Review
Construction & Building Technology
Seungwon Baek, Wooyong Jung, Seung H. Han
Summary: This paper reviews the current state and future insights of text analytics in the construction industry, pointing out the diverse sources of text data and the dominance of ontology- and rule-based approaches, with recent attempts to incorporate machine learning methods. It envisions potential advancements in construction engineering and management through the latest text analysis techniques fueled by digital transformation.
AUTOMATION IN CONSTRUCTION
(2021)
Review
Chemistry, Multidisciplinary
Yili Wang, Jiaxuan Guo, Chengsheng Yuan, Baozhu Li
Summary: Twitter Sentiment Analysis is an active subfield of text mining, which has attracted considerable interest among researchers. This research provides a comprehensive review of the latest developments in this area, including newly proposed algorithms and applications. The survey classifies each publication based on its significance to specific TSA methods and depicts the current research direction in the field of TSA.
APPLIED SCIENCES-BASEL
(2022)
Review
Biochemistry & Molecular Biology
Sofia I. R. Conceicao, Francisco M. Couto
Summary: In building biological networks, providing reliable interactions is crucial. Text mining methods can help extract knowledge from scientific literature to overcome the challenge of tracking recent discoveries. These tools can lead to more reliable and personalized networks by identifying relations between entities of interest.
Article
Computer Science, Information Systems
Amina Boufrida, Zizette Boufaida
Summary: The paper introduces a framework for acquiring complex relationships and coding rules from textual content by utilizing natural language processing tools and text matching techniques. It enriches the existing domain ontology and enhances relational expressiveness by combining existing domain knowledge with newly derived rules.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Health Care Sciences & Services
Emily Hadley, Laura Haak Marcial, Wes Quattrone, Georgiy Bobashev
Summary: This research evaluates the free-response text section in the F990H form of nonprofit hospitals using natural language processing, focusing on health equity and disparities. The study finds that although hospitals show increasing awareness of health equity and disparities in their community benefit documentation, this does not necessarily align with public interest or result in additional action. Further investigation on alignment with community health needs assessments and improvements to F990H reporting requirements are proposed.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hyejin Jang, Yujin Jeong, Byungun Yoon
Summary: This study proposes a methodology for designing a TechWord-based lexical database that aims to improve the text mining performance of technological information.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biochemical Research Methods
Bram van Es, Leon C. Reteig, Sander C. Tan, Marijn Schraagen, Myrthe M. Hemker, Sebastiaan R. S. Arends, Miguel A. R. Rios, Saskia Haitjema
Summary: When developing models for clinical information retrieval and decision support systems, the extraction of labels from free text in electronic health records is crucial. This study compares three methods for negation detection in Dutch clinical notes, and found that the biLSTM and RoBERTa-based models consistently outperformed the rule-based model in terms of accuracy. The findings also provide insights for further improvement and suggest the viability of different approaches depending on the use case.
BMC BIOINFORMATICS
(2023)
Article
Computer Science, Information Systems
Gildasio Antonio de Oliveira Junior, Rafael Timoteo de Sousa Jr, Robson de Oliveira Albuquerque, Luis Javier Garcia Villalba
Summary: This research focuses on the robustness and vulnerabilities of sentiment classifiers in social media applications against new adversarial attacks, proposing some countermeasures that might mitigate these attacks.
COMPUTER COMMUNICATIONS
(2021)
Article
Engineering, Biomedical
Javier O. Corvi, Austin McKitrick, Jose M. Fernandez, Carla V. Fuenteslopez, Josep L. Gelpi, Maria-Pau Ginebra, Salvador Capella-Gutierrez, Osnat Hakimi
Summary: This article introduces an automated system for extracting biomaterial-related information from MEDLINE research abstracts using text mining technologies. The system identifies 16 concept types related to biomaterials and deposits them, along with the abstract and relevant metadata, into the DEBBIE database. DEBBIE is accessible through a web application that enables keyword searches and displays results in a user-friendly manner, facilitating efficient organization and mapping of biomaterials information.
ADVANCED HEALTHCARE MATERIALS
(2023)
Article
Computer Science, Information Systems
Zhiwen Xie, Runjie Zhu, Jin Liu, Guangyou Zhou, Jimmy Xiangji Huang, Xiaohui Cui
Summary: This paper introduces the construction of medical knowledge graphs based on machine learning and artificial intelligence in response to the COVID-19 pandemic. It proposes a graph feature collection network (GFCNet) for COVID-19 KG embedding task, which considers both neighbor and attribute features in KGs. Experimental results on the COVID-19 drug KG dataset demonstrate the effectiveness and efficiency of the proposed model, and future directions for deepening the study on COVID-19 KGE task are discussed.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Marco Arazzi, Serena Nicolazzo, Antonino Nocera, Manuel Zippo
Summary: The study of Online Social Networks provides opportunities to understand how human society works at scale. This paper focuses on the language used by users and its impact on online communities. By adopting a multi-relational model and introducing a new relation type (co-interest), thematic communities can be derived. By analyzing Twitter and Reddit, it is found that language plays a significant role in the formation of strong communities.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Food Science & Technology
Ziyang Chen, Cristhiam Gurdian, Chetan Sharma, Witoon Prinyawiwatkul, Damir D. Torrico
Summary: Increased meat consumption has been linked to various environmental and animal welfare issues. To address this, alternative proteins like plant-based and insect-based proteins have gained popularity in research. Text mining and NLP have been explored as efficient tools in identifying trends and sentiments in sensory studies, providing a rapid and comprehensive analysis of consumer perceptions towards alternative proteins.
