2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)最新文献_第9页

ICIIS 2020 Table of Contents ICIIS 2020目录

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/iciis51140.2020.9342668

A. Chathurika, L. Y. Perumpuliarachchi, S. Abeyratne, R. Wijekoon

引用次数: 0

Unsupervised Feature Learning for Whatsapp network Data packets using Autoencoder 使用自动编码器的Whatsapp网络数据包的无监督特征学习

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342674

S. Ramraj, G. Usha

{"title":"Unsupervised Feature Learning for Whatsapp network Data packets using Autoencoder","authors":"S. Ramraj, G. Usha","doi":"10.1109/ICIIS51140.2020.9342674","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342674","url":null,"abstract":"Nowadays the network traffic analyses plays a important role in network management. The network management includes Quality of Service, blocking a particular service or application with in the organization network. There are two versions of network traffic analysis existing one is encrypted and other is unencrypted. Instant Message applications such as whatsapp,viber,telegram are generating encrypted network traffic. This type of traffic can be analyzed by analyzing the behavior of network packets flow. The objectives of doing such encrypted traffic analysis include Traffic Clustering, Application Type and Protocol Classification, Anomaly Detection or File Identification. This research is focused on capturing the whatsapp data packets at router level and clustering the packets. Since the packets are captured at router level they dont have any label. It is proposed to apply unsupervised Machine Learning, Deep Learning algorithm such as K Means, PCA, Autoencoder are applied for clustering the network data packets. PCA, Autoencoder are both unsupervised learning approach for dimensionality reduction. The Autoencoder along with K Means algorithm gives good results in clustering the network packets according to their file type(jpg,pdf,mp4).","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"14 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":"132728162","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: 1

Smart Irrigation based on Crops using IoT 基于物联网的农作物智能灌溉

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342736

Shyam Peraka, R. Sudheer, B. N. Rao, A. Teja, E. N. Kumar

{"title":"Smart Irrigation based on Crops using IoT","authors":"Shyam Peraka, R. Sudheer, B. N. Rao, A. Teja, E. N. Kumar","doi":"10.1109/ICIIS51140.2020.9342736","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342736","url":null,"abstract":"Water is the main resource for Agriculture and still, most of the farmers are using traditional methods of irrigation for farming and a large amount of water is getting wasted due to these methods. These outdated techniques have to be replaced with automated techniques. In this paper, we proposed a new irrigation system, which works based on the latest IoT technology to reduce the wastage of water and it reduces manual labor to irrigate the crops. The main objective of the proposed irrigation system is to supply the required amount of water to the crop based on the type and stage of the crop. The proposed irrigation system pumps the water to the crop based on the type, area, and date of the plantation of the crop, and these parameters are registered by the farmer through the IoT-based Android App. The designed irrigation system uses ESP8266 Controller, Moisture, and Water Level sensors for irrigating the crops. The problem with the moisture sensor-based irrigation system is supplying water to the crop only based on the sensor reading, but different crops require different amounts of water at different stages. Hence, in this paper, we divided the total crop duration into five different stages. Based on the type and stage, the crop gets irrigated automatically using the motor incorporated in the circuit and the motor action can be controlled using the algorithm designed for ESP8266. Another problem with the moisture sensor is it shows maximum reading even when the water level is low. This problem can be resolved by using a water level sensor and hence, the proposed smart irrigation system is superior to the existing moisture sensor-based irrigation system. The key factor involved in the proposed methodology is fixing the water level of the crop instead of the quantity of water. The water level is measured by using a level sensor and it measures the water level in terms of the height of water in the field. Hence, the proposed irrigation system works efficiently in both rainy and high-temparature conditions.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"3 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":"133373625","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: 7

Word embedding-based Part of Speech tagging in Tamil texts 泰米尔语文本中基于词嵌入的词性标注

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342640

Sajeetha Thavareesan, S. Mahesan

引用次数: 97

Automatic Threat Detection in Baggage Security Imagery using Deep Learning Models 基于深度学习模型的行李安全图像自动威胁检测

