2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)最新文献_第6页

Artificial Intelligence into Multimedia Deepfakes Creation and Detection 人工智能在多媒体深度伪造创作与检测中的应用

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099744

Moaiad Ahmed Khder, Samer Shorman, Duaij Thabit Aldoseri, Mohammed Mansoor Saeed

引用次数: 0

Data Mining Hospital Treatment and Discharge Summary of Sickle Cell Disease Patients 数据挖掘镰状细胞病患者的住院治疗和出院总结

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099773

Mohammed Gollapalli, A. Alfaleh

{"title":"Data Mining Hospital Treatment and Discharge Summary of Sickle Cell Disease Patients","authors":"Mohammed Gollapalli, A. Alfaleh","doi":"10.1109/ITIKD56332.2023.10099773","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099773","url":null,"abstract":"Sickle cell disease (SCD) is a hereditary blood disorder that affects certain parts of the world. This disease affects hemoglobin, causing red blood cells to change shape, such as sickle and crescent, making it difficult to supply oxygen to all of the human body's cells. Various genotypes of SCD have been discovered; the most common disorder is sickle cell anemia. This study is a continuation of our ongoing research on 191,406 clinical records of SCD patients who visited and got hospitalized over a 12-year period (between 2008 - 2020). This paper focused on conducting the retrospective analysis and then applying data mining classification algorithms on SCD patients' data based on hospitalization records, hospital visits, hospital admissions reasons, department patients were admitted to, the length of time patients were treated in the hospital, blood transfer section for S C D patients, and discharge reason for different types of S C D patients. Five distinct classification models with ten cross-validations were experimented using the Naive Bayes, J48, SVM, NN, and PART algorithms. Furthermore, parameter optimization was carried out to determine the optimal classification results of each algorithm. Naïve Bayes with an accuracy of 95.50%, was faster, correctly classified clinical cases, and provided detailed correlation results for each of the target features. Finally, we extracted knowledge clusters on hospital clinical services for SCD patients, which were then validated by medical doctors in order to better serve SCD patients visiting the hospital.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126063070","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

Energy-Efficiency in Cloud Datacenters: A Survey 云数据中心的能源效率:调查

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099685

M. AlGhamdi, Ghaida Alsaab, Nada Alsunbol, Lamya Albraheem

引用次数: 0

Determining Linguistic Features of Hate Speech from 2016 Philippine Election-Related Tweets 从2016年菲律宾选举相关推文中确定仇恨言论的语言特征

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10100008

Raphael Christen K. Enriquez, M. R. Estuar

{"title":"Determining Linguistic Features of Hate Speech from 2016 Philippine Election-Related Tweets","authors":"Raphael Christen K. Enriquez, M. R. Estuar","doi":"10.1109/ITIKD56332.2023.10100008","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100008","url":null,"abstract":"Hate speech is characterized as a deliberate attack directed towards a group of people motivated by aspects of the group, s identity. There is a growing interest in solutions involving automatic hate speech detection in response to the proliferation of hate speech. However., most automatic hate speech detection tools are designed for high-resource languages such as English which results in challenges in detecting hate speech in low-resource languages such as Filipino. Social media users within the Philippines predominantly use native language or a code-switched variation such as Taglish as the preferred linguistic style in online communication. This study seeks to determine linguistic features that characterize hate speech in the Philippine setting. The study characterizes hate speech using the following features: bilingual., part-of-speech., and psycho-linguistic features. Feature extraction was facilitated via fastText., NLTK (Natural Language Toolkit)., and LIWC (Linguistic Inquiry and Word Count) from an existing Filipino hate speech corpus collected during the 2016 Philippine Presidential Elections. Results show that hate speech from this dataset has significantly different features from non-hate speech. Specifically., the distinct features include language dominance., frequency of code-switching., frequency of parts-of-speech., and LIWC's summary variables and psychological process. These features which have been demonstrated to be statistically different between hate speech and non-hate speech can be leveraged to augment existing hate speech detection models., particularly within low-resource language contexts.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"23 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132805619","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 Deep Learning Model for Classification of EEG Signals for Neuromarketing 神经营销中脑电信号分类的深度学习模型

