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A Smart Approach of LPG Monitoring and Detection System Using IoT

A Smart Approach of LPG Monitoring and Detection System Usin...

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international conference on computing and networking Technology (ICCNT)

作者： Nagib Mahfuz Shawan Karmokar Md. Ismail Hossain Rana American International University - Bangladesh (AIUB) Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Liquefied petroleum gas (LPG) is most widely used all over the world for heating, cooking, vehicle fuel, and so many other fueling purposes. LPG is a highly flammable gas and leakage of LPG occurs major accidents. this paper approaches a smart technique for monitoring the leakage of LP Gas using IoT. In this research, a smart electronic system is developed for monitoring the presence of LP gas, Natural gas, butane, temperature, humidity, and heat index through a webserver. this system can trigger an alarm if the gas leakage is found or any measured parameters exceed the threshold value and also send an alarming SMS to the concerned authority. It can prevent the exploration occurs due to gas leakage. this system is integrated with sensors array which measures the important index related to gas presence and exploration. NodeMCU is a development board having an ESP8266 Wi-Fi chip that is used as a controller unit. the sensors data are fed into a NodeMCU and it imports these data to a website that is accessible from anywhere by using the internet. A 16*2 LCD is connected with the NodeMCU for displaying the sensor's value onsite. A user can enquire about the gas presence by sending SMS also. It's a NodeMCU based low-cost smart system to overcome accidents and gas leakage.

关键词： Sensors Monitoring Gas detectors Temperature measurement Temperature sensors Internet of things Liquid crystal displays

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Data Sequence Map Flooding in MPTCP Framework: Potential Challenges and Efficient Countermeasures

Data Sequence Map Flooding in MPTCP Framework: Potential Cha...

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international conference on computing and networking Technology (ICCNT)

作者： V Anil Kumar Debabrata Das CSIR Fourth Paradigm Institute (CSIR-4PI) Bangalore India International Institute of Information Technology (IIIT) Bangalore India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Multipath Transmission Control Protocol (MPTCP) is a new protocol currently under design and standardization by the Internet Engineering Task Force (IETF). Its primary objective is to enable TCP to operate over multiple paths simultaneously. the protocol consists of a set of new signaling options that needs to be exchanged regularly between MPTCP capable endpoints through the TCP option field. Data Sequence Map (DSM) is one of the most crucial information that needs to be exchanged between the MPTCP endpoints. In this paper, we analyze the DSM exchange mechanism in MPTCP, from a security perspective, and identify potential misbehaviors by MPTCP endpoints. In particular, considering the fact that MPTCP is a stateful transport layer protocol, we explore the possibility of a new adverse scenario called Data Sequence Map flooding (DSM flooding). To the best of our knowledge, this paper for the first time describes three representative scenarios of DSM flooding: 1) DSM flooding through pure acknowledgements (ACKs), 2) DSM Flooding through map splitting and 3) Noncontiguous map splitting and flooding. DSM flooding can be performed by either of the MPTCP endpoints after establishing a MPTCP connection. We highlight the impact of DSM flooding on the other endpoint. We also propose novel countermeasures, including a map aggregation technique for the map receiving endpoint, to reduce the impact of DSM flooding in MPTCP framework.

关键词： Internet Receivers Security Data transfer Wires Floods Transport protocols

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Airline tweets sentimental analysis using Adaptive rider optimization based support vector neural network

Airline tweets sentimental analysis using Adaptive rider opt...

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international conference on computing and networking Technology (ICCNT)

作者： S.Sathish Kumar Aruchamy Rajini Hindustan College of Arts and Science Coimbatore Tamil Nadu India NGM College Pollachi Tamil Nadu India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Nowadays, peoples are posting their personal opinion about different brands on social media. Brands such as airlines, cars, sports teams, entertainment, finance, retail, and the food industry are popular on Twitter. Among them, airlines are the most used brand in business people. In airline companies, building customer loyalty is a major challenge. In the past, traveller's reviews are manually read, analyze, and categorize, which required a lot of effort and time. To avoid the problem, an efficient automatic sentimental analysis method is proposed. the main aim of this paper is to fining best and work airline from tweets. the proposed method consists of three stages namely, pre-processing, feature extraction, and sentiment classification. Initially, the collected reviews are pre-processed to reduce the complexity of classification process. After the pre-processing, word2vec conversion is performed using a skip-gram model. then this output vector is given to the Adaptive Rider optimization based support vector neural network (AR-SVNN) classifier to classify a review as positive, negative, or neutral. Here, the SVNN classifier is enhanced using adaptive rider optimization (ARO) algorithm. the performance of the proposed methodology is analyzed in terms of different metrics namely, accuracy, precision, recall and F-Measure. the experimental results show that proposed method outperformed the other methods.

关键词： Feature extraction Optimization Neural networks Classification algorithms Blogs Social networking (online) Companies

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Quarantine Quibbles: A Sentiment Analysis of COVID-19 Tweets

Quarantine Quibbles: A Sentiment Analysis of COVID-19 Tweets

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international conference and Workshop on computing and Communication (IEMCON)

作者： Jason Nguyen Ritu Chaturvedi School of Computer Science University of Guelph Guelph

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

With the advent of the COVID-19 pandemic, people have flocked to social media in order to stage their thoughts surrounding these unusual circumstances. this paper aims to uncover public sentiment regarding the novel coronavirus pandemic on the microblogging platform Twitter. this is done through a proposed algorithm that builds off of existing aspect-based sentiment analysis approaches and opts for a Naïve-Bayes route to classify existing Tweets that have been atomized into n-grams. this research concludes that overall sentiment regarding the COVID-19 outbreak over July 2020 is a combination of pessimism and dejection as our quarantine denizens take to their online platforms in airing their polemic opinions.

关键词： COVID-19 Sentiment analysis Social networking (online) Pandemics Blogs Optimized production technology Mobile communication

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Smart Home Gardening Management System: A Cloud-Based Internet-of-things (IoT) Application in VANET

Smart Home Gardening Management System: A Cloud-Based Intern...

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international conference on computing and networking Technology (ICCNT)

作者： Sachin Sharma Abhinav Sharma Tanya Goel Rohan Deoli Seshadri Mohan Graphic Era Deemed to be University Dehradun India University of Arkansas at Little Rock Little Rock Arkansas USA

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

the Cloud-based techniques emerging Internet of things (IoT) with Wireless Sensor Networks (WSNs) are enabling many new applications and new opportunities to people in VANET scenario. this paper presents a smart home gardening system; which is able to gather real-time data with various parameters used in gardening system. the technology used in this paper is going to help the society in terms of economic impact. Home gardening is considered an essential new trend for the awareness of the society towards environment. the efficient wireless communication using smart sensors facilitates cost effective solutions to real-time home gardening management system. Precision home gardening management system may optimize resources utilizations, smart sensors deployment and improves society awareness towards pollution free environment. this paper presents the design, implementation and validation process of new innovative technologies which can gather data related to home gardening like humidity, temperature, fertilizers compositions, and many more, push gathered data into VANET cloud for analysis, generate alerts and notify it to user for appropriate actions. In this paper, we present Cloud-based IoT technologies in VANET implementation for smart home gardening management system, which primarily focuses on real-world challenge of developing pollution free smart home in cities. We demonstrate the implementation of proposed system and discuss the results.

关键词： Internet of things Sensors Smart homes Temperature sensors Smart cities Cloud computing Vehicular ad hoc networks

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international conference on Ubiquitous and Future Networks, ICUFN

International Conference on Ubiquitous and Future Networks, ...

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11th international conference on Ubiquitous and Future Networks, ICUFN 2019

ISBN: (纸本)9781728113395

the proceedings contain 176 papers. the topics discussed include: arrhythmia classification system using deep neural network;revenue model with multi-access edge computing for cellular network architecture;MIMO communication based on adaptive passive time reversal in deep water;a study on simplified test bench evaluation model of application layer protocols for pre-5G service;selection of CDMA and OFDM using DNN in underwater acoustic channels;experiments of in-vehicle inductive high-voltage power line communication;content name privacy in tactical named data networking;energy efficiency improvement based on optimal buffer thresholds model for wireless sensor devices;handover protocol in ad-hoc diver networks using visual light communication;and controller adaptive load balancing for SDN networks.

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Scalable Graph Convolutional Network based Link Prediction on a distributed Graph Database Server

Scalable Graph Convolutional Network based Link Prediction o...

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IEEE international conference on Cloud computing, CLOUD

作者： Anuradha Karunarathna Dinika Senarath Shalika Madhushanki Chinthaka Weerakkody Miyuru Dayarathna Sanath Jayasena Toyotaro Suzumura University of Moratuwa Moratuwa Sri Lanka WSO2 Inc. USA Barcelona Supercomputing Center Barcelona Spain

ISBN: (数字)9781728187808

ISBN: (纸本)9781728187815

Graph Convolutional Networks (GCN) have become a popular means of performing link prediction due to the high accuracy offered by them. However, scaling such link prediction into large graphs of billions of vertices and edges with rich types of attributes is a significant issue to be addressed due to the storage and computation limitations of the machines. In this paper we present a scalable link prediction approach which conducts GCN training and link prediction on top of a distributed graph database server called JasmineGraph. We partition graph data and persist them in multiple workers. We implement parallel graph node embedding generation using GraphSAGE algorithm in multiple workers. Our approach avoids facing performance bottlenecks in GCN training using an intelligent scheduling algorithm. We show our approach scales well with an increasing number of partitions (2,4,8, and 16) using four real world data sets called Twitter, Amazon, Reddit, and DBLP-V11. JasmineGraph was able to train a GCN from the largest dataset DBLP-V11 (> 9.3GB) in 11 hours and 40 minutes time using 16 workers on a single server while the original GraphSAGE implementation could not process it at all. the original GraphSAGE implementation processed the second largest dataset Reddit in 238 minutes while JasmineGraph took only 100 minutes on the same hardware with 16 workers leading to 2.4 times improved performance.

关键词： Training Cloud computing Social networking (online) Scheduling algorithms distributed databases Prediction algorithms Servers

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Bengali Question Answering System Using Seq2Seq Learning Based on General Knowledge Dataset

Bengali Question Answering System Using Seq2Seq Learning Bas...

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international conference on computing and networking Technology (ICCNT)

作者： Mumenunnessa Keya Abu Kaisar Mohammad Masum Bhaskar Majumdar Syed Akhter Hossain Sheikh Abujar Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Context-based QA system is a leading research area in NLP. An automatic QA system that can respond to the answer, and which is related to the given context. A deep learning-based model provides a more factual result for today's QA system. Here we introduce a deep learning-based Seq2Seq model for Bengali context-based QA system using general knowledge dataset. Where context and question are part of the encoder and related answer is part of the decoder. All automatic system can discern any language by machine translation. Sequence wise learning is a good solution for those types of automatic system learning. Input tokens are encoded by the encoder and output tokens are decoded by the decoder. Each sequence is stored in LSTM cell that maintains the sequence of input and output. Most of the AI system is developed in different languages. Compared with other languages the Bengali language needs to expand research this field. the major perspective of this research to develop an AI based QA system for the Bengali language. For experiment total, two thousand Bengali general knowledge data is used that also provides a dataset for Bengali QA system. In the dataset, the context contains the main feature for the question. After training our model it gives 99 % accuracy for this dataset and 89% accuracy for validation. the trained model gives a good response in answer prediction.

关键词： Knowledge discovery Mathematical model Decoding Internet Training Data models Logic gates

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A Deep Learning Based Assistive System to Classify COVID-19 Face Mask for Human Safety with YOLOv3

A Deep Learning Based Assistive System to Classify COVID-19 ...

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international conference on computing and networking Technology (ICCNT)

作者： Md. Rafiuzzaman Bhuiyan Sharun Akter Khushbu Md. Sanzidul Islam Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Computer vision learning pay a high attention due to global pandemic COVID-19 to enhance public health service. During the fatality, tiny object detection is a more challenging task of computer vision, as it recruits the pair of classification and detection beneath of video illustration. Compared to other object detection deep neural networks demonstrated a helpful object detection with a superior achievement that is Face mask detection. However, accession with YOLOv3 covered by an exclusive topic which through certainly happening natural disease people get advantage. Added with face mask detection performed well by the YOLOv3 where it measures real time performance regarding a powerful GPU. whereas computation power with low memory YOLO darknet command sufficient for real time manner. Regarding the paper section below we have attained that people who wear face masks or not, its trained by the face mask image and non face mask image. Under the experimental conditions, real time video data that finalized over detection, localization and recognition. Experimental results that show average loss is 0.0730 after training 4000 epochs. After training 4000 epochs mAP score is 0.96. this unique approach of face mask visualization system attained noticeable output which has 96% classification and detection accuracy.

关键词： Training Face recognition Object detection Real-time systems Annotations Task analysis Streaming media

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Designing of Cost-Effective Human Assistive Robot and Performance Enhancement

Designing of Cost-Effective Human Assistive Robot and Perfor...

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international conference on computing and networking Technology (ICCNT)

作者： Md.Fahad Hasan Imteaz Rahaman Md. Shaoran Sayem Md. Mahbub Hasan Borhanul Kabir Tamal Md. Anisur Rahman Rubel American International University-Bangladesh Dhaka Bangladesh Rajshahi University of Engineering & Technology Rajshahi Bangladesh Bangladesh Army University of Engineering & Technology Natore Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

this paper represents an assistive robotic technology to assist elderly people who are unable to move frequently and walk properly and also forget to take medicine. the goal is to implement a prototype and test its capability for helping the elder people to make their life easy and live better. the working prototype has been designed for four features. First, it has a heartbeat sensor where doctors or nurses will easily measure the patient's heartbeat rate. the second one is a common box that will open by touch using an obstacle detector which is known as the sonar sensor. third, an individual patient has an individual box that will open only by punch RFID. And lastly, the moving part of this robot where wheels are used including motors and sensors. this sensor flows the line and reaches the patient in proper time. this proposed robot is a design based on Arduino Uno and Arduino Nano. the proposed human assistive robot provides 96% to 99% accuracy to determine heart rate compared to ECG heart rate for smokers and nonsmoker persons in two different seasons-winter and summer. the prototype is developed to help the elderly people to make their life easy and reduce the nurse's work and make the digital hospital.

关键词： Robot sensing systems Robots Heart rate Radiofrequency identification Heart beat Mobile robots Heart rate variability

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