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Automated Exploratory Data Analysis 自动化探索性数据分析
UMT Artificial Intelligence Review Pub Date : 2021-12-31 DOI: 10.32350/air.0102.04
Hubble Dhillon
{"title":"Automated Exploratory Data Analysis","authors":"Hubble Dhillon","doi":"10.32350/air.0102.04","DOIUrl":"https://doi.org/10.32350/air.0102.04","url":null,"abstract":"This study introduces a novel framework that can be generalized for an automated exploratory data analysis to test a given hypothesis. The current work is about a drug-related trend and also provides a specific model to test a motivation-related hypothesis in the case of COVID-19. With the utilization of the right, appropriate, and optimized solution available to solve a problem, it is significant that the user feels motivated to delve into the solution for the betterment of society. \u0000KEYWORDS: automated exploratory data analysis, motivation-related hypothesis","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125650242","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
Convolutional Autoencoder for Image Denoising 卷积自编码器图像去噪
UMT Artificial Intelligence Review Pub Date : 2021-12-31 DOI: 10.32350/air.0102.01
Abdul Ghafar, Usman Sattar
{"title":"Convolutional Autoencoder for Image Denoising","authors":"Abdul Ghafar, Usman Sattar","doi":"10.32350/air.0102.01","DOIUrl":"https://doi.org/10.32350/air.0102.01","url":null,"abstract":"Image denoising is a process used to remove noise from the image to create a sharp and clear image. It is mainly used in medical imaging, where due to the malfunctioning of machines or due to the precautions taken to protect patients from radiation, medical imaging machines create a lot of noise in the final image. Several techniques can be used in order to avoid such distortions in the image before their final printing. Autoencoders are the most notable software used to denoise images before their final printing. These software are not intelligent so the resultant image is not of good quality. In this paper, we introduced a modified autoencoder having a deep convolutional neural network. It creates better quality images as compared to traditional autoencoders. After training with a test dataset on the tensor board, the modified autoencoder is tested on a different dataset having various shapes. The results were satisfactory but not desirable due to several reasons. Nevertheless,  our proposed system still performed better than traditional autoencoders. \u0000KEYWORDS: image denoising, deep learning, convolutional neural network, image autoencoder, image convolutional autoencoder","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"7 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114887929","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
Comparison of the Predictive Models of Human Activity Recognition (HAR) in Smartphones 智能手机人类活动识别(HAR)预测模型的比较
UMT Artificial Intelligence Review Pub Date : 2021-12-31 DOI: 10.32350/air.0102.03
Muhmammad Ehsan
{"title":"Comparison of the Predictive Models of Human Activity Recognition (HAR) in Smartphones","authors":"Muhmammad Ehsan","doi":"10.32350/air.0102.03","DOIUrl":"https://doi.org/10.32350/air.0102.03","url":null,"abstract":"This report compared the performance of different classification algorithms such as decision tree, K-Nearest Neighbour (KNN), logistic regression, Support Vector Machine (SVM) and random forest. The dataset comprised smartphones’ accelerometer and gyroscope readings of the participants while performing different activities, such as walking, walking downstairs, walking upstairs, standing, sitting, and laying. Different machine learning algorithms were applied to this dataset for classification and their accuracy rates were compared. KNN and SVM were found to be the most accurate of all. \u0000KEYWORDS— decision tree, Human Activity Recognition (HAR), K-Nearest Neighbour (KNN), logistic regression, random forest, Support Vector Machine (SVM)","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128361622","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
Rumor Identification on Twitter Data for 2020 US Presidential Elections with BERT Model 基于BERT模型的2020年美国总统大选Twitter数据谣言识别
UMT Artificial Intelligence Review Pub Date : 2021-06-30 DOI: 10.32350/umtair.11.03
A. Rahim
{"title":"Rumor Identification on Twitter Data for 2020 US Presidential Elections with BERT Model","authors":"A. Rahim","doi":"10.32350/umtair.11.03","DOIUrl":"https://doi.org/10.32350/umtair.11.03","url":null,"abstract":"Social Media platforms provide rich resources to its users to connect, share and search the information of their interest. It is becoming part of every day’s life and politics is no different. In fact, social media platforms are becoming more significant when it comes to governmental issues and political campaigns. As information spreads within seconds, it’s extremely challenging to control and monitor the authenticity of the information. Many attempts have been made in this regard, in this paper, we briefly overview some major efforts and discuss the patterns found in the rumors and fake news that can be found by latest machine learning techniques. We extracted the tweets data specifically with hashtag_donaldtrump during the high time of 2020 US presidential election and to test their authenticity and the similar data from fact check websites Snopes.com, factcheck.org and politifact.org. We applied the already established BERT model to train on checked data and tested on the one million tweets data. In doing so, we found a reliable accuracy and proposed the fact that once all the truthful information is saved and pretrained in the model, it is able to auto identify the validation of the information shared. Also, once established such kind of models are also helpful in finding the behavior of rumors and pattern showed for American politics.","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114296636","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
