Healthcare Service in Cloud and Internet of Things Using Cuckoo Search and PSO Optimization Techniques

2018 ◽  
Vol 15 (11) ◽  
pp. 3571-3575 ◽  
Author(s):  
K Silambarasan ◽  
P Kumar
Keyword(s):  
Internet Of Things ◽  
Healthcare Service ◽  
Cuckoo Search ◽  
Optimization Techniques

scholarly journals An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 953
Author(s):  
Ali M. Eltamaly
Keyword(s):  
Maximum Power Point Tracking ◽  
Cuckoo Search ◽  
Optimization Techniques ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

PMU Placement Optimization for Fault Observation Using Different Techniques

2021 ◽  
pp. 196-220
Author(s):  
Hamid Bentarzi
Keyword(s):  
Cuckoo Search ◽  
Optimal Number ◽  
Optimization Techniques ◽  
Grey Wolf Optimizer ◽  
Placement Optimization ◽  
Teaching Learning Based Optimization ◽  
Measurement Units ◽  
Pmu Placement ◽  
Teaching Learning ◽  
Full Network

This chapter presents different techniques for obtaining the optimal number of the phasor measurement units (PMUs) that may be installed in a smart power grid to achieve full network observability under fault conditions. These optimization techniques such as binary teaching learning based optimization (BTLBO) technique, particle swarm optimization, the grey wolf optimizer (GWO), the moth-flame optimization (MFO), the cuckoo search (CS), and the wind-driven optimization (WDO) have been developed for the objective function and constraints alike. The IEEE 14-bus benchmark power system has been used for testing these optimization techniques by simulation. A comparative study of the obtained results of previous works in the literature has been conducted taking into count the simplicity of the model and the accuracy of characteristics.

Comparative Performance Analysis of Optimization Techniques on Vector Quantization for Image Compression

2017 ◽  
Vol 7 (1) ◽  
pp. 19-43 ◽  
Author(s):  
Karri Chiranjeevi ◽  
Umaranjan Jena ◽  
Sonali Dash
Keyword(s):  
Performance Analysis ◽  
Image Compression ◽  
Vector Quantization ◽  
Signal To Noise Ratio ◽  
Bat Algorithm ◽  
Cuckoo Search ◽  
Optimization Techniques ◽  
Convergence Time ◽  
Comparative Performance

Linde-Buzo-Gray (LBG) Vector Quantization (VQ), technically generates local codebook after many runs on different sets of training images for image compression. The key role of VQ is to generate global codebook. In this paper, we present comparative performance analysis of different optimization techniques. Firefly and Cuckoo search generate a near global codebook, but undergoes problem when non-availability of brighter fireflies and convergence time is very high respectively. Hybrid Cuckoo Search (HCS) algorithm was developed and tested on four benchmark functions, that optimizes the LBG codebook with less convergence rate by taking McCulloch's algorithm based levy flight and variant of searching parameters. Practically, we observed that Bat algorithm (BA) peak signal to noise ratio is better than LBG, FA, CS and HCS in between 8 to 256 codebook sizes. The convergence time of BA is 2.4452, 2.734 and 1.5126 times faster than HCS, CS and FA respectively.

scholarly journals Multilevel Image Thresholding for Image Segmentation using Hybrid Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 4272-4279
Keyword(s):  
Image Segmentation ◽  
Search Algorithm ◽  
Similarity Index ◽  
Structural Similarity ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Entropy Maximization ◽  
Image Thresholding ◽  
Segmentation Threshold

Image thresholding is an extraction method of objects from a background scene, which is used most of the time to evaluate and interpret images because of their advanced simplicity, robustness, time reduced, and precision. The main objective is to distinguish the subject from the background of the image segmentation. As the ordinary image segmentation threshold approach is computerized costly while the necessity for optimization techniques are highly recommended for multi-tier image thresholds. Level object segmentation threshold by using Shannon entropy and Fuzzy entropy maximized with hGSA-PS. An entropy maximization of hGSA-PS dependent multilevel image thresholds is developed, where the results are best demonstrated in PSNR, misclassification, structural similarity index and segmented image quality compared to the Firefly algorithm, adaptive cuckoo search algorithm and the search algorithm gravitational.

scholarly journals Cloud Computing and Internet of Things Concepts Applied on Buildings Data Analysis

2017 ◽  
Vol 13 (4) ◽  
pp. 39-49 ◽  
Author(s):  
Florin-Adrian Hebean ◽  
Sorin Caluianu
Keyword(s):  
Cloud Computing ◽  
Data Analysis ◽  
Internet Of Things ◽  
Optimization Techniques ◽  
Shared Resources ◽  
Temperature Deviation ◽  
Analysis Techniques ◽  
Automation And Control ◽  
Lower Temperature ◽  
Industry Area

Abstract Used and developed initially for the IT industry, the Cloud computing and Internet of Things concepts are found at this moment in a lot of sectors of activity, building industry being one of them. These are defined like a global computing, monitoring and analyze network, which is composed of hardware and software resources, with the feature of allocating and dynamically relocating the shared resources, in accordance with user requirements. Data analysis and process optimization techniques based on these new concepts are used increasingly more in the buildings industry area, especially for an optimal operations of the buildings installations and also for increasing occupants comfort. The multitude of building data taken from HVAC sensor, from automation and control systems and from the other systems connected to the network are optimally managed by these new analysis techniques. Through analysis techniques can be identified and manage the issues the arise in operation of building installations like critical alarms, nonfunctional equipment, issues regarding the occupants comfort, for example the upper and lower temperature deviation to the set point and other issues related to equipment maintenance. In this study, a new approach regarding building control is presented and also a generalized methodology for applying data analysis to building services data is described. This methodology is then demonstrated using two case studies.

