In recent years, the extensive need for high-quality acquisition platforms for various 3D mapping applications has rapidly increased, especially in sensor performance, portability, and low cost. Image-based UAV sensors have overwhelming merits over alternative solutions for their high timeline and resilience data acquisition systems and the high-resolution spatial data they can provide through extensive Computer Vision (CV) data processing approaches. However, applying this technique, including the appropriate selection of flight mission and image acquisition parameters, ground settings and targeting, and Structure from Motion- Multi-View Stereo (SfM-MVS) post-processing, must be optimized to the type of study site and feature characteristics. This research focuses on optimizing the application of UAV-SfM photogrammetry in an urban area on the east bank of the Tigris River in the north region of Iraq following optimized data capturing plan and SfM-MVS photogrammetric workflow. The research presented the practical application of optimized flight planning, data acquisition, image processing, accuracy analysis, and evaluation based on ground truth targets designed for the proposed optimal routine. This includes investigating the influence of the number and distribution of GCPs, flying heights, and processing parameters on the quality of the produced 3D data. The research showed the potential of low-budget and affordable UAV devices to deliver robust 3D products in a relatively short period by demonstrating the value of UAV-based image techniques when contributed to CV algorithms. The results showed powerful outcomes with validation errors reaching a centimeter-level from 100 m flying height when applying the optimized flight plan settings and the appropriate selection of the number and distribution of GCPs. The study established a streamlined UAV mapping procedure, demonstrated the viability of UAV use for 3D mapping applications, offered suggestions for enhancing future applications, and offered clues as to whether or not UAVs could serve as a viable alternative to conventional ground-based surveying techniques in accurate applications.
Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
... Show MoreThe Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t
... Show MorePattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o
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Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h
... Show MoreImage databases are increasing exponentially because of rapid developments in social networking and digital technologies. To search these databases, an efficient search technique is required. CBIR is considered one of these techniques. This paper presents a multistage CBIR to address the computational cost issues while reasonably preserving accuracy. In the presented work, the first stage acts as a filter that passes images to the next stage based on SKTP, which is the first time used in the CBIR domain. While in the second stage, LBP and Canny edge detectors are employed for extracting texture and shape features from the query image and images in the newly constructed database. The p
Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel
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This paper presents mechanical and electrical design, and implementation process of industrial robot, 3-DoF type SCARA (selective compliment assembly robot arm),with two rotations and one translation used for welding applications.The design process also included the controller design which was based on PLC(programmable logic controller) as well as selection of mechanical and electrical components.The challenge was to use the available components in Iraq with reasonable costs. The robot mentioned is fully automated using programmable logic controller PLC(Zelio type SR3-B261BD),with 16inputs and 10 outputs. The PLC was implemented in FBD logic to obtain three different automatic motions with hi
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