Review
Computer Science, Theory & Methods
Luciano Ignaczak, Guilherme Goldschmidt, Cristiano Andre Da Costa, Rodrigo Da Rosa Righi
Summary: The article discusses the application of text mining in the cybersecurity domain to improve activity efficiency and proposes a taxonomy to demonstrate the different activities supported by text mining. It also discusses text classification performance, neural network support, and highlights future research directions.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Hardware & Architecture
Yuliang Li, Aaron Feng, Jinfeng Li, Shuwei Chen, Saran Mumick, Alon Halevy, Vivian Li, Wang-Chiew Tan
Summary: This paper introduces OpineDB, a subjective database system that allows users to pose subjective queries using their own words. Through experiments with real data, it is demonstrated that subjective databases can better satisfy user needs compared to other techniques.
Article
Computer Science, Information Systems
Yin-Fu Huang, Yi-Hao Li
Summary: NLP enables machines to understand natural languages. This paper proposes developments in translating sentimental statements using deep learning techniques, with satisfactory results.
Article
Automation & Control Systems
Nitish Pathak, Shams Tabrez Siddiqui, Anjani Kumar Singha, Heba G. Mohamed, Shabana Urooj, Abhinandan R. Patil
Summary: The study proposes a blockchain-based method to safeguard data in IoT devices and sensors, and validates its effectiveness through the use of various devices and platforms.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Mesfer Al Duhayyim, Heba. G. G. Mohamed, Jaber. S. S. Alzahrani, Rana Alabdan, Mohamed Mousa, Abu Sarwar Zamani, Ishfaq Yaseen, Mohamed Ibrahim Alsaid
Summary: Precise rainfall prediction is crucial for planning security measures in smart city environments, and this article introduces a Fuzzy Cognitive Maps with a Metaheuristics-based Rainfall Prediction System (FCMM-RPS) technique that can automatically and efficiently predict rainfall with a maximum accuracy of 94.22%.
Article
Green & Sustainable Science & Technology
Muhammad Imran Nadeem, Kanwal Ahmed, Dun Li, Zhiyun Zheng, Hend Khalid Alkahtani, Samih M. Mostafa, Orken Mamyrbayev, Hala Abdel Hameed
Summary: Due to the exponential increase in internet and social media users, fake news travels rapidly, and no one is immune to its adverse effects. This paper presents an automated method for detecting fake news to counteract the spread of disinformation. The proposed multimodal EFND integrates contextual, social context, and visual data from news articles and social media to build a multimodal feature vector with a high level of information density. EFND has outperformed the baseline and state-of-the-art machine learning and deep learning models, achieving high accuracy on standard fake news datasets.
Review
Computer Science, Information Systems
Naqash Ahmad, Yazeed Ghadi Ghadi, Muhammad Adnan, Mansoor Ali
Summary: Due to increasing demands of electricity, different continents are transforming their smart grids infrastructure into super smart grids (SSGs) by interconnecting power system networks between countries to manage future demands. SSGs use renewable energy to reduce greenhouse gas emissions. The research focuses on technical challenges in developing SSGs for European and SAARC continents and presents a fuzzy logic using a hybrid cluster model for a reliable energy supply. Simulation using MATLAB is performed to validate the suggested SSGs model consisting of eighteen bus networks.
Article
Computer Science, Information Systems
Muhammad Imran Nadeem, Kanwal Ahmed, Dun Li, Zhiyun Zheng, Hafsa Naheed, Abdullah Y. Muaad, Abdulrahman Alqarafi, Hala Abdel Hameed
Summary: This paper proposes a multi-label text classification model for news, using an automated expert system to optimize CNN's classification of multi-label news items. By integrating a high-level metaheuristic optimization algorithm to automate the tuning of hyperparameters, the performance of multi-label news classification is improved.
Article
Computer Science, Information Systems
Zain ul Abideen, Tehseen Mazhar, Abdul Razzaq, Inayatul Haq, Inam Ullah, Hisham Alasmary, Heba G. G. Mohamed
Summary: Annual surveys in Pakistan show that the literacy rate is increasing gradually but not at the desired speed. There is a need for a model to analyze student enrollment in schools, and in this proposed work, machine learning algorithms are used to extract significant features from enrollment data and predict future registrations and target levels. The proposed model also helps address the issue of fewer enrollments and improve the literacy rate.
Article
Computer Science, Artificial Intelligence
Hao Tang, Uzair Aslam Bhatti, Jingbing Li, Shah Marjan, Mehmood Baryalai, Muhammad Assam, Yazeed Yasin Ghadi, Heba G. Mohamed
Summary: In recent years, ozone has become the primary pollutant affecting urban air quality. Accurate and efficient ozone prediction is crucial for pollution prevention and control. This study proposes a method using VMD, EEMD, and LSTM for ozone concentration prediction, achieving better results than baseline models and serving as a reliable model for ozone forecasting.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Minghao Cheng, Hao Tang, Asad Khan, Syam Melethil Sethumadhavan, Muhammad Assam, Di Li, Yazeed Yasin Ghadi, Heba G. Mohamed, Uzair Aslam Bhatti
Summary: The technology of visual servoing, driven by the digital twin, has great potential for enhancing smart manufacturing assembly and dispensing applications. Network-based methodologies are used to approximate the vision-motion correlation and improve the accuracy and reliability of visual servoing systems. However, obtaining sufