Journal of Big Data and Artificial Intelligence最新文献

A New Era of Artificial Intelligence Begins – Where Will it Lead Us? 人工智能新时代开启--它将把我们引向何方？

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.40

Jim Samuel, Abhishek Tripathi, E. Mema

引用次数: 0

In Memory of Dr. David Belanger 纪念戴维-贝兰杰博士

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.38

George Avirappattu, Mahmoud Daneshmand, Matthew Hale, M. Brennan-Tonetta, Jim Samuel, Rashmi Jain

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Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text 机器翻译能否传递情感？利用意大利语文本建立多语言情感分析有效性的分析流程

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.30

Richard Anderson, Carmela Scala, Jim Samuel, Vivek Kumar, P. Jain

{"title":"Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text","authors":"Richard Anderson, Carmela Scala, Jim Samuel, Vivek Kumar, P. Jain","doi":"10.54116/jbdai.v2i1.30","DOIUrl":"https://doi.org/10.54116/jbdai.v2i1.30","url":null,"abstract":"\u0000 \u0000 \u0000Abstract Natural language processing (NLP) is being widely used globally for a variety of value-creation tasks ranging from chat-bots and machine translations to sentiment and topic analysis and multilingual large language models (LLMs). However, most of the advances are initially implemented within the English language framework, and it takes time and resources to develop comparable resources in other languages. The advances in machine translations have enabled the rapid and effective conversion of content in global languages into English and vice-versa. This creates potential opportunities to apply English language NLP methods and tools to other languages via machine translations. However, although this idea is powerful, it needs to be validated and processes and best practices need to be developed and kept updated. The present research is an effort to contribute to the development of best practices and an evaluation framework. We present a systematic and repeatable state-of-the-art process to evaluate the viability of applying English language sentiment analysis tools to Italian text by using multiple English language machine translation mechanisms such that it can be easily extended to other languages. \u0000 \u0000 \u0000","PeriodicalId":516603,"journal":{"name":"Journal of Big Data and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512903","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

Investment under Uncertainty: The Role of Inventory Dynamics 不确定性下的投资：库存动态的作用

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.28

Chuanqian Zhang, Xue Cui, Sudipto Sarkar

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BERT based Blended approach for Fake News Detection 基于 BERT 的混合假新闻检测方法

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.27

Satish Mahadevan Sr, Shafqaat Ahmad

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Machine Learning Study: Identification of Skin Diseases for Various Skin Types Using Image Classification. 机器学习研究：利用图像分类识别各种皮肤类型的皮肤病。

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.32

Gulhan Bizel, Albert Einstein, Amey G Jaunjare, Sharath Kumar Jagannathan

{"title":"Machine Learning Study: Identification of Skin Diseases for Various Skin Types Using Image Classification.","authors":"Gulhan Bizel, Albert Einstein, Amey G Jaunjare, Sharath Kumar Jagannathan","doi":"10.54116/jbdai.v2i1.32","DOIUrl":"https://doi.org/10.54116/jbdai.v2i1.32","url":null,"abstract":"Increased machine learning methods have helped improvise human interaction with digital devices which helps in skin disease identification, prediction, and classification by employing algorithms. Image classification for skin disease application algorithms can detect caucasian skin tones but poorly performs when analyzing other skin colors. In this research, a deep learning algorithm was used to address the problem that other applications perform poorly with the classification of skin disease types. \u0000Convolutional Neural Network (CNN), a machine-learning algorithm was used to classify images and add the predicted images within the data set. The images in the data set covered a lot of patient factors such as age, sex, disease site (hand, feet, head, nails, etc.), skin color (white, yellow, brown, black) and different periods of lesions (early, middle, or late). Multiple private applications can detect skin diseases during the analysis. For the darker color skin population, the performance was poor, and skin cancer detection was not possible even with the help of image recognition. \u0000This research aims to conduct an analysis of visual searches within skin-related health searches to identify opportunities to provide digital health consumers with visual search results that are more representative of America’s diverse populations.","PeriodicalId":516603,"journal":{"name":"Journal of Big Data and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139640634","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

Crime Frequency During COVID - 19 and Black Lives Matter Protests COVID - 19 和 "黑人生命至上 "抗议活动期间的犯罪率

Journal of Big Data and Artificial Intelligence Pub Date : 2024-01-07 DOI: 10.54116/jbdai.v2i1.26

Aylin Kosar, Mehmet Turkoz

{"title":"Crime Frequency During COVID - 19 and Black Lives Matter Protests","authors":"Aylin Kosar, Mehmet Turkoz","doi":"10.54116/jbdai.v2i1.26","DOIUrl":"https://doi.org/10.54116/jbdai.v2i1.26","url":null,"abstract":"\u0000 \u0000 \u0000The COVID-19 disrupted the daily life of individuals within the United States and around the world when government restrictions were put into place. During the pandemic restrictions, social unrest took place after the death of George Floyd. Our objective is to study the crime rate during the pandemic and social unrest that took place after the death of George Floyd. We used data from four cities that were heavily affected with the pandemic and social unrest: Seattle, San Francisco, Los Angeles, and Philadelphia. Holt-Winters and SARIMA models were used to see if there was any change of crime during the pandemic and social unrest in addition to before and after the social unrest. Los Angeles had the lowest crime frequency out of the four cities while Philadelphia had the highest. All Holt-Winters models and SARIMA models showed around January 2020, during when the first case of COVID-19 occurred, crime was the same for all four cities except for Philadelphia where crime had dropped for a particular time until it increased again. There was no clear evidence to suggest that crime was affected during the COVID-19 pandemic and the social unrest during the protests. \u0000 \u0000 \u0000","PeriodicalId":516603,"journal":{"name":"Journal of Big Data and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512921","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