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Recognizing Foreign Object Debris (FOD): False Alarm Reduction Implementation
No full textRecognition of foreign object debris (FOD) on ruwanys is mandatory to avert the accidents and emergency. The accurate and precise estimation of FOD is very complex because of the intricated shape and their different tiny sizes as well which are noe easily visilble. For the prompt removal of the FOD from the runways a robust, accurate and precise system is badly needed. Therefore, in our research we have proposed a vigor system comprised of ultrasonic sensor and infrared images capturing device with a combination of fake alerts reduction algorithm based on infrared images distribution and morphological edge identification. After the segmentation and morphological processing, the decision a unifying divider was designed to identify the actual targets. Several approaches have been done for the detailed and rapid investigation of FOD. Testing and validation have proved that our proposed research performed well compared to the other techniques. In this research ultrasonic sensors results are integrated with the processed infrared images
Chaotic Local Search Based Algorithm for Optimal DGPV Allocation
No full textThe advent of advanced technology has led to the increase of electricity demand in most countries in the world. This phenomenon has made the power system network operate close to the stability limit. Therefore, the power utilities are looking forward to the solution to increase the loadability of the existing infrastructure. Integration of renewable energy into the grid such as Distributed Generation Photovoltaic (DGPV) can be one of the possible solutions. In this paper, Chaotic Mutation Immune Evolutionary Programming (CMIEP) algorithm is used as the optimization method while the chaotic mapping was employed in the local search for optimal location and sizing of DGPV. The chaotic local search has the capability of finding the best solution by increasing the possibility of exploring the global minima. The proposed technique was applied to the IEEE 30 Bus RTS with variation of load. The simulation results are compared with Evolutionary Programming (EP) and it is found that CMIEP performed better in most of the cases
Data Exfiltration of Ultrasonic Signal in Computer Security System: A Review
No full textIt is crucial for public users and service providers to stay abreast of the progress and trends on data exfiltration in computer security system. In cryptosystem, it is unnoticeable for computer and mobile users to realize that inaudible sound used to transmit signals carrying pervasive sensitive data was in the low frequency ultrasonic range. Acoustic attacks on ultrasonic signal emanated by electronic devices have long been investigated among researchers. This paper is an exploration on the practicality of ultrasonic data exfiltration between computers in term of computer security system. It will discuss some work done by previous researchers in general, based on scientific, technological, and security perspectives. There will be inclusions of practical applications already in existence as well as future studies in related fields
Interference Temperature Measurements and Spectrum Occupancy Evaluation in the Context of Cognitive Radio
No full textThis paper presents a refined radio spectrum measurement platform specifically designed for spectrum occupancy surveys in the context of Cognitive radio. Cognitive radio permits the opportunistic usage of licensed bands by unlicensed users without causing harmful interference to the licensed user. In this work, a study based on the measurement of the 800 MHz to 2.4 GHz frequency band at two different locations inside Universiti Teknologi Malaysia (UTM), Johor Bahru campus, Malaysia is presented. Two Tektronix RSA306B spectrum analyzer are set up to conduct simultaneous measurements at different locations for a 24 hours period. The analysis conducted in this work is based on the real spectrum data acquired from environment in the experimental set up. Busy and idle channels were identified. The channels subject to adjacent-channel interference were also identified, and the impact of the detection threshold used to detect channel activities was also discussed. The consistency of the observed channel occupation over a range of thresholds and a sudden drop has good characteristics in determining an appropriate threshold needed in order to avoid interference
Cryptographic Hashing Method using for Secure and Similarity Detection in Distributed Cloud Data
No full textThe explosive increase of data brings new challenges to the data storage and supervision in cloud settings. These data typically have to be processed in an appropriate fashion in the cloud. Thus, any improved latency may originanimmense loss to the enterprises. Duplication detection plays a very main role in data management. Data deduplication calculates an exclusive fingerprint for each data chunk by using hash algorithms such as MD5 and SHA-1. The designed fingerprint is then comparing against other accessible chunks in a database that dedicates for storing the chunks. As an outcome, Deduplication system improves storage consumption while reducing reliability. Besides, the face of privacy for responsive data also arises while they are outsourced by users to cloud. Aiming to deal with the above security challenges, this paper makes the first effort to honor the notion of distributed dependable Deduplication system. We offer new distributed Deduplication systems with privileged reliability in which the data chunks are distributed across a variety of cloud servers. The protection needs an different of using convergent encryption as in foregoing Deduplication systems
Fuzzy Logic Enhanced Direct Torque Control with Space Vector Modulation
No full textOver the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness.
