Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Trip generation is the first phase in the travel forecasting process. It involves the estimation of the
total number of trips entering or leaving a parcel of land per time period (usually on a daily basis);
as a function of the socioeconomic, locational, and land-use characteristics of the parcel.
The objective of this study is to develop statistical models to predict trips production volumes for a
proper target year. Non-motorized trips are considered in the modeling process. Traditional method
to forecast the trip generation volume according to trip rate, based on family type is proposed in
this study. Families are classified by three characteristics of population social class, income, and
number of vehicle ownersh

The study of entry and reentry dynamics for space vehicles is very important, particularly for manned vehicles and vehicles which is carry important devices and which can be used again. There are three types for entry dynamic, ballistics entry, glide entry and skip entry. The skip entry is used in this work for describing entry dynamics and determining trajectory. The inertia coordinate system is used to derive equations of motion and determines initial condition for skip entry. The velocity and drag force for entry vehicle, where generate it during entry into earth’s atmosphere are calculated in this work. Also the deceleration during descending and determining entry angles, velocities ratio and altitude ratio have been studied. The c

The paper presents an annotated checklist of the Salticidae of Armenia. This study was carried out in 2019-2020 in order to provide an inventory of the Salticidae fauna. Thirteen species are reported for the Armenian fauna for the first time: Afraflacilla epiblemoides (Chyzer, 1891); Aelurillus v-insignitus (Clerck, 1757); Asianellus festivus (C. L. Koch, 1834); Heliophanus dubius C. L. Koch, 1835; Heliophanus kochii Simon, 1868; Heliophanus tribulosus Simon, 1868; Heliophanus curvidens (O. Pickard-Cambridge, 1872); Macaroeris nidicolens (Walckenaer, 1802); Pellenes diagonalis (Simon, 1868); Pellenes geniculatus (Simon, 1868); Pellenes seriatus (Thorell, 1875); Pellenes tripunctatus (Walckenaer, 1802) and Phlegra fasciata (Hahn, 1826).