The main challenge of military tactical communication systems is the accessibility of relevant information on the particular operating environment required for the determination of the waveform's ideal use. The existing propagation model focuses mainly on broadcasting and commercial wireless communication with a highs transceiver antenna that is not suitable for numerous military tactical communication systems. This paper presents a study of the path loss model related to radio propagation profile within the suburban in Kuala Lumpur. The experimental path loss modeling for VHF propagation was collected from various suburban settings for the 30-88 MHz frequency range. This experiment was highly affected by ecological factors and existing wave propagation effects such as reflection, diffraction, scattering, and Doppler effect. Radio propagation performance is evaluated by collecting received power at the allocated substation and comparing it against existing propagation models. The existing propagation model also will be tuned close to the measurement value by identifying the best path loss exponent to perform a suitable model for a suburban area. Theoretical assessments and analysis of the initial measurement stage for radio propagation show the extensive contribution of radio field from potential obstacles at lower VHF frequencies for both short and medium ranges around there. The explanation indicates the standard radio propagation prediction models that are generally reasonable for the suburban area. From the general error analysis, it is seen that, the performance of the LDPL with adjusting path loss exponent is the suitable model since it has least value of error metrics.
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreAmorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.
This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreWere analyzed curved optical fates Almarchih absolute colony of the binary type, the Great Palmstqrh using mathematical relationships derived for that and that gave us the results closer to the results of the observed spectral Great Colonial
Hypocrisy is found in various aspects of life, whether in religion, politics, or social parts. Hence, some of the church's hypocrisy is an outcome of different ups and downs in life. Starting with the problem in the novel, some of the hypocritical pastors engaged in an immense role in affecting the folk's lives because they persuaded people that God ordered them to do so. To accomplish their personal interests, the abusive monks disguise their verbal speech, smiles, and fine clothes like mild sheep to delusional followers, leaving them with guilt, shame, and spiritual scars. The present study aims to examine the hypocrisy and heresy of the church as portrayed in Okezie Nwoka's novel entitled God of Mercy. It reflects the source of
... Show MoreThis paper presents an in-depth stylistic analysis of the linguistic artistry andliterary techniques employed by Paulo Coelho in his novel By the River Piedra ISat Down and Wept. A close reading approach guided by stylistics and linguisticsframeworks reveals Coelho's extensive incorporation of imaginative metaphors,vivid imagery, poetic diction, and resonant symbols across the narrative. Analysisspecifically elucidates how Coelho adeptly manipulates various stylistic features toconvey thematic content, shape characterization, and produce aesthetic impacts.Findings provide critical insights into Coelho’s linguistic mastery and contribute toresearch in stylistics and literary linguistics through rigorous examination of anentire contemporary
... Show MoreWith the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored
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