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2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)最新文献

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English-Chinese Corpus Information Collection and Quantum Translation Based on Big Data 基于大数据的英汉语料库信息收集与量子翻译
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640782
Xiangdong Guo, Caixia He
{"title":"English-Chinese Corpus Information Collection and Quantum Translation Based on Big Data","authors":"Xiangdong Guo, Caixia He","doi":"10.1109/I-SMAC52330.2021.9640782","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640782","url":null,"abstract":"With the continuous development of Big Data information resources, the resources that people can obtain through the Internet have also increased. At present, there are about 3,000 known languages in the world. Research on machine translation and automatic acquisition of machine translation knowledge has strong practical significance for people to break through language barriers and make use of Internet information. Based on the description of the whole process of bilingual corpus construction, this essay proposes the flexibility of the information change model and quantum translation platform of the English-Chinese corpus based on big data.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125631562","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
Recognition of Bird Species Using Multistage Training with Transmission Learning 基于传递学习的多阶段训练方法识别鸟类物种
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640676
R. K N, Rohitha Pasumarty
{"title":"Recognition of Bird Species Using Multistage Training with Transmission Learning","authors":"R. K N, Rohitha Pasumarty","doi":"10.1109/I-SMAC52330.2021.9640676","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640676","url":null,"abstract":"Object localization is a computer vision technique to identify real-world objects such as birds, cats, flowers, cars in images or videos. The algorithm is based on a feature extraction and learning algorithm to recognize instances of an object category. Bird’s species are the most amazing creature exist on earth. They are sensitive to changes in the environment and hence acts as bioindicator species. The main aim of this project is to identify bird species from a high-resolution digital image of Himalayan birds which would help beginner bird watchers or general people for identification. The data sets for the identification of birds are provided by Kaggle which consists of 16 species of birds. For the reduction of the overfitting problem, a data augmentation process is implemented. The model achieves an accuracy of 50.64 or 0.5064% on the dataset of Kaggle.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132021532","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: 14
Automated Voice Controlled Car Using Arduino with Camera 使用Arduino带摄像头的自动语音控制汽车
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640688
C. Thirumarai Selvi, N. Anishviswa, G. A. Karthi, K. Darshan, M. G. Balaji
{"title":"Automated Voice Controlled Car Using Arduino with Camera","authors":"C. Thirumarai Selvi, N. Anishviswa, G. A. Karthi, K. Darshan, M. G. Balaji","doi":"10.1109/I-SMAC52330.2021.9640688","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640688","url":null,"abstract":"This paper focuses on voice controlled car with camera, which is constructed by using major components called Arduino Uno, bluetooth module, motor driver circuit, camera and microsd card module. This automation provides a convenient way to control voice-controlled robot. This automation can aid people, who cannot walk. Voice Controlled car is controlled by using specific commands, which are recognized by mike with the mobile application. The mobile application recognize six commands and they are LEFT, RIGHT, FORWARD, BACK, STOP, KEEP WATCH IN ALL DIRECTION. This mobile application can be used in android or IOS cellphones. Here, the Bluetooth module is used for controlling the voice-controlled car wirelessly and utilizes MicroSD card for storing the video from the camera.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132840158","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
Real-time Feedback System of Funding Data Flow Based on Data Tracking and Classification 基于数据跟踪与分类的资金数据流实时反馈系统
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640661
Ruizhu Xi, Bencai Gao, Xiao Xia
{"title":"Real-time Feedback System of Funding Data Flow Based on Data Tracking and Classification","authors":"Ruizhu Xi, Bencai Gao, Xiao Xia","doi":"10.1109/I-SMAC52330.2021.9640661","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640661","url":null,"abstract":"Data analysis and clustering technologies have becoming the state-of-the-art method of analyzing the complex information. Hence, this paper studies the real-time feedback system of the funding data flow based on the data tracking and classification. The existing research work pays little attention to the secure deletion of private data in mobile cloud, especially the secure deletion of payment information and sensitive private messages generated by mobile cloud and mobile terminal, which is not recoverable, hence, the model is implemented with the optimization of data tracking framework and the classification. After building the model, this research wrk applies it into the funding data flow tracking and monitoring, as well as considering the real-time requirement. The proposed system has been tested on various data sets and the convincing results are achieved.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138082","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 Survey on Analysis of Genetic Diseases Using Machine Learning Techniques 利用机器学习技术分析遗传病的研究综述
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640723
B. Dhanalaxmi, K. Anirudh, G. Nikhitha, R. Jyothi
{"title":"A Survey on Analysis of Genetic Diseases Using Machine Learning Techniques","authors":"B. Dhanalaxmi, K. Anirudh, G. Nikhitha, R. Jyothi","doi":"10.1109/I-SMAC52330.2021.9640723","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640723","url":null,"abstract":"The approach of new technological developments in the genetic disease repository has facilitated genetic disease treatment. In the post-genomic time gene detection, which causes genetically excessive diseases, is one of the greatest deterrent tasks. Complex diseases are frequently very heterogeneous and make biological markers difficult to identify. Markers commonly depend on the Machine Learning Algorithms to define, but their success completely depends on the quality and dimensions of the data present. In the machine learning area, computers are promised to support people and analyze large and complex data systems primarily for the production of practically enhanced algorithms. A supervised machine learning methodology has been developed to predict complex genes that cause disease and experiment with the developed algorithm to improve and identify genetic classifications that engage in complex diseases. Genetic Disease Analyzer (GDA) was de veloped using machine learning using the Principal Component Analysis (PCA), Random forest, Naive Bayes and Decision Tree algorithms and the results were compared. The accuracy of 98.79% and sensitivity of 98.67% for the GEO data set is provided for the GDA model. The results of machine learning approaches were examined and their practical applications were discussed in the study of genetic and genomic data.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302548","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
