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An Overview of the Basic NLP Resources Towards Building the Assamese-English Machine Translation 构建阿萨姆语-英语机器翻译的基本自然语言处理资源综述
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.7
Nibedita Roy, Apurbalal Senapati
{"title":"An Overview of the Basic NLP Resources Towards Building the Assamese-English Machine Translation","authors":"Nibedita Roy, Apurbalal Senapati","doi":"10.21467/proceedings.115.7","DOIUrl":"https://doi.org/10.21467/proceedings.115.7","url":null,"abstract":"Machine Translation (MT) is the process of automatically converting one natural language into another, preserving the exact meaning of the input text to the output text. It is one of the classical problems in the Natural Language Processing (NLP) domain and there is a wide application in our daily life. Though the research in MT in English and some other language is relatively in an advanced stage, but for most of the languages, it is far from the human-level performance in the translation task. From the computational point of view, for MT a lot of preprocessing and basic NLP tools and resources are needed. This study gives an overview of the available basic NLP resources in the context of Assamese-English machine translation.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122112315","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
IoT Based Automation and Blockchain for Medical Drug Storage and Smart Drug Store 基于物联网的自动化和区块链的医疗药品存储和智能药店
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.8
S S Suryakrishnaa, K. Praveen, S. Tamilselvan, S. Srinath
{"title":"IoT Based Automation and Blockchain for Medical Drug Storage and Smart Drug Store","authors":"S S Suryakrishnaa, K. Praveen, S. Tamilselvan, S. Srinath","doi":"10.21467/proceedings.115.8","DOIUrl":"https://doi.org/10.21467/proceedings.115.8","url":null,"abstract":"The increase in the work stress and decrease in the time for oneself has led to the rise in the dependency on the medicines and drugs. The drugs and medicines are the key sources for saving the human life when the patient is in the danger. In order to maintain regular and quality supply of the drugs and medicines has to monitor on the regular basis. There are numerous medicines and drugs brought in the store but usually drugs and medicines are stolen to satisfy one’s greed, get expired or placed at unknown locations in the store. So to prevent such situation and saving the life of the patient Drug and Medicine Monitoring Model can be used. The model uses the RFID and IoT technology in order to monitor the drugs and medicines in the store. In medical and drug using systems which are increasing work stress and decreasing the time for oneself that has risen in dependency. The danger situation drugs and medicine is the main source for saving human life when the people are in danger. A daily regular basis to maintain a quality supply of the drug and medicine has been monitored. While traveling and transportation time is numerous medicines and drugs brought from the store but usually it is stolen to one’s greed and the medicines and drugs or placed at unknown locations. To prevent and save a patent life and monitoring model can be used to check the medicine and drug. In our model RFID tag and IoT technology can be used to monitor medicine and drug storage with the help of hospitals and how having a knowledge of the system and chemist of the medical and drugs available, the medicines and drugs quality of location and their safety.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129185752","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
Using Machine Learning to Predict Distributed Denial-of-Service (DDoS) Attack 使用机器学习预测分布式拒绝服务(DDoS)攻击
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.21
Q. Adeshina, B. Saha
{"title":"Using Machine Learning to Predict Distributed Denial-of-Service (DDoS) Attack","authors":"Q. Adeshina, B. Saha","doi":"10.21467/proceedings.115.21","DOIUrl":"https://doi.org/10.21467/proceedings.115.21","url":null,"abstract":"The IT space is growing in all aspects ranging from bandwidth, storage, processing speed, machine learning and data analysis. This growth has consequently led to more cyber threat and attacks which now requires innovative and predictive security approach that uses cutting-edge technologies in order to fight the menace. The patterns of the cyber threats will be observed so that proper analysis from different sets of data will be used to develop a model that will depend on the available data. Distributed Denial of Service is one of the most common threats and attacks that is ravaging computing devices on the internet. This research talks about the approaches and the development of machine learning classifiers to detect DDoS attacks before it eventually happen. The model is built with seven different selection techniques each using ten machine learning classifiers. The model learns to understand the normal network traffic so that it can detect an ICMP, TCP and UDP DDoS traffic when they arrive. The goal is to build a data-driven, intelligent and decision-making machine learning algorithm model that will use classifiers to categorize normal and DDoS traffic using KDD-99 dataset. Results have shown that some classifiers have very good predictions obtained within a very short time.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124460481","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