Self-Operating Stock Exchange – A Deep Reinforcement Learning Approach 自操作证券交易所——一种深度强化学习方法
UMT Artificial Intelligence Review Pub Date : 2021-06-30 DOI: 10.32350/umtair.11.02
Hammad Ghulam Mustafa
{"title":"Self-Operating Stock Exchange – A Deep Reinforcement Learning Approach","authors":"Hammad Ghulam Mustafa","doi":"10.32350/umtair.11.02","DOIUrl":"https://doi.org/10.32350/umtair.11.02","url":null,"abstract":"Stock trading approaches play an important role in equity. However, it is tough to create a financially beneficial approach in a complicated and evolving stock market. In this manuscript, we suggest an epsilon greedy policy in our DQN prototype that allows you to get effective policy for the agent this could optimize the predicted values of the total reward across any sequential steps ranging from the present state i. E. To maximize the state-action-value function through engaging with the environment q (s, a) to recommend when to buy, sell or hold. In this prototype, the state depends on routine principles of buy, sell or hold of existing data and the state alter as the buying and selling session alters. The prototype is able to grow rapidly the responses to market on reward signals but by agents which will allow us to understand about the holding and buying of the stocks.","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124229156","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
Architectures, Security Issues, and Usage Scenarios of EC EC的体系结构、安全问题和使用场景
UMT Artificial Intelligence Review Pub Date : 2021-06-30 DOI: 10.32350/umtair.11.04
M. Sattar, Amna Mubashar, Rimsha Fareed, Muhammad Rizwan
{"title":"Architectures, Security Issues, and Usage Scenarios of EC","authors":"M. Sattar, Amna Mubashar, Rimsha Fareed, Muhammad Rizwan","doi":"10.32350/umtair.11.04","DOIUrl":"https://doi.org/10.32350/umtair.11.04","url":null,"abstract":"Demand for the digital media is increasing exponentially due to the data generated with regards to IoT devices, thus for these growing needs certain advancements have been made in various technologies like cloud computing which has transitioned to fog and edge computing. The differences between each technology relate to many factors like security, privacy, Big data issues, bandwidth, and radio access networking. Thus, we have discussed the problems faced by older versions of cloud computing and how Mobile Edge Computing (MEC) helps to overcome most of these problems. MEC is explored where it offers real-time information thus providing benefits to the end-users. The growth of MEC is such that, as discussed further, it is used in normal habitual routines like real-time grocery shopping. This paper explores the various architectures, use cases and security aspects of edge computing.","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129580159","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 Literature Review of Artificial Intelligence 人工智能的文献综述
UMT Artificial Intelligence Review Pub Date : 2021-06-30 DOI: 10.32350/air.11.01
Agha Wafa Abbas Wafa, Muzammil Hussain Muzammil Hussain
{"title":"A Literature Review of Artificial Intelligence","authors":"Agha Wafa Abbas Wafa, Muzammil Hussain Muzammil Hussain","doi":"10.32350/air.11.01","DOIUrl":"https://doi.org/10.32350/air.11.01","url":null,"abstract":"Artificial Intelligence has ameliorated in prominence during the last decade. In practically every area, Artificial Intelligence has had a consequential contribution. It has grown into a tremendous technology that has revolutionized the way human beings communicate and may transform the way human beings look to the future. Nowadays, discoveries in artificial intelligence (AI) that outperform humans in some tasks generate headlines. I exhibit a spiffing updated literature-review for Artificial Intelligence. Other works offered domain-specific plus non-comprehensive, as well as shortcomings on their introduction, background information, related work, and discussion and future directions. This research intends to provide diverse AI techniques, which can be implement to preclude cyber-assaults; the Artificial Intelligence and its uses in a variety of fields. This literature review will definitely assist scientists and readers in comprehending the technologies, fields, uses, and applications of AI. Furthermore, in terms of state of knowledge, introduction, background information, related work, discussion, and future directions, this literature review outperformed previous literature review publications.","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127309644","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: 56
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