2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)最新文献_第2页

Information Extraction from Arabic Medications Leaflets 阿拉伯语药物单张信息提取

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013568

Adnan Yahya, Hala Salameh, Maram Belbeisi, Noor Shamasneh

{"title":"Information Extraction from Arabic Medications Leaflets","authors":"Adnan Yahya, Hala Salameh, Maram Belbeisi, Noor Shamasneh","doi":"10.1109/AICT55583.2022.10013568","DOIUrl":"https://doi.org/10.1109/AICT55583.2022.10013568","url":null,"abstract":"Making information in electronic documents easily accessible has been a major concern over the past years. There has been increasing interest in gleaning information from unstructured text and presenting it as structured data using information extraction (IE). Since Arabic has seen major growth in web content, mainly unstructured text, the need for IE from Arabic documents has gained importance. The processing capacity needed for IE far exceeds human ability to extract knowledge manually. The medical field is one such area, where awareness of health issues makes the task of automating medical informatics crucial for better access to medical knowledge. Thus, work on extracting information from medical documents has increased rapidly. In this paper we address the issue of IE from Arabic drug leaflets. We use a combination of rule-based, machine learning and deep learning methods and employ a suit of tools that account for the particularities of Arabic to extract information from Arabic drug package inserts to make this information available in structured form and thus better accessible to regular users and health care providers. A prototype system that utilizes the IE results was developed with useful functionality such as alerting to possible Adverse Drug Reactions (ADR) and finding drug alternatives.","PeriodicalId":441475,"journal":{"name":"2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124599108","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

Turnstile Access based on Facial Recognition and Vaccine Passport Verification 基于人脸识别和疫苗护照验证的旋转门通道

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013579

S. Aliyeva, Ali Parsayan

引用次数: 0

Discrete Hilbert Transform via Memristor Crossbars for Compact Biosignal Processing 基于忆阻交叉棒的离散希尔伯特变换在紧凑生物信号处理中的应用

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013604

Lei Zhang, Zhuolin Yang, Kedar K. Aras, Igor R. Efimov, G. Adam

引用次数: 0

Artificial Intelligence in Medicine for Chronic Disease Classification Using Machine Learning 使用机器学习进行慢性疾病分类的医学人工智能

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013587

M. Rakhimov, Ravshanjon Akhmadjonov, Shahzod Javliev

{"title":"Artificial Intelligence in Medicine for Chronic Disease Classification Using Machine Learning","authors":"M. Rakhimov, Ravshanjon Akhmadjonov, Shahzod Javliev","doi":"10.1109/AICT55583.2022.10013587","DOIUrl":"https://doi.org/10.1109/AICT55583.2022.10013587","url":null,"abstract":"Artificial intelligence (AI) systems in medicine are one of the most important modern trends in global healthcare. Artificial intelligence technologies are fundamentally changing the global healthcare system, making it possible to radically rebuild the system of medical diagnostics while reducing healthcare costs. AI is actively used in research to develop methods for diagnosing coronary heart disease (CHD). There are different types of CHD. Before treating a disease, it is necessary to determine which class of diseases it belongs to. Based on the feature space of the disease, it is possible to classify the type of CHD. Machine learning algorithms can solve this problem. The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve classification problems. The dataset is the more important part of the supervised machine learning algorithm for training. Gathering data is the most important step in solving any supervised machine learning problem. But choosing more important part from the collected data is one of the tasks to be solved. The main purpose of this study is to select more useful parametric attributes from the dataset to obtain a high F1-score of CHD classification.","PeriodicalId":441475,"journal":{"name":"2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126785610","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

Genetic Algorithm for RCPSP With Fuzzy NPV 具有模糊NPV的RCPSP遗传算法

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013494

Aleksandr M. Bulavchuk, D. Semenova

引用次数: 1

Proactive Computer Network Monitoring based on Homogeneous LSTM Ensemble 基于同构LSTM集成的主动计算机网络监控

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013593

R. Shikhaliyev

引用次数: 0

Real-time sleep prediction using a virtual sensor to estimate Heart Rate Variability through Respiratory Rate 实时睡眠预测使用虚拟传感器估计心率变异性通过呼吸率

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013549

Luigi Pugliese, Massimo Violante, Sara Groppo

引用次数: 1

Reinforcement Learning Based Robot Control 基于强化学习的机器人控制

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013595

Z. Guliyev, Ali Parsayan

{"title":"Reinforcement Learning Based Robot Control","authors":"Z. Guliyev, Ali Parsayan","doi":"10.1109/AICT55583.2022.10013595","DOIUrl":"https://doi.org/10.1109/AICT55583.2022.10013595","url":null,"abstract":"Reinforcement learning (RL) has been proven to be a feasible method for learning complicated actions autonomously from sensory observations. Even though many of the deep RL studies have been centered on modelled control and computer games, which has nothing to do with the limits of learning in actual surroundings, deep RL has also revealed its potential in allowing robots to acquire complicated abilities in the real-world situations. Real-world robotics, on the other hand, is an intriguing area for testing the algorithms of this kind, because it is directly related to the learning procedure of humans. Deep RL might enable developing movement abilities without a precise modelling of the robot dynamics and with minimum engineering. However, because of hyper-parameter sensitivity and low sampling capability, it is difficult to implement deep RL to robotic tasks involving real-world applications. It is comparable simple to tune hyper-parameters in simulations, while it can be a challenging task when it comes to physical world, for example, biped robots. Acquiring the ability to move and perceive in the actual world involves a variety of difficulties, some are simpler to handle than others that are frequently overlooked in RL studies which are limited to simulated environments. This paper provides approaches to deal with a variety of frequent difficulties in deep RL arising while training a biped robot to walk and follow a specific path.","PeriodicalId":441475,"journal":{"name":"2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121948303","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

Multiagent Reinforcement Learning for Integrated Network: Applying to a Part of the Road Network of Krasnoyarsk City 集成网络的多智能体强化学习:在克拉斯诺亚尔斯克市部分道路网络中的应用

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013610

Timofei I. Tislenko, D. Semenova, Nataly A. Sergeeva, E. Goldenok, Nadezhda V. Kononova

引用次数: 0

Quantitative and Semantic Analysis of Texts in Turkic Languages using Universal Declaration of Human Rights (UDHR) as a Corpus 以《世界人权宣言》为语料库的突厥语语篇数量语义分析

2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2022-10-12 DOI: 10.1109/AICT55583.2022.10013645

A. Adamov, Gozel Khasanova

{"title":"Quantitative and Semantic Analysis of Texts in Turkic Languages using Universal Declaration of Human Rights (UDHR) as a Corpus","authors":"A. Adamov, Gozel Khasanova","doi":"10.1109/AICT55583.2022.10013645","DOIUrl":"https://doi.org/10.1109/AICT55583.2022.10013645","url":null,"abstract":"Thanks to Web, ubiquitous digital technologies and the increasing usage of digital environment by humans for work, entertainment, education and other activities, huge amounts of textual data is generated and available online. Text is the most informative and at the same time most sophisticated data type in terms of its comprehension by machines. The Text Analytics is a field that involves number of computer science disciplines to process textual data and transforms it into computer readable format suitable for another field of study Natural Language Processing to extract meaning.This research paper is an attempt to apply broad variety of statistical analysis methods to the corpora of several Turkic languages using Universal Declaration of Human Rights as a Corpus. Quantitative Text Analysis as a research area is focused on understanding the human language through statistics and numbers. As the language is the most effective tool to describe the social world, the Quantitative Text Analysis enables social exploration of the rial world at the scale.","PeriodicalId":441475,"journal":{"name":"2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124297190","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