Design of Driver Alcohol Detection System with Automatic Engine Locking 发动机自动锁定的驾驶员酒精检测系统设计
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.11
S. Siddiqui, Neda Fatima, Anwar Ahmad
{"title":"Design of Driver Alcohol Detection System with Automatic Engine Locking","authors":"S. Siddiqui, Neda Fatima, Anwar Ahmad","doi":"10.21467/proceedings.115.11","DOIUrl":"https://doi.org/10.21467/proceedings.115.11","url":null,"abstract":"Drunken Driving is one of the most fatal causes of premature deaths around the world. According to WHO, about 20% of the fatally injured drivers have excess alcohol in their blood in high income countries whereas the figures may be as high as 69% in low and middle income countries. In India alone, there have been 38,000 road mishaps due to drunk driving in the past three years according to the latest report of Ministry of Road Transport and Highways. The objective of this paper is to make human driving safer and overcome such incidences. The present paper describes the process of detection of alcohol in sample breath testing, developed using Arduino and Arduino Integrated Design Environment (IDE). The system will sense the alcohol concentration in breath and control the switching of ignition engine according the data it receives. Also, it allows the driver a delay time in case the breath is detected after the vehicle has started to avoid traffic mismanagement. Finally, it will send an SMS alert to his/her relatives/close friends to alert them of possible drunken driving incident and prevent it.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129310268","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
Design of Smart Heart Rate Monitoring and Stress Detection System with Cloud Data Storage and Privacy 具有云数据存储和隐私的智能心率监测和应力检测系统的设计
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.10
Neda Fatima, S. Siddiqui, Anwar Ahmad
{"title":"Design of Smart Heart Rate Monitoring and Stress Detection System with Cloud Data Storage and Privacy","authors":"Neda Fatima, S. Siddiqui, Anwar Ahmad","doi":"10.21467/proceedings.115.10","DOIUrl":"https://doi.org/10.21467/proceedings.115.10","url":null,"abstract":"The COVID-19 pandemic affected the entire world in various ways. It influenced the global order, lives, livelihoods, travel, workspace, digital systems and most importantly the health systems. One unarguably the most unusual and striking effect of the pandemic has been on the mental health of people worldwide as lives underwent drastic changes in the pandemic. As the pandemic continues, the demand for mental health treatment is only increasing with focus on more personalized and customized healthcare as each individual has his/her own sets of issues, fears and insecurities and ‘one size-fits-all’ approach cannot be practiced in such cases. This paper presents a comprehensive solution in the form of a novel stress monitoring system that detects stress levels and guides the person to relax by pursuing a hobby like watching a meditative video or distract for some time and play some soothing game. It also alerts his personal psychiatrist or doctor who can then check up on him and prescribe him appropriate treatment and medication in case of high stress levels.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126613012","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
Intelligent Intrusion Detection System using Supervised Learning 基于监督学习的智能入侵检测系统
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.3
Sandipan Roy, Apurbo Mandal, Debraj Dey
{"title":"Intelligent Intrusion Detection System using Supervised Learning","authors":"Sandipan Roy, Apurbo Mandal, Debraj Dey","doi":"10.21467/proceedings.115.3","DOIUrl":"https://doi.org/10.21467/proceedings.115.3","url":null,"abstract":"Going digital involves networking with so many connected devices, so network security becomes a critical task for everyone. But an intrusion detection system can help us to detect malicious activity in a system or network. But generally, intrusion detection systems (IDS) are not reliable and sustainable also they require more resources. In recent years so many machine learning methods are proposed to give higher accuracy with minimal false alerts. But analyzing those huge traffic data is still challenging. So, in this article, we proposed a technique using the Support Vector Machine & Naive Bayes algorithm, by using this we can solve the classification problem of the intrusion detection system. For evaluating our proposed method, we use NSL-KDD and UNSW-NB15 dataset. And after getting the result we see that the SVM works better than the Naive Bayes algorithm on that dataset.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125241762","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 COVID-19 Corpus Creation for Bengali: In the Context of Language Study 基于语言研究的孟加拉语COVID-19语料库创建
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.9
Prasanta Mandal, Apurbalal Senapati