Ziegler-Nichols Based Proportional-Integral-Derivative Controller for a Line Tracking Robot
No full textLine tracking robots have been widely implemented in various applications. Among various control strategies, a proportional-integral-derivative (PID) algorithm has been widely proposed to optimize the performance of a line tracking robot. However, the motivation of using a PID controller, instead of a proportional (P) or a proportional-integral (PI) controller, in a line tracking task has seldom been discussed. Particularly, the use of a systematic tuning approach e.g. closed loop Ziegler Nichols rule to optimize the parameters of a PID controller has rarely been investigated. Thus, this paper investigates the performance of P, PI, and PID controllers in a line tracking task, and the ability of Ziegler Nichols rule to optimize the parameters of the P, PI, and PID controllers. First, the ultimate gain value, Ku and ultimate period of oscillation, Pu were estimated using a proposed approach. Second, the values of KP, KI and KD were estimated using the Ziegler Nichols formulae. The performance of a differential wheeled robot in the line tracking task was evaluated using three different speeds. Results indicate that the Ziegler Nichols rule coupled with the proposed method is able to identify the parameters of the P, PI, and PID controllers systematically in the line tracking task. Findings indicate that the mobile robot coupled with a proportional controller achieved the best performance compared to PI and PID controllers in the line tracking process when the estimated initial parameters were used
Discrete Chicken Swarm Optimization for the Quadratic Assignment Problem
No full textThe main objective of our research is to improve an adaptation of the chicken swarm optimization algorithm (CSO) to solve the quadratic assignment problem, which is a well-known combinatorial optimization problem. The new approach is based on the CSO without using a local search, the CSO-QAP is a stochastic method inspired from the behavior of chickens in swarm while searching for food. The experiments are performed on a set of 56 benchmark QAPLIB instances. To prove the robustness of our algorithm a comparative analysis is done with the known metaheuristic of Genetic algorithm based on SCX. The average percentage of error to get the best Known solution in our proposed work with the results obtained by applying a simple genetic algorithm using sequential constructive crossover for the quadratic assignment problem. The results show the effectiveness of the proposed CSO-QAP to solve the Quadratic assignment problem in term of time and quality of solutions. The proposed adaptation can be further applied by using a local search strategy to solve the same problem or another combinatorial problem
A Study about SOA Based Agriculture Management Data Framework
No full textAgricultural MDF is a sort of data framework concentrating on the agricultural generation, administration, logical research data gathering, ordering, arranging, recovery and yield; it is an imperative piece of the farming informatization. In view of the examination of circumstance and issue of rural data management, this paper give a coordination model of utilizing SOA to outline agrarian MDF. The SOA's hypothesis, execute innovation and application structure and character were talked about in detail. In light of the investigation of necessity is meaning of agrarian MDF. Utilizing the planning thought of SOA, based-SOA farming MDF was presented, and the fundamental idea, model of configuration was talked about in points of interest
Analysis of BBNs Over Fault Detection and Diagnosis in Industrial Application
No full textIn Industrial procedures, to trust the achievement of planned operation, actualising new and exact strategy for perceiving irregular working conditions, known as shortcomings, is essential. A powerful technique for blame location and analysis helps to decrease the effect of these deficiencies, praises the wellbeing of operation, limits downtime and lessens fabricating costs. In this paper, utilisation of BBNs examined for a benchmark synthetic modern process, known as, Tennessee Eastman keeping in mind the end goal to accomplish prime blame location and specific likely finding of their causes. Use of Bayesian conviction systems for blame location and conclusion of Tennessee Eastman prepare in the graphical setting depiction has not been tried yet. The accomplishment of this component affirms capacity and straightforwardness utilisation of it as an asymptomatic framework in specific current procedures