An Encryption Algorithm for Long-Distance Data Transmission in the Internet of Things Based on Channel Nonlinear Transformation 基于信道非线性变换的物联网远距离数据传输加密算法
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640784
Ang Li, Chen Zhang, Lei Li
{"title":"An Encryption Algorithm for Long-Distance Data Transmission in the Internet of Things Based on Channel Nonlinear Transformation","authors":"Ang Li, Chen Zhang, Lei Li","doi":"10.1109/I-SMAC52330.2021.9640784","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640784","url":null,"abstract":"Communication and information transmission can be seen everywhere in people's lives, and its safety is extremely important. In order to further improve the security of data transmission in communication, in addition to adopting traditional source encryption codes, it is also very necessary to increase channel encryption measures. This thesis focuses on channel encryption, introduces and analyzes the encryption algorithm for long-distance data transmission in the Internet of Things based on channel nonlinear transformation. At the same time, in order to verify the feasibility, reliability and confidentiality of the above-mentioned channel encryption method, a verification communication system was designed.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115379263","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
Power Load flow analysis for Active Islanding Mode 主动孤岛模式下的电力潮流分析
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640725
Keshav Kumar, Anil Kumar Kori
{"title":"Power Load flow analysis for Active Islanding Mode","authors":"Keshav Kumar, Anil Kumar Kori","doi":"10.1109/I-SMAC52330.2021.9640725","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640725","url":null,"abstract":"For problem of load flow and power flow analysis is variable stability index. Also, arrangement of different bus system and fault tolerance occurrence across the load. In this case, resolution of power quality and improvement of power distribution performance apply islanding protection method. This paper is resenting result and simulation section arrangement of 9 bus system and Reducing Fault effects.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"64 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123443971","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 QRE-based Game Model for better IDS 使用基于qre的游戏模型创造更好的IDS
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9641035
M. J. Kumar, B. Rao, N. Sai, S. S. Kumar
{"title":"Using QRE-based Game Model for better IDS","authors":"M. J. Kumar, B. Rao, N. Sai, S. S. Kumar","doi":"10.1109/I-SMAC52330.2021.9641035","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9641035","url":null,"abstract":"WSN is a large-scale ad hoc network with the property of sufficient accessibility, including the all extents of correspondence applications, similar to medical care, home computerization, far off perceptions, snags recognition, and so forth WSN comprises of gigantic measure of small actuators, situated on better places which have minimal expense and simple establishment with limitations of restricted energy assets, computational limit and memory size. WSN is presented to numerous security dangers because of its restrictions, broadcast nature and unattended climate. Numerous distributions have proposed various IDS plans to effectively safeguard WSNs against security dangers. To conquer this issue, the proposed paper examines distinctive proposed IDS systems and analyzes them to survey the effectiveness from their qualities and shortcomings. In this paper, obstruction affirmation structure is masterminded and executed utilizing game hypothesis and AI to perceive various assaults. Game theory is organized and used to apply the IDS ideally in WSN. The game model is organized by depicting the players and the differentiating frameworks. QRE considered game hypothesis is utilized to pick the systems in ideal manner for the impedance's region. Further, these obstructions are assigned disavowing of association assault, rank assault or express sending assaults utilizing oversaw AI procedure subject as far as possible and rules. Results show that the entirety of the assaults are seen with commendable region rate and the proposed approach gives ideal utilization of IDS","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123986114","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
Real or Fake: An intrinsic analysis using supervised machine learning algorithms 真假:使用监督机器学习算法进行内在分析
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640675
Ameyaa Biwalkar, Ashwini Rao, K. Shah
{"title":"Real or Fake: An intrinsic analysis using supervised machine learning algorithms","authors":"Ameyaa Biwalkar, Ashwini Rao, K. Shah","doi":"10.1109/I-SMAC52330.2021.9640675","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640675","url":null,"abstract":"Different platforms of information data semantics are affected by Fake news in the recent years. Due to the inherent writing style and propagation speed of such false information, it has been difficult to pinpoint them from the true ones. The related work in the field makes use of various supervised as well as unsupervised machine-learning algorithms to classify and detect fake news. This paper provides an in-depth overview of the algorithms that are being used for detection. The paper also provides an analysis of notable algorithms on two datasets: Source based Fake News classification and Fake and Real News dataset. The results show that supervised algorithms with proper embedding and vectorizer models can provide great accuracies. The experimentation output shows the effectiveness of the proposed architecture.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123535390","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
Implementation of Machine Learning Classifier for DTN Routing DTN路由机器学习分类器的实现
2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2021-11-11 DOI: 10.1109/I-SMAC52330.2021.9640863
J. George, R. Santhosh
{"title":"Implementation of Machine Learning Classifier for DTN Routing","authors":"J. George, R. Santhosh","doi":"10.1109/I-SMAC52330.2021.9640863","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640863","url":null,"abstract":"This paper presents, better routing method in Delay Tolerant Network using Machine learning. Delay Tolerant Network is a wireless network, in which nodes are changing its positions dynamically in an unexpected way due to that Round trip time and error rates are very high. Examples are Disaster area, under the sea, Space communication, etc. In the proposed method neighbouring nodes are predicted by machine learning classifiers. These nodes use message history delivery information to deliver the message on destination. With the help of Bundle protocol implementation IBR-DTN [3], collects network traffic status and real-world location trace. These information uses to emulate DTN environment by Common Open Research Emulator (CORE) [2]. The new application is used to predict the results, preparation for the network history data, analysis and classification-based routing.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122275564","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
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