromagnetic radiation increased by 155.6% (in particular, in urban areas by 194.1%), and the median of average levels - by 75.2% (in particular, in urban areas by 141.1%). No significant changes in electromagnetic radiation levels were detected before and after the modernization of mobile base stations in rural areas. It has been proven that there are no prerequisites for increasing the maximum permissible level to 100 μW/cm2 when implementing 4G and 5G technologies at mobile base stations.

Intelligent Interference Management in UAV-Based HetNets

Unmanned aerial vehicles (UAVs) can play a key role in meeting certain demands of cellular networks. UAVs can be used not only as user equipment (UE) in cellular networks but also as mobile base stations (BSs) wherein they can either augment conventional BSs by adapting their position to serve the changing traffic and connectivity demands or temporarily replace BSs that are damaged due to natural disasters. The flexibility of UAVs allows them to provide coverage to UEs in hot-spots, at cell-edges, in coverage holes, or regions with scarce cellular infrastructure. In this work, we study how UAV locations and other cellular parameters may be optimized in such scenarios to maximize the spectral efficiency (SE) of the network. We compare the performance of machine learning (ML) techniques with conventional optimization approaches. We found that, on an average, a double deep Q learning approach can achieve 93.46% of the optimal median SE and 95.83% of the optimal mean SE. A simple greedy approach, which tunes the parameters of each BS and UAV independently, performed very well in all the cases that we tested. These computationally efficient approaches can be utilized to enhance the network performance in existing cellular networks.

Meningkatkan kemandirian dan hasil belajar peserta didik dengan menggunakan Mobile Learning PERSIKA berbasis Ispring Suite 9 (A useful mobile base learning media in the Covid-19 era)

Perkembangan teknologi saat ini berkembang begitu pesat dan semakin canggih di semua bidang, tak terkecuali di dunia pendidikan. Teknologi saat ini mulai dimanfaatkan di bidang pendidikan yaitu di sekolah baik oleh guru dan peserta didik sebagai alat penunjang berlangsungnya kegiatan pembelajaran. Dengan adanya hal itu maka diperlukan adanya pengembangan lebih lanjut pada media pembelajaran dengan memanfaatkan teknologi yang berkembang dengan cepat dan canggih ini. Pendidikan menjadi salah satu aspek yang terdampak pandemi Coronavirus Disease (Covid-19). Penyebaran virus ini terbilang sangat cepat di Indonesia sejak awal tahun 2020, dampak dari adanya covid-19, saat ini pembelajaran dilakukan secara daring (online), sehingga guru dituntut untuk kreatif serta inovatif dalam mengoptimalkan teknologi dalam kegiatan pembelajaran. Oleh karena itu, penelitian ini bertujuan untuk menghasilkan produk Mobile Learning PERSIKA berbasis iSpring Suite 9 untuk meningkatkan kemandirian dan hasil belajar peserta didik. Produk media pembelajaran yang dikembangkan terdapat enam menu dan fitur yang mempermudah penggunaan dalam pengoperasiannya Cakupan materi yang lengkap, serta ukuran file sebesar 7,91 MB dapat membantu peserta didik dalam meningkatkan kemandirian dan hasil belajar peserta didik. Penelitian dan pengembangan ini menggunakan model Research and Development Borg and Gall yang telah dimodifikasi. Teknik analisis data yang digunakan adalah deskriptif persentase hitung manual dan serta uji Mann-Whitney. Hasil penelitian dan pengembangan ini adalah Mobile Learning PERSIKA berbasis iSpring Suite 9 mata pelajaran Administrasi Umum yang bernama PERSIKA yang telah dinyatakan valid dan layak digunakan dalam pembelajaran Administrasi Umum Kompetensi dasar Menganalisis Persyaratan Personil Administrasi Kantor oleh ahli media, ahli materi, dan 6 siswa uji coba kelompok kecil serta terbukti terdapat perbedaan kemandirian dan hasil belajar secara signifikan pada uji coba kelompok besar dimana hasil tes kelas eksperimen lebih tinggi daripada kelas kontrol. Sehingga dapat disimpulkan bahwa PERSIKA layak dan efektif digunakan sebagai media pembelajaran untuk meningkatkan kemandirian dan hasil belajar Peserta didik pada mata pelajaran Administrasi Umum.

Meningkatkan hasil belajar peserta didik dengan menggunakan Mobile Learning berbasis Flip Pdf Pro Maker (myflip) (A useful mobile base learning media in the Covid-19 era)

