Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

BACKGROUND: Clavicle fractures are common injuries in young active individuals, the mid third of the clavicle is most commonly fractured part(80% of clavicle fracture) OBJECTIVE: To compare the outcomes of operative and non operative management of displaced and or comminuted closed fracture of the mid third of clavicle in young adults PATIENTS AND METHODS: This prospective observational study of 24 patients of fracture of the mid third of the clavicle was conducted in Alkindy teaching hospital from July 2015 to January 2017 and divided into two groups; one managed by operative treatment with plate and screws and the other by non operative sling immobilization after taking the consent and the patients were seen at 2, 4, 6 weeks,3, 6, and 9 m

RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

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 research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

Nanocrystalline micro-mesoporous ZSM/MCM-41 composite was synthesized using alkaline treatment method and two step of crystallization in poly tetraflouroethylene (PTFE) lined autoclave. The synthesized zeolites was characterized by X-Ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Atomic force microscopy (AFM), Fourier transport infrared (FTIR), and N₂ adsorption-desorption (BET). It was approved that the best results for alkaline leaching can be got with 1.5M NaOH solution. High surface (BET) area of 630 m²/g with pore volume of 0.55 cm³/g has been got. AFM reports showed a nano-level size for average particle size of 50nm.

Aluminum Metal Matrix Composites (ALMMCs) was prepared by using stir casting technique for AA 7075 aluminum alloy as a matrix reinforced with SiC particles at various percentages (3, 6, 9 and 12 wt. % ) and 75µm in grain size. The prepared composite material can be used for many applications such as aerospace, automobiles and many industrial sectors. Abrasive wear test was carried out by two stages: the first stage was done by changing the emery papers at various grit sizes 180, 320, 500, and 1000µm with constant applied load 15N. While the second stage was carried out by changing the applied loads 5, 10, 15, 20 and 25N with constant emery paper at 320 µm grit size. Microstructure examination, hardness test and roughn