Day 1 Mon, June 28, 2021最新文献

Prediction of Energy Consumption by Ships at the port using Deep Learning 基于深度学习的港口船舶能耗预测

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-30 DOI: 10.36548/jeea.2021.2.005

P. Hengjinda, J. Chen

{"title":"Prediction of Energy Consumption by Ships at the port using Deep Learning","authors":"P. Hengjinda, J. Chen","doi":"10.36548/jeea.2021.2.005","DOIUrl":"https://doi.org/10.36548/jeea.2021.2.005","url":null,"abstract":"The harbours using green ports have become a common mode of enabling the use of environment friendly energy consumption. In this paper, two major contributions are made: reduction of energy consumption in the ports by using ships; prediction of energy consumption with respect to a green port. The characteristics that will play a crucial role in energy consumption of ships are considered and a detailed analysis has been performed to predict the energy consumed by the ships. Deep learning methodologies such as, K-Nearest Regression (KNR), Linear Regression (LR), BP Network (BP), Random Forest Regression (RF) and Gradient Boosting Regression (GBR) are used to determine the different characteristics of the ships that are used while the external features of the ports are given as input. To determine the efficiency of the proposed work, k-fold cross validation is also incorporated. Based on feature importance, the crucial features of the algorithm are selected. The influence of different changing aspects on the ship's energy usage is identified, and reduction methods are implemented appropriately. According to the observed data, the most essential factors that may be utilised to estimate energy consumption of the ship are efficiency of facilities, actual weight, deadweight tonnage, and net tonnage. As the efficiency increases, there is also a significant reduction and the power consumption of the ship at the rate of 8% and 32% in port and berth respectively.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77685611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of Modelling for Piezoelectric Energy Harvesting Solutions 压电能量收集方案建模的比较分析

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-30 DOI: 10.36548/jeea.2021.2.006

J.S.K. Raj, G. Ranganathan

引用次数: 1

Energy Efficient Data Mining Approach for Estimating the Diabetes 一种评估糖尿病的高效数据挖掘方法

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-30 DOI: 10.36548/jeea.2021.2.004

R RajeshSharma

引用次数: 0

A Review on future challenges and concerns associated with an Internet of Things based automatic health monitoring system 基于物联网的自动健康监测系统的未来挑战和关注综述

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-30 DOI: 10.36548/jeea.2021.2.003

A. Pandian

{"title":"A Review on future challenges and concerns associated with an Internet of Things based automatic health monitoring system","authors":"A. Pandian","doi":"10.36548/jeea.2021.2.003","DOIUrl":"https://doi.org/10.36548/jeea.2021.2.003","url":null,"abstract":"This research article surveys the most recent IoT healthcare system research articles as the integration of IoT models have been extended to healthcare systems, such as health monitoring, fitness routines, and other applications. Extensive research study has been conducted on Internet of Things (IoT) technology to enhance the monitoring efficiency. This research is aimed at investigating the Internet of Things [IoT] architecture with an emphasis on cloud-based applications. The most significant challenges in the Internet of Things [IoT] include different elements such as accuracy and energy consumption, wherein this research is focused on improving the performance of IoT-based medical equipment. In this research, data management techniques for the Internet of Things-based cloud healthcare system are also thoroughly investigated. The performance and limitations of the Internet of Things (IoT) health system are evaluated. The majority of studies are successful in detecting a wide range of markers and correctly predicting illness. The Internet of Things (IoT) health system is being developed as an effective solution to the health concerns of elderly population. The major drawbacks of current systems are their increased energy consumption, reduced availability of resources, and safety concerns resulting from the use of a large number of different pieces of equipment.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86412774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Intelligence based Business Process Automation for Enhanced Knowledge Management 基于人工智能的业务流程自动化增强知识管理

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-27 DOI: 10.36548/jeea.2021.2.001

V. Bindhu

引用次数: 1

SDN Controller and Blockchain to Secure Information Transaction in a Cluster Structure SDN控制器和区块链在集群结构中保护信息交易

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-27 DOI: 10.36548/jtcsst.2021.2.006

Suma

{"title":"SDN Controller and Blockchain to Secure Information Transaction in a Cluster Structure","authors":"Suma","doi":"10.36548/jtcsst.2021.2.006","DOIUrl":"https://doi.org/10.36548/jtcsst.2021.2.006","url":null,"abstract":"The Internet of Things [IoT] is one of the most recent technologies that has influenced the way people communicate. With its growth, IoT encounters a number of challenges, including device heterogeneity, energy construction, comparability, and security. Energy and security are important considerations when transmitting data via edge networks and IoT. Interference with data in an IoT network might occur unintentionally or on purpose by malicious attackers, and it will have a significant impact in real time. To address the security problems, the suggested solution incorporates software defined networking (SDN) and blockchain. In particular, this research work has introduced an energy efficient and secure blockchain-enabled architecture using SDN controllers that are operating on a novel routing methodology in IoT. To establish communication between the IoT devices, private and public blockchain are used for eliminating Proof of Work (POW). This enables blockchain to be a suitable resource-constrained protocol for establishing an efficient communication. Experimental observation indicates that, an algorithm based on routing protocol will have low energy consumption, lower delay and higher throughput, when compared with other classic routing algorithms.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74837589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard 无人机热成像技术在葡萄园水状态自动化中的应用

