scholarly journals Document Image Compression using DC-DWT

2019 ◽  
Vol 8 (10) ◽  
pp. 3505-3509
Keyword(s):  
Image Compression ◽  
Search Algorithm ◽  
Curvelet Transform ◽  
Image Transmission ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Document Image ◽  
Discrete Wavelet ◽  
And Storage

Scanned Document Image compression is an important technology for digital image transmission and storage. This study proposes a unique image compression system based on discrete curvelet transform & discrete wavelet Transform (DC-DWT) with a varying pixels position. The discrete wavelet and the Curvelet transform technique, which because of their outcomes and characteristics, DWT and CT are the most suitable technology for the varied field of image processing. The position of a pixel in the document images and the high-impact components are handled using the curve let transform technique during the compression of the JPEG image. The Cuckoo search algorithm is used for image enhancement. Depending on two primary criteria checks, excellent outcomes were achieved; the compression ratio and the quality of recreated scan document.

scholarly journals A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2611
Author(s):  
José García ◽  
José Lemus-Romani ◽  
Francisco Altimiras ◽  
Broderick Crawford ◽  
Ricardo Soto ◽  
...  
Keyword(s):  
Local Search ◽  
Knapsack Problem ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Local Search Operator ◽  
Insight Into

Optimization techniques, specially metaheuristics, are constantly refined in order to decrease execution times, increase the quality of solutions, and address larger target cases. Hybridizing techniques are one of these strategies that are particularly noteworthy due to the breadth of applications. In this article, a hybrid algorithm is proposed that integrates the k-means algorithm to generate a binary version of the cuckoo search technique, and this is strengthened by a local search operator. The binary cuckoo search algorithm is applied to the NP-hard Set-Union Knapsack Problem. This problem has recently attracted great attention from the operational research community due to the breadth of its applications and the difficulty it presents in solving medium and large instances. Numerical experiments were conducted to gain insight into the contribution of the final results of the k-means technique and the local search operator. Furthermore, a comparison to state-of-the-art algorithms is made. The results demonstrate that the hybrid algorithm consistently produces superior results in the majority of the analyzed medium instances, and its performance is competitive, but degrades in large instances.

scholarly journals Traffic signs recognitionusing cuckoo search algorithm and Curvelettransform with image processing methods

2019 ◽  
Vol 11 (2) ◽  
pp. 74-81
Author(s):  
Ahmed Saadi Abdullah ◽  
Majida Ali Abed ◽  
Ahmed Naser Ismael
Keyword(s):  
Image Processing ◽  
Traffic Accidents ◽  
Search Algorithm ◽  
Curvelet Transform ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Fourth Step ◽  
Processing Techniques

Compliance with traffic signs is one of the most important things to follow to avoid traffic accidents as well as compliance with traffic rules in terms of parking, speed control, and other traffic sings. Progress in different areas, such as self-propelled car manufacturing or the production of devices that help the visually impaired, require values to find a way to determine traffic signals with high precision in this research, The first step is to take a picture of the traffic sign and apply some digital image processing techniques to increase image contrast and eliminate noise in the image, the second step resize of origin image  , the third step convert color to(YCbCr, HSB) or stay on RGB, the fourth step  image is disassembled using  curvelet  transform and get coefficients , and the last step using cuckoo search algorithm to recognition sings traffics ,the MATLAB (2011b) program was used to implement the proposed algorithm . After applying this method to a set of traffic the percentage of discrimination of traffic signs was yellow 93%, green 94%, blue 94.5%, red 96%.

scholarly journals A Method Towards Allocation of VM using a Cuckoo Search Algorithm

2019 ◽  
Vol 8 (9S4) ◽  
pp. 136-142
Keyword(s):  
Large Scale ◽  
Search Algorithm ◽  
Cloud Model ◽  
New Technology ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Test Results ◽  
Allocation Policy ◽  
Qos Parameters

Cloud computing is a new technology created for complex systems with massive service sharing. It is not easy to analyze the cloud model due to its complex and large scale structure. To meet the user's requirement along with the quality of service (QoS) parameters become the most dominating research issue. The QoS parameters are affected due to various issues such as load balancing, Virtual Machine (VM), makespan, throughput, Utilization of Hosts’ Processing Capability (UHPC) and many more. The allocation policy of VM mainly used to place VMs on hosts at various datacenters. This article outlines the new VM allocation policy using Modified Best Fit Decreasing (MBFD) along with with Cuckoo Search (CS) algorithm that delivers the VM burden between hosts to improve the handling capability and the cloud system performance. The test results are obtained using CloudSim trace simulation and the QoS are compared with existing allocation policies of VM.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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