Showing papers in "Sustainable Computing: Informatics and Systems in 2022"

TL;DR: In this article , a deep learning algorithm called Graph Long Short-Term Memory (GLSTM) neural network was used to predict the air quality characteristics and the evolutionary algorithm called Dragon fly optimizer has been used to localize the node based on the prediction.

TL;DR: In this article , the authors proposed an airport AGV path optimization model based on the Dijkstra algorithm of ant colony optimization (ACO-DA) to reduce the operating cost and path cost of AGVs.

TL;DR: In this paper , the authors implemented sustainable soft computing via application of Artificial Neural Networks (ANN) to predict the desalination plant output more accurately using a backpropagation (BP) algorithm.

TL;DR: In this paper , the authors proposed an ACO-DNN model for network intrusion detection in a cloud-based environment, which is based on Ant Colony Optimization (ACO) and Deep Neural Network (DNN).

TL;DR: In this paper , the authors proposed a novel based cloud storage mechanism with accessing governor using Authenticated Privacy Ethereum based Blockchain (APEBC) technique, which is based on Encoded Policy Attribute Based Encrypted embedded with Ethereum concept.

TL;DR: In this paper , the authors presented a solar photovoltaic energy harvesting system for charging the high voltage electric vehicle battery using a partial resonant inverter driven doubler rectifier circuit.

TL;DR: In this paper , the authors proposed a novel hybrid CHO and Hunger Games Search (ChOA-HGS) algorithm for clustering and multi-hop routing optimization in UWSNs.

TL;DR: In this article , the authors presented a digital twin modeling application for improving process and product quality in a refrigerator production line of a large Turkish durable goods manufacturer, Arçelik, collaborates with a Digital Twin Startup, Simularge.

TL;DR: In this article , the partially isolated multi-port DC-DC converter topography for renewable energy harvested in DC micro-grid is presented, where the model predictive control based MPC provides highly efficient operation, low static error, and better load regulation irrespective of the category.

TL;DR: In this paper , a review of smart techniques used for the analysis of mobility data in the prediction of traffic flow in urban areas is presented, and the results of implementing said techniques are shown, in addition, the procedures performed are described and analyzed to understand the benefits and limitations of these smart techniques.

TL;DR: In this article , the reliability assessment of the supply chain and the analysis of the green logistics innovation strategy have improved the environmental pollution of the logistics industry and reduced the vehicle emissions in transportation by 26.9%.

TL;DR: In this paper , the authors present a systematic and bibliographic overview of the literature on improving the energy efficiency of smart city equipment and present the geographical locations where most publications in this discipline have been released.

TL;DR: In this article , an energy and task completion time minimization scheme for the unmanned aerial vehicles (UAVs)-empowered mobile edge computing (MEC) system, where several UAVs are deployed to serve large-scale users' equipment (UEs).

TL;DR: In this article, a novel ensemble-based classifier is proposed to identify thyroid patients, and the thyroid dataset is obtained from the UCI library and the simulation is carried out utilizing Python programming.

TL;DR: In this paper , a novel ensemble-based classifier is proposed to identify thyroid patients, and the thyroid dataset is obtained from the UCI library and the simulation is carried out utilizing Python programming.

TL;DR: In this paper , a comprehensive review on heat pipes for use in data center cooling systems will be carried out, starting from the working principle, heat transfer analysis and applications, and the review works will be analyzed in terms of the system research methodology, energy performance evaluation, and IT tasks.

TL;DR: In this paper , a Hidden Markov Model (HMM) model is proposed for predicting the availability of each fog computing provider regarding factors such as the number of incoming requests to each fog, deadline-missed workflows, and the offloaded tasks from the fogs to the cloud computing.

TL;DR: In this article , the U-Net architecture was employed as a deep encoder-decoder convolutional neural network (CNN) for pixel-wise semantic segmentation of sugar beet, weed, and soil.

TL;DR: In this paper , the authors presented a new intelligent system based on multi-agent system for energy management in micro-grid with grid-connected mode and mainly based on wind energy, which is a model based on a deep recurrent neural network with Long Short Term Memory which takes as input a number of previous values of the wind speed and as output the wind power produced for the next hour.

TL;DR: In this paper , the authors analyzed the asymmetric cryptography approach along with key pair which supports in system security and proposed a customer proactive reengagement over mobile-based telecommunication systems.

TL;DR: In this paper , a hybrid metaheuristics for energy efficiency resource allocation (HMEERA) for the CCC environment is presented, which involves the hybridization of the Group Teaching Optimization Algorithm (GTOA) with rat swarm optimizer (RSO) algorithm, called GTOA-RSO.

TL;DR: In this paper , an Adaptive Network Fuzzy Inference System (ANFIS) based model of the normal operation of the photovoltaic system is constructed and used as a reference for abnormal operation detection, where the training data of the ANFIS-based model has been acquired using a WSN.

TL;DR: In this article , the Grid Topological Network Architecture (GNTN) is presented to give an efficient route if there is a fault-tolerant networking system is presented in this work.

TL;DR: Wang et al. as discussed by the authors used a multi-convolutional neural network (CNN) model, combined with diseased leaf segmentation and a weight initialization method, for automatic identification of tea leaf diseases in small samples.

TL;DR: In this article , the authors present a modular and generic system that can control the UAV by evaluating vision-based ML tasks directly inside the resource-constrained UAV, and demonstrate the ability of the developed system to dynamically react to the environment to provide the necessary maneuver after detecting the target exploiting only the constrained computational resources.

TL;DR: In this article , a multiobjective genetic algorithm based fuzzy c-means clustering (MOGA-FCM) algorithm has been proposed for driver stress recognition, which adopts Electrocardiogram (ECG) signal as input which is further used to compute features.

TL;DR: In this paper , the authors proposed a basic concept of digital twin, and gave the construction method and possible applications of the energy internet digital twin in the integrated regional energy system of smart cities.

TL;DR: Zhang et al. as discussed by the authors proposed a SKPSNet-50 convolutional neural network model to realize the accurate identification of maize leaf diseases in natural scene images, which replaces the 3 × 3 convolution kernel in the backbone network with Select Kernel-Point-Swish-B (SKPS), which is an improved building block of the selected kernel (SK) unit, and replaces the ReLU activation function with the Swish_B activation function to improve the feature extraction capability.

TL;DR: In this article , an Artificial Hummingbird (AHB) algorithm-based feature selection model for the smart grid environment with optimal DL enabled stability prediction (AHbFS-ODLSP) is presented.

TL;DR: In this article , the authors proposed an effective load balancing algorithm named Fuzzy Golden Eagle Load Balancing (FGELB), which consists of three stages, namely: assigning priority to the tasks, resource ranking and scheduling, and power management.