2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)最新文献_第3页

Fake news detection using discourse segment structure analysis 基于语段结构分析的假新闻检测

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058106

Anmol Uppal, Vipul Sachdeva, Seema Sharma

{"title":"Fake news detection using discourse segment structure analysis","authors":"Anmol Uppal, Vipul Sachdeva, Seema Sharma","doi":"10.1109/Confluence47617.2020.9058106","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058106","url":null,"abstract":"Online news platforms greatly influence our society and culture in both positive and negative ways. As online media becomes more dependent for source of information, a lot of fake news is posted online, that widespread with people following it without any prior or complete information of event authenticity. Such misinformation has the potential to manipulate public opinions. The exponential growth of fake news propagation have become a great threat to public for news trustworthiness. It has become a compelling issue for which discovering, examining and dealing with fake news has increased in demand. However, with the limited availability of literature on the issue of uncovering fake news, a number of potential methodologies and techniques remains unexplored. The primary aim of this paper is to review existing methodologies, to propose and implement a method for automated deception detection. The proposed methodology uses deep learning in discourse-level structure analysis to formulate the structure that differentiates fake and real news. The baseline model achieved 74% accuracy.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125163297","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: 15

Improvement in fuel economy of hybrid hydraulic powertrain by conducting a comparative study of two different optimization strategies 通过两种不同优化策略对混合动力液压传动系统燃油经济性的提高进行比较研究

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9057867

Bedatri Moulik, Anupama Prakash, A. Ganguly

引用次数: 0

Collective Intelligence: When, Where and Why 集体智慧:时间、地点和原因

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058000

Vanshika Nehra, Renuka Nagpal, Rajni Sehgal

{"title":"Collective Intelligence: When, Where and Why","authors":"Vanshika Nehra, Renuka Nagpal, Rajni Sehgal","doi":"10.1109/Confluence47617.2020.9058000","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058000","url":null,"abstract":"The term “Collective” is just not restricted to the human beings but can also be referred to the organisms such as flock of birds, swarm of bees, colony of bats etc. In computer environments, the term may also refer to groups of virtual artificially intelligent agents. Most generally it can applicable to the workings of the entire planet or universe as smart organization whose intelligence is supplied and manifested through the entities within it. Collective Intelligence is a no new terms infact it’s been used from several decades now but what’s new is the emergence of computer technology which makes it a new and one of the most promising application of it used in a variety of field. Machine learning and Artificial Intelligence are making an enormous buzz around the world. The plenty of utilizations in Artificial Intelligence have changed the substance of innovation. This paper would give an overview of the promising future aspects and researches in the field of Collective Intelligence in brief. We need to concentrate on the elements that guide collective intelligence if we really want to optimize our groups for excellent cooperation. We need to concentrate on personality characteristics that are not so simple to follow, yet they are critical to the long-term achievement of organizations, such as intellect, consciousness, compassion, empathy, and regard. In this paper along with the definition of the Collective Intelligence, it would be measured, compared with individual intelligence and its applications are studied in brief.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133219786","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

Review on computer aided diagnosis of pancreatic cancer using Artificial Intelligence System 人工智能系统在胰腺癌计算机辅助诊断中的研究进展

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9057939

H. S. Saraswathi, Mohammed Rafi, K. G. Manjunath, A. Shankar

引用次数: 2

Classification and Diagnosis of Invasive Ductal Carcinoma Using Deep Learning 浸润性导管癌的深度学习分类与诊断

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058077

F. Siddiqui, Shubham Gupta, Shashwat Dubey, Shariq Murtuza, Arti Jain

引用次数: 5

Modeling and Simulating large scale Cyber Effects for Cybersecurity using Riverbed Modeler 使用河床建模器建模和模拟网络安全的大规模网络效应