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10100014

Syed Muhammad Usman, Syed Mohsin Ali Shah, Onome Christopher Edo, J. Emakhu

{"title":"A Deep Learning Model for Classification of EEG Signals for Neuromarketing","authors":"Syed Muhammad Usman, Syed Mohsin Ali Shah, Onome Christopher Edo, J. Emakhu","doi":"10.1109/ITIKD56332.2023.10100014","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100014","url":null,"abstract":"Advertising campaigns for marketing and advertisement of different consumer items is a well-known strategy to boost sales and public awareness. It can lead towards greater profit margins for the factories or companies. Reproduction of products typically depends on numerous factors, such as market usage, reviewer comments, ratings, etc. In neuromarketing a person is examined with the help of EEG signals generated in his/her brain so that his emotions can be recognized for making certain decisions. Therefore, research in this area is in high demand but has not yet achieved an adequate standard. We provide a predictive modelling framework to interpret consumer preferences for e-commerce goods by analyzing EEG data. In this research study, volunteers of varying ages and genders were asked to visually feel the effect of different packaging of products and the corresponding EEG signals generated inside their brains were monitored. Several experiments by varying approaches were performed on the dataset that contain the EEG signals of consumers. Two machine learning and a deep learning classifier were employed to evaluate the accuracy of the model. After conducting different experiments, it was observed that the proposed approach performs superior, and the framework can be leveraged to create a more effective business model.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123897883","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

DEWA R&D Data Lake: Big Data Platform for Advanced Energy Data Analytics DEWA研发数据湖:先进能源数据分析的大数据平台

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099717

H. Y. Youssef, M. Ashfaque, Jayakumar V. Karunamurthy

引用次数: 1

Exploring The Role of Big Data Algorithm Recommendation in Smart Cities- Taking Book recommendation As an Example 探索大数据算法推荐在智慧城市中的作用——以图书推荐为例

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099656

Yijia Cheng, Haojie Chen, Lu Xu, Kunhao Chen, Xiaofan Wang, Zhengdong Huang

引用次数: 0

Generation and retrieval of procedural memory using natural intelligence for an articulated robot 基于自然智能的关节机器人程序记忆生成与检索

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10100232

Souraneel Chattoraj, T. Kalganova

{"title":"Generation and retrieval of procedural memory using natural intelligence for an articulated robot","authors":"Souraneel Chattoraj, T. Kalganova","doi":"10.1109/ITIKD56332.2023.10100232","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100232","url":null,"abstract":"This article presents the basics of a working framework to emulate the cognitive function of procedural learning found in natural intelligence to aid in kinematic decision making in a robot. This contrasts with pure iterative recursion or regression techniques. Articulated robots comprise of only rotary joints with a stationary or mobile base reference to the world and are useful in manufacturing, maintenance, and operations to make labor intensive work easier for humans. The motivation for this work is to utilize the potential of cybernetic automation systems to keep up with scaling demands in supply chain production and further build sustainable means to support our growth in the future. In this research a robot is modelled for the process of calculating actuation commands from a starting point in the Euclidean task space to a target. This is known as Inverse Kinematics (IK), named in distinction to Forward Kinematics (FK) which calculates where a point on the robot will be in the task space, for a predefined set of joint positions. We aim to cover the gap in research to connect the development of procedural memory to path planning for a link manipulator robot. We ask the question, if there is any benefit of using procedural memory to reduce the calculation time taken for inverse kinematics to predict a path.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129354925","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 Single Time of Quantum Computer for Shor's Factoring Algorithm 利用量子计算机的单时间进行Shor因子分解算法

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10099702

Yousef AlHammadi

引用次数: 0

Cloud-Based Big Data Analytics on IoT Applications 基于云的物联网应用大数据分析

2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) Pub Date : 2023-03-08 DOI: 10.1109/ITIKD56332.2023.10100150

Ghadeer Alrehaili, N. Galam, Rawan Alawad, Lamya Albraheem

引用次数: 0