Berdasarkan kondisi dan fenomena saat ini, coronavirus masih menjadi masalah utama dalam berbagai bidang, salah satunya yaitu bidang pendidikan yang menjadi salah satu aspek terdampak masalah tersebut. Penyebaran virus ini terbilang sangat cepat dimana sejak akhir tahun 2019 Coronavirus Disease (Covid-19) telah terjadi masalah kesehatan dan berpengaruh terhadap berbagai kebijakan pendidikan, yang salah satu kebijakannya yaitu dilakukannya pembelajaran secara daring (online), sehingga guru dituntut untuk kreatif mengoptimalkan teknologi dalam kegiatan pembelajaran. Oleh karena itu, penelitian ini bertujuan untuk menghasilkan produk MyFlip berbasis Flip PDF Pro Maker untuk meningkatkan hasil belajar peserta didik. Produk media pembelajaran yang dikembangkan terdapat Tujuh menu dan fitur yang mempermudah penggunaan dalam pengoperasiannya Cakupan materi yang lengkap, serta ukuran file sebesar 53 MB dapat membantu peserta didik dalam meningkatkan hasil belajar peserta didik. Penelitian dan pengembangan ini menggunakan model Research and Development Borg and Gall yang telah dimodifikasi. Teknik analisis data yang digunakan adalah deskriptif dan deskriptif persentase. Hasil penelitian dan pengembangan ini adalah MyFlip berbasis Flip PDF Pro Maker pada mata pelajaran Teknologi Perkantoran yang bernama MyFlip yang telah dinyatakan sangat valid dan layak digunakan dalam pembelajaran kearsipan oleh ahli media, ahli materi, dan 6 Peserta Didik uji coba kelompok kecil serta terbukti terdapat perbedaan hasil belajar secara signifikan pada uji coba kelompok besar dimana hasil tes kelas eksperimen lebih tinggi daripada kelas kontrol. Sehingga dapat disimpulkan bahwa MyFlip layak dan efektif digunakan sebagai media pembelajaran untuk meningkatkan hasil belajar Peserta didik pada mata pelajaran Teknologi Perkantoran.

A heap strategy for UAV deployment issues under mobile terrestrial wireless communication networks

Unmanned on-board mobile base stations (MBSs) can more effectively solve wireless connectivity problems in terrestrial communication networks without fixed infrastructure. The purpose of this article is to minimize the number of MBS required to provide wireless coverage for a set of distributed ground terminals (GTs). Traditional clustering algorithms are no longer applicable because each drone has a different coverage area size and the traditional K-Means clustering algorithm has no limit on the number of heaps that can exceed the maximum coverage area of a single drone, making it impossible for a drone to provide services. In response to this problem, the traditional K-Means clustering algorithm is optimized, and the results of the optimized K-Means clustering algorithm are stacked to ensure that each pile has the corresponding drone capability to serve it.

Blade Control for Surface Profile Tracking by Heavy-Duty Bulldozers

The bulldozer is a heavy-duty earthmoving machine used in ground surface profiling and soil manipulation. Tracking the desired surface gradients with the hydraulically actuated manipulator while compensating for the mobile base motion is important in high-performance surface grading and traction control. In this paper, we present an approach for surface elevation tracking control for earthmoving work done by bulldozers using inertial measurement units (IMUs) and roof mounted global navigation satellite system (GNSS) antennas. We use mapping between the desired surface profile and hydraulic actuator velocities using the elevation surface and its gradient, the mobile manipulator Jacobian, and mobile base pose estimation by the extended Kalman filter (EKF) framework. With the proposed method, a relatively simple low-level actuator space control scheme can produce sufficient accuracy in varying elevation requirements besides leveling work. In an experimental setup, flat and uneven surface profiles were followed with average errors below 2 cm computed using kinematics. An external GNSS survey gave a coarse verification of the actual surface profile, showing average errors below 4 cm. This paper demonstrates a blade controller on a heavy-duty tracked vehicle with high manipulator inertia, hydraulic dynamics, and body vibrations. The experimental results validate the efficacy of the proposed method, also revealing the needs for further development.

Automation conditions of mobile base station shelter via cloud and IoT computing applications

In this paper, a monitoring and controlling process of the mobile base station shelter has been implemented. We have proposed a model that is based on a firebase cloud service and the principle of the internet of things (IoT) to carry out the process of automation. In this model, we have used Raspberry Pi 4 as the main microcontroller of our system that has interacted with a DHT11 Humidity-Temperature sensor and a PIR motion sensor. It's found that the Pi4 module provides efficient analysis, low consumption of power, and effective control of the operation. It turns ON/OFF the electrical appliances automatically inside the shelter. The main advantage of our proposed model is to maintain the temperature and humidity degrees inside the shelter within the required range of operation. Another important advantage is to diminish the tall human exertion level behind the monitoring process throughout the day. The model has been tested through a localhost server via an HTML page. The last one was created with the assistance of HTML and CSS languages to be used as a local user interface. Moreover, the Raspberry Pi 4 was programmed by Python Language to catch up on the reading of the sensors, processes the data, and sends it to the cloud service. Finally, those data will be shown in real-time to the authenticated user on the database of the firebase cloud service.

TOF-Based Fast Self-Positioning Algorithm for UWB Mobile Base Stations

To solve the problem of heavy workload and high cost when acquiring the position of Ultra-Wideband (UWB) mobile base stations in sports fields, a fast self-positioning algorithm for UWB mobile base stations algorithm based on Time of Flight (TOF) is proposed. First, according to the layout of the base stations in the sports field, the local coordinate system is determined, and an equation based on the ranging information between the base stations is established; the Least Square method is used to calculate the coordinates of each base station, and the Newton Iteration method is used to converge the positioning results. Then the origin and propagation law of positioning error, as well as the method of reducing the positioning error are analyzed. The simulation data and experimental results show that the average positioning accuracy of the mobile base station is within 0.05 m, which meets the expected accuracy of the base station position measurement. Compared with traditional manual measurement methods, base station self-positioning can effectively save deployment time and reduce workload.