scholarly journals Integrated Healthcare Services for Ageing in Place

2021 ◽  
Vol 15 (3) ◽  
pp. 267-277
Author(s):  
Wiroon Sriborrirux ◽  
Aoranich Saleewong ◽  
Nakorn Indra-Payoong ◽  
Panuwat Danklang ◽  
Hanmin Jung
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Healthcare Service ◽  
Healthcare Professionals ◽  
Healthcare Services ◽  
Medical Assistance ◽  
Integrated Healthcare ◽  
Ageing In Place ◽  
Smart Living ◽  
Service Protocol

This study investigates how healthcare practitioners handle significant circumstancesof providing medical assistance and treatments to patients and what challenges theyface. Drawing on key healthcare stakeholders and mixed smart living methods, wedevelop a guideline service protocol for Internet of Things (IoT) solution to helphealthcare stakeholders in coping with operational difficulties. IoT technology is one ofthe key determinants that empowers healthcare professionals to achieve their tasks,and our goal is to study the functions that provides to local citizens, especially olderpeople, and to evaluate how the functions and platform could assist corporatecompliance policies to increase the efficiency of healthcare service. Our fieldexperiments have indicated a need to educate healthcare users about IoT applicationthat provide advantages in decision making. In addition, our research has explored andevaluated the impacts and factors that influence the development and collaboration byallowing workflows of healthcare stakeholders and by following integrated smart livingplatform and required service protocol.

scholarly journals Cuckoo search algorithm to solve the problem of economic emission dispatch with the incorporation of facts devices under the valve-point loading effect

2021 ◽  
Vol 34 (4) ◽  
pp. 569-588
Author(s):  
Larouci Benyekhlef ◽  
Sitayeb Abdelkader ◽  
Boudjella Houari ◽  
Ayad Ahmed Nour El Islam
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Fuel Cost ◽  
Loading Effect ◽  
Facts Devices ◽  
Emission Dispatch ◽  
Valve Point Loading Effect ◽  
Economic Emission Dispatch

The essential objective of optimal power flow is to find a stable operating point which minimizes the cost of the production generators and its losses, and keeps the power system acceptable in terms of limits on the active and reactive powers of the generators. In this paper, we propose the nature-inspired Cuckoo search algorithm (CSA) to solve economic/emission dispatch problems with the incorporation of FACTS devices under the valve-point loading effect (VPE). The proposed method is applied on different test systems cases to minimize the fuel cost and total emissions and to see the influence of the integration of FACTS devices. The obtained results confirm the efficiency and the robustness of the Cuckoo search algorithm compared to other optimization techniques published recently in the literature. In addition, the simulation results show the advantages of the proposed algorithm for optimizing the production fuel cost, total emissions and total losses in all transmission lines.

scholarly journals An Optimized Model for Energy Efficiency on Cloud System using PSO & CUCKOO Search Algorithm

2019 ◽  
Vol 8 (9S) ◽  
pp. 138-144
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Programming Languages ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Google Docs ◽  
Platform As A Service ◽  
Multiple Resources

Cloud computing is one of the growing technologies, these days. Cloud computing is a paradigm that is surrounded by multiple resources, which helps in resource utilization. Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (Saas) are named as services of cloud computing. In the IaaS models, users can rent infrastructure of the data center as a service. Some of the examples of IAAS are Google Compute Engine (GCE) and Amazon Web Service (AWS). In the PaaS models, users can take services like operating system and database. Some of the examples of PAAS are Microsoft Azure and Google App Engine. In the SaaS models, users can access and install application software and databases via Internet. Examples of SAAS are Citrix GoToMeeting and Google Docs. In this paper algorithms named as PSO and CSA are discussed The objective of optimization for energy consumption on cloud has also been discussed in the paper. Along with the optimization techniques, the detailed literature reviews have been presented. To achieve the proposed work, CloudSim simulators and standard programming languages have been used. The performance of the proposed work will be analyzed by using the various performance parameters such as response time, energy efficiency and execution time.

scholarly journals 5G and intelligence medicine—how the next generation of wireless technology will reconstruct healthcare?

2019 ◽  
Vol 2 (4) ◽  
pp. 205-208 ◽  
Author(s):  
Dong Li
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Patient Experience ◽  
Healthcare Service ◽  
Healthcare Services ◽  
Wireless Transmission ◽  
Wireless Technology ◽  
Total Cost ◽  
5G Technologies

Abstract Despite intensive efforts, there are still enormous challenges in provision of healthcare services to the increasing aging population. Recent observations have raised concerns regarding the soaring costs of healthcare, the imbalance of medical resources, inefficient healthcare system administration, and inconvenient medical experiences. However, cutting-edge technologies are being developed to meet these challenges, including, but not limited to, Internet of Things (IoT), big data, artificial intelligence, and 5G wireless transmission technology to improve the patient experience and healthcare service quality, while cutting the total cost attributable to healthcare. This is not an unrealistic fantasy, as these emerging technologies are beginning to impact and reconstruct healthcare in subtle ways. Although the technologies mentioned above are integrated, in this review we take a brief look at cases focusing on the application of 5G wireless transmission technology in healthcare. We also highlight the potential pitfalls to availability of 5G technologies.

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