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058026

Rajiv Parwani, H. Al-Amoudi, Abdul Jhummarwala

{"title":"Modeling and Simulating large scale Cyber Effects for Cybersecurity using Riverbed Modeler","authors":"Rajiv Parwani, H. Al-Amoudi, Abdul Jhummarwala","doi":"10.1109/Confluence47617.2020.9058026","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058026","url":null,"abstract":"Organizations have moved towards service based architectures and applications are hosted in the Clouds. An interruption in online delivery of such services is of grave concern to the organizations as it causes problems to a large number of users. The identification of the security vulnerability in these systems which can be exploited by cybercriminals is of utmost importance when developing an architecture for online hosting of applications. Defensive capabilities to thwart the cybercriminals must be deployed. A Distributed Denial of Service (DDoS) attack is commonly employed to create panic and prevent the delivery of services to legitimate users. This paper presents the use of network security simulation and modeling for understanding the effect of cyberattacks such as DDoS on a system. Experimentations conducted include deployment of services such as FTP, Email, and HTTP in a simulated environment. The main aim is to simulate network infrastructure and security policies before online deployment of the services. As these services will be used by a large number of users concurrently, it would be important to create a resilient system against modern DDoS attacks. The observations from the simulations will allow to share and expand the knowledge of the users for development of secure systems.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115530196","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

Segmentation and Detection of Road Region in Aerial Images using Hybrid CNN-Random Field Algorithm 基于cnn -随机场混合算法的航拍图像道路区域分割与检测

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058045

Sukanya, Gaurav Dubey

{"title":"Segmentation and Detection of Road Region in Aerial Images using Hybrid CNN-Random Field Algorithm","authors":"Sukanya, Gaurav Dubey","doi":"10.1109/Confluence47617.2020.9058045","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058045","url":null,"abstract":"Road detection and segmentation is an important aspect in navigation system and is widely used to detect new roads and patterns in the region. These system has the main objective to help navigate the autonomous vehicle and robot on the ground. Road detection is very useful in finding valid road path where the vehicle can go for supportive vehicles preventing the collision with the obstacles, object detection on the road and other necessary information exchange. It has a variety of uses such as the disaster monitoring, traffic monitoring, crop monitoring, border surveillance, security and so on. There are several techniques used for detection and segmentation purpose of roads such as Artificial Neural Network, Support Vector Machine (SVM), Self-Organizing Map (SOM), Convolution Neural Network (CNN), and Deep learning techniques. In this paper, a new technique for road detection and segmentation is proposed which includes a combination algorithm of CNN and Random Field segmentation for road maps using aerial images. This road detection and segmentations give alternative solution for road classification and detection with a higher accuracy. In this system normally accuracy (ACC) have an average range of 97.7%.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114017974","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

Key Attributes for a Quality Mobile Application 高质量移动应用程序的关键属性

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058278

Parita Jain, Anupam Sharma, P. Aggarwal

引用次数: 4

Future Location Prediction of a Mobile User Using Historic Visiting Patterns 利用历史访问模式预测移动用户的未来位置

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058084

A. Kumari, Chandan Chhabra, Saurabh Singh

{"title":"Future Location Prediction of a Mobile User Using Historic Visiting Patterns","authors":"A. Kumari, Chandan Chhabra, Saurabh Singh","doi":"10.1109/Confluence47617.2020.9058084","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058084","url":null,"abstract":"The ability of modern smartphones to provide us with real time location-based data is one of its most important features. Being able to predict a person’s future location based on the real time location data would be the next step in utilizing this functionality. Using this functionality, combined with machine learning one’s probable destination can be predicted with a reasonable accuracy. People don’t always use map-based navigation for the places they visit every day, like their work place or school and there may be significant traffic on the regular route taken, however, if our device knows where we’re headed, it can warn us beforehand and help us reroute. This functionality can also be used by cops to determine the future location of a criminal fleeing a crime scene.These features and functionalities can be implemented through various machine learning algorithms which are compared to determine the most accurate one. The proposed system can predict a user’s future location using the current location and time, learning from the user’s previously visited locations.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115667009","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

Performance Analysis of various Information Platforms for recognizing the quality of Indian Roads 印度道路质量识别的各种信息平台的性能分析

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9057829

Prabhat Singh, Abhay Bansal, Sunil Kumar

引用次数: 4