2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)最新文献_第7页

ICIIS 2020 Copyright Page ICIIS 2020版权页面

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/iciis51140.2020.9342692

引用次数: 0

Secured Cross Layered Watermark Embedding For Digital Image Authentication Using IWT - SVD 基于IWT - SVD的数字图像认证安全跨层水印嵌入

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342680

K. J. Devi, Priyanka Singh

引用次数: 1

Prediction of Anti-reflection Coating Thickness of a Solar Cell using Artificial Neural Network 应用人工神经网络预测太阳能电池增透涂层厚度

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342669

Maneesh Kumar Shivhare, A. Yadav, S. Pillai, V. Vashishtha, Manish Kumar

引用次数: 2

Generating Silver Nanoparticles from Ipomoea aquatica Extract 从海苔提取物中制备纳米银颗粒

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342721

Joyce Simbajon, Hardeep Kumar

引用次数: 0

An Ensemble Approach To Emphysema Classification 肺气肿分类的集成方法

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342718

C. Bhuma

{"title":"An Ensemble Approach To Emphysema Classification","authors":"C. Bhuma","doi":"10.1109/ICIIS51140.2020.9342718","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342718","url":null,"abstract":"Any disease or disorder in the human body if recognized at an early stage, effective treatment can be given. Emphysema is a type of CPOD (Chronic obstructive pulmonary disease) and it is due to malfunctioning of lungs. Breathing becomes difficult with this disease. It occurs due to the stretching and damaging of air sacs in the lungs. In this work, an ensemble approach is proposed using the features extracted from the last global average pooling layer of the pre trained convolutional neural networks which are trained on ‘Imagenet’ data set. These features are given to an Error Correcting Output Code classifier with the base classifier being Support Vector Machine. Three best pre trained networks are selected based on the average classification accuracy. An ensemble of the three classifiers is considered. Based on the majority voting, weighed average probability and highest probability strategy, the test images labels are identified. Hold out validation (80% training and 20% testing) is used to assess the performance of the proposed algorithm. A popular database of computed tomography emphysema images is chosen to validate our proposal. A peak classification accuracy of 100% and an average classification accuracy of 95.88% is obtained with a combination of Resnet18, Shufflenet, and Resnet 101 pre trained networks with the averaged probability as a choice in the prediction of labels of test images. Compared to the state of the art approaches for classifying emphysema, the proposed method is superior in terms of classification accuracy.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122889894","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: 2

ICIIS 2020 Title Page ICIIS 2020标题页

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/iciis51140.2020.9342731

引用次数: 0

Expectation-Based Multi-Attribute Multi-Hop Routing (EM2 R) in Underwater Acoustic Sensor Networks 基于期望的水声传感器网络多属性多跳路由(em2r)

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342645

B. R. Chandavarkar, Akhilraj V. Gadagkar

引用次数: 1

Energy Management System for Neighbourhood EV based Taxi Parking Station 基于邻里电动汽车的出租车停车站能量管理系统

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342696

Shankanee Illangarathna, P. Binduhewa

{"title":"Energy Management System for Neighbourhood EV based Taxi Parking Station","authors":"Shankanee Illangarathna, P. Binduhewa","doi":"10.1109/ICIIS51140.2020.9342696","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342696","url":null,"abstract":"Penetration of Electric Vehicles (EVs) are now increasing as EVs are pollution free during the operation and more economical than the IC engine driven vehicles. Thus, there is a great interest in EVs. In developing countries, three-wheelers, which is the most popular taxi in most of the developing countries, are considered as the cheapest option for short distances travelling due to its small space. Electric three-wheelers are also emerging in the market. One of the major constraints of introducing an electric three-wheeler is the lack of sufficient charging stations for these small electric vehicles. There is an opportunity to develop photovoltaic (PV) based charging stations for Three-wheeler parks. This paper presents an Energy Management System (EMS) for a standalone PV system with Energy storage, which is to be used to charge Electric Three-wheelers in a park. Users of the Three-wheeler park have the ability to reserve the charging slots via mobile application. The simulation results of the EMS were obtained and presented considering real PV daily profiles and threewheeler usage patterns.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115617593","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

Reinforcement learning control of servo actuated centrally pivoted ball on a beam 梁上伺服驱动中心旋转球的强化学习控制

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342690

Archana Ganesh, Banu Sundareswari Murugesan, M. Panda, T. Ganapathy, Dhanalakshmi Kaliaperumal

{"title":"Reinforcement learning control of servo actuated centrally pivoted ball on a beam","authors":"Archana Ganesh, Banu Sundareswari Murugesan, M. Panda, T. Ganapathy, Dhanalakshmi Kaliaperumal","doi":"10.1109/ICIIS51140.2020.9342690","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342690","url":null,"abstract":"The objective of this work is to devise a controller using Reinforcement Learning (RL) agents, for unstable and complex control systems like the ball beam system. The reinforcement learning agent's job is to keep the ball's position as close as possible to a set point. The Reinforcement Learning agent learns through rewards. Every action is taken such that the reward value is maximized. The reward becomes maximum if setpoint and the current ball position are as close as possible. So, a ball position from the sensor, in terms of reward is taken as feedback to predict the next action. The predicted action is the angle of the beam which needs to be turned by the motor. The action space considered is of a continuous domain, and the Reinforcement Learning algorithms that have been used are Proximal Policy Optimization (PPO) and Deep Deterministic Policy Gradient (DDPG). Once the environment dynamics are defined, hyper-parameters of the reinforcement learning algorithms pertaining to this environment are tuned, and the model is trained. Servo motor is used as the actuation mechanism.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"344 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122920281","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

Aspect Based Sentiment Oriented Hotel Recommendation Model Exploiting User Preference Learning 利用用户偏好学习的基于方面的情感导向型酒店推荐模型

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342744

Mahirangi Godakandage, S. Thelijjagoda

{"title":"Aspect Based Sentiment Oriented Hotel Recommendation Model Exploiting User Preference Learning","authors":"Mahirangi Godakandage, S. Thelijjagoda","doi":"10.1109/ICIIS51140.2020.9342744","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342744","url":null,"abstract":"Due to the advancement of the technology, people tend to focus on the online content related to products and services available through websites and the opinions of others which are provided in the form of reviews and comments. In the tourism domain, travelers are more concerned with the place of accommodation, facilities provided by a hotel, the location or the environment that the hotel is situated and tend to find the hotels that fulfill their requirements. They have to go through each and every review or comment in order to get a clear idea about a particular hotel, according to the opinion of the previous reviewers, which is a difficult and time-consuming task. Therefore, through this research, the users are provided with a system which analyses hotel reviews and provides aspect based personalized hotel recommendations that help users to easily find the best hotel according to their preferences, without having to go through a lot of reviews. For that, the proposed system was implemented with four steps, namely data gathering, data pre-processing, aspect extraction and sentiment analysis, and visualization of the output. In the implemented system, hotel reviews were analyzed and extracted the overall opinion of the reviews as opinion units with their related aspects. Based on the sentiment of those opinion units and the preferences of the user, the best hotels were suggested enabling the users to get an insight about the hotels. For this approach, aspect-based sentiment analysis was used. In addition to that, a weighted average calculation method was used for the final recommendations of the hotels, which suit users’ preferences in an accurate manner.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125519074","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: 3