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342691

Aditya Mithal, Manit Baser, Dhiraj

引用次数: 1

Rice Plant Leaf Disease Detection and Severity Estimation 水稻叶片病害检测与严重程度评估

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342653

Radhika Wadhawan, Mayyank Garg, A. Sahani

引用次数: 4

An Adaptive System of Yogic Gesture Recognition for Human Computer Interaction 面向人机交互的瑜伽手势识别自适应系统

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342678

Priyanka Choudhary, S. Tazi

{"title":"An Adaptive System of Yogic Gesture Recognition for Human Computer Interaction","authors":"Priyanka Choudhary, S. Tazi","doi":"10.1109/ICIIS51140.2020.9342678","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342678","url":null,"abstract":"The purpose of the research is to validate the potential of Yogic Hand Gestures in a well-formed human-computer interface with a real-time image sequence taken on a video recording device to trace the potential subject region(PSR) spontaneously, essentially, the hand region with the help of skin detection algorithm, and detect, and perceive hand gestures for human-computer interaction. To detect skin, we use skin colour detection and softening to remove extra background information from the image, and then use background subtraction to detect the PSR. Moreover, to avoid the background information, we use the kernelised correlation filters (KCF) algorithm to track the detected PSR. The image size of the PSR is then resized to 50px * 50px and then fed into the deep convolutional neural network (CNN) to identify eight yogic hand gestures. The deep CNN architecture developed in this study that is a modified VGGNet. The above process of tracking and recognition is repeated with a ranking algorithm to produce a real-time impression, and the system’s execution continues until the hand leaves the camera range. While recognising the gesture primarily, it adds the top-ranked image captures to add into the sample pool for future training, the training data set reaches a recognition rate of 99.00%, and the test data set has a recognition rate of 95.89%, which represents the feasibility of the practical application. The implemented proof of concept and the custom yogic gesture dataset, namely the YoGiR-1 dataset, are availed on request.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"29 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":"115901234","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

Non Invasive Wearable Device for Fetal Movement Detection 胎儿运动检测的无创可穿戴设备

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342662

U. Delay, B. M. T. M. Nawarathne, D. Dissanayake, M. Ekanayake, G. Godaliyadda, J. Wijayakulasooriya, R. Rathnayake

引用次数: 9

A Survey: Strategies for detection of Autism Syndrome Disorder 自闭症综合征障碍的检测策略调查

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342647

Pratik Soygaonkar, Balaji Patil

{"title":"A Survey: Strategies for detection of Autism Syndrome Disorder","authors":"Pratik Soygaonkar, Balaji Patil","doi":"10.1109/ICIIS51140.2020.9342647","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342647","url":null,"abstract":"The Autism Spectrum Disorder (ASD) is known to be characterized by decreased social interactions to stimuli, difficulties in communication, repetitive behaviours and physical movements, unusual or severely limited interests. Since it affects different individuals differently and to different extents, it is very challenging to diagnose and differentiate from other neurodevelopmental disorders. The earlier it is diagnosed, the better it is for the individual, as an intervention protocol can be charted at the earliest. Research shows that early intervention can be very beneficial in the long term as the affected individuals’ symptoms can be reduced to a great extent and in some cases they may not show up on the spectrum at all, but the lack of awareness and objective diagnostic tools makes it difficult to diagnose at an early age. The objective nature of the automated approaches to the screening of Autism Spectrum Disorder would be considered as a viable option for a second opinion and by an extension also an efficient screening process after which the patients would be referred to a therapist. Tests like eye tracking, detection of physical attributes via wearable and static IoT devices, classification on MRI scans and voice prosody detection techniques are easily reproducible and more time efficient than a one on one interview session with a therapist. In this paper we explore the various innovations made in automating the screening process. This paper lists the demerits of the subjective existing diagnosis systems and also surveys and complies the various eye gazing, voice prosody, wearable IoT modules, their contributions and their impacts in making the diagnosis process of Autism Spectral Disorder more objective and efficient.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"13 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":"121721643","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: 1

ICIIS 2020 Cover Page ICIIS 2020封面

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/iciis51140.2020.9342704

引用次数: 0