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-27 DOI: 10.36548/jeea.2021.2.002

S. Shakya

{"title":"Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard","authors":"S. Shakya","doi":"10.36548/jeea.2021.2.002","DOIUrl":"https://doi.org/10.36548/jeea.2021.2.002","url":null,"abstract":"Thermal imaging is utilized as a technique in agricultural crop water management due to its efficiency in estimating canopy surface temperature and the ability to predict crop water levels. Thermal imaging was considered as a beneficial integration in Unmanned Aerial Vehicle (UAV) for agricultural and civil engineering purposes with the reduced weight of thermal imaging systems and increased resolution. When implemented on-site, this technique was able to address a number of difficulties, including estimation of water in the plant in farms or fields, while considering officially induced variability or naturally existing water level. The proposed effort aims to determine the amount of water content in a vineyard using the high-resolution thermal imaging. This research work has developed an unmanned aerial vehicle (UAV) that is particularly intended to display high-resolution images. This approach will be able to generate crop water stress index (CWSI) by utilizing a thermal imaging system on a clear-sky day. The measured values were compared to the estimated stomatal conductance (sg) and stem water (s) potential along the Vineyard at the same time. To evaluate the performance of the proposed work, special modelling approach was used to identify the pattern of variation in water level. Based on the observation, it was concluded that both ‘sg’ and ‘s’ value have correlated well with the CWSI value by indicating a great potential to monitor instantaneous changes in water level. However, based on seasonal changes in water status, it was discovered that the recorded thermal images did not correspond to seasonal variations in water status.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90515507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain 物联网领域偏远地区道路事故位置检测黑匣子构建

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-23 DOI: 10.36548/JTCSST.2021.2.005

J. Chen, S. Smys

{"title":"Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain","authors":"J. Chen, S. Smys","doi":"10.36548/JTCSST.2021.2.005","DOIUrl":"https://doi.org/10.36548/JTCSST.2021.2.005","url":null,"abstract":"In recent years, both developed and developing countries have witnessed an increase in the number of traffic accidents. Aside from a significant rise in the overall number of on-road commercial and non-commercial vehicles, advancements in transportation infrastructure and on-road technologies may result in road accidents, which generally result in high mortality. More than half of these fatalities are the result of delayed response by medical and rescue personnel. If an accident site receives quick medical treatment, an accident victim's chances of survival may improve considerably. Based on the IoT-based multiple-level vehicle environment, this study proposes a low-cost accident detection and alarm system. Vehicles are equipped with a \"Black Box\" board unit and an accident location identification module for the Global Positioning System (GPS), in addition to mechanical sensors (accelerometer, gyroscope) for accurate accident detection. This study has evaluated the proposed system with average packet delivery ratio (PDR) vs. relay nodes. Our simulation results have evaluated the evolution of relay nodes in the mobile / sensor node through internet gateway. It has also been demonstrated that the packet delivery ratio is inversely related to the incremental number of relay nodes.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89193777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction of reliable image captioning system for web camera based traffic analysis on road transport application 基于网络摄像机的交通分析可靠图像字幕系统的构建在道路运输中的应用

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-17 DOI: 10.36548/JTCSST.2021.2.004

R. Dhaya

{"title":"Construction of reliable image captioning system for web camera based traffic analysis on road transport application","authors":"R. Dhaya","doi":"10.36548/JTCSST.2021.2.004","DOIUrl":"https://doi.org/10.36548/JTCSST.2021.2.004","url":null,"abstract":"The automated captioning of natural images with appropriate descriptions is an intriguing and complicated task in the field of image processing. On the other hand, Deep learning, which combines computer vision with natural language, has emerged in recent years. Image emphasization is a record file representation that allows a computer to understand the visual information of an image in one or more words. When it comes to connecting high-quality images, the expressive process not only requires the credentials of the primary item and scene but also the ability to analyse the status, physical characteristics, and connections. Many traditional algorithms substitute the image to the front image. The image characteristics are dynamic depending on the ambient condition of natural photographs. Image processing techniques fail to extract several characteristics from the specified image. Nonetheless, four properties from the images are accurately described by using our proposed technique. Based on the various filtering layers in the convolutional neural network (CNN), it is an advantage to extract different characteristics. The caption for the image is based on long short term memory (LSTM), which comes under recurrent neural network. In addition, the precise subtitling is compared to current conventional techniques of image processing and different deep learning models. The proposed method is performing well in natural images and web camera based images for traffic analysis. Besides, the proposed algorithm leverages good accuracy and reliable image captioning.","PeriodicalId":11075,"journal":{"name":"Day 1 Mon, June 28, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79258207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis 基于深度学习分析的高效客户情感检测方法综述

Day 1 Mon, June 28, 2021 Pub Date : 2021-07-14 DOI: 10.36548/JTCSST.2021.2.003

Kottilingam Kottursamy

引用次数: 26