{"title":"A COVID-19 Corpus Creation for Bengali: In the Context of Language Study","authors":"Prasanta Mandal, Apurbalal Senapati","doi":"10.21467/proceedings.115.9","DOIUrl":"https://doi.org/10.21467/proceedings.115.9","url":null,"abstract":"A corpus is a large collection of machine-readable texts, ideally, that should be representative of a Language. Corpus plays an important role in several natural language processing (NLP) and linguistic research. The corpus development itself is a substantial contribution to the resource building of language processing. The corpora play an important role in linguistic study as well as in several NLP tasks like Part-Of-Speech (POS) tagging, Parsing, Semantic tagging, in the parallel corpora, etc. There are numerous corpora in the literature of different languages and most of them are created for a specific purpose. Hence it is obvious that a researcher cannot use any corpus for their particular task. This paper also focuses on an automated technique to create a COVID-19 corpus dedicated to the research in linguistic aspects because of the pandemic situation.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123760514","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
Machine Learning Driven IoT Based Smart Health Care Kit 基于机器学习驱动物联网的智能医疗保健工具包
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.24
Lekhasree Narayanagari, B. Saha
{"title":"Machine Learning Driven IoT Based Smart Health Care Kit","authors":"Lekhasree Narayanagari, B. Saha","doi":"10.21467/proceedings.115.24","DOIUrl":"https://doi.org/10.21467/proceedings.115.24","url":null,"abstract":"This paper focuses on developing a machine learning driven IOT based smart healthcare kit. It plays an important role in emergency medical service like Intensive Care Units (ICU), by using an INTEL GALILEO 2ND generation development board. It facilitates to monitor and track different health indicators such as Blood Pressure, Pulses, and Temperature of the patient. This system allows to send the real time data of a patient to the physician and record it for future use. In this research we conducted two experiments: a)heart disease prediction from pathology data and b) lung disease prediction from X-ray images. For heart disease prediction we evaluate the performance of K-Nearest Neighbour and Random Forest Classifier and for lung disease prediction, we use VGG19 deep architecture. Experimental results demonstrate that machine learning can help to automate the IoT based smart healthcare kit and help doctors to diagnose the diseases.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128121274","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
End-to-End Speech Recognition Using Recurrent Neural Network (RNN) 基于递归神经网络的端到端语音识别
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.20
Rene Avalloni de Morais, B. Saha
{"title":"End-to-End Speech Recognition Using Recurrent Neural Network (RNN)","authors":"Rene Avalloni de Morais, B. Saha","doi":"10.21467/proceedings.115.20","DOIUrl":"https://doi.org/10.21467/proceedings.115.20","url":null,"abstract":"Deep learning algorithms have received dramatic progress in the area of natural language processing and automatic human speech recognition. However, the accuracy of the deep learning algorithms depends on the amount and quality of the data and training deep models requires high-performance computing resources. In this backdrop, this paper adresses an end-to-end speech recognition system where we finetune Mozilla DeepSpeech architecture using two different datasets: LibriSpeech clean dataset and Harvard speech dataset. We train Long Short Term Memory (LSTM) based deep Recurrent Neural Netowrk (RNN) models in Google Colab platform and use their GPU resources. Extensive experimental results demonstrate that Mozilla DeepSpeech model could be fine-tuned for different audio datasets to recognize speeches successfully.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132460020","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
Road Extraction from Remotely Sensed Data: A Review 基于遥感数据的道路提取研究进展
Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.14
Mohd Jawed Khan, P. Singh
{"title":"Road Extraction from Remotely Sensed Data: A Review","authors":"Mohd Jawed Khan, P. Singh","doi":"10.21467/proceedings.115.14","DOIUrl":"https://doi.org/10.21467/proceedings.115.14","url":null,"abstract":"Up-to-date road networks are crucial and challenging in computer vision tasks. Road extraction is yet important for vehicle navigation, urban-rural planning, disaster relief, traffic management, road monitoring and others. Road network maps facilitate a great number of applications in our everyday life. Therefore, a systematic review of deep learning approaches applied to remotely sensed imagery for road extraction is conducted in this paper. Four main types of deep learning approaches, namely, the GANs model, deconvolutional networks, FCNs, and patch-based CNNs models are presented in this paper. We also compare these various deep learning models applied to remotely sensed imagery to show their performances in extracting road parts from high-resolution remote sensed imagery. Later future research directions and research gaps are described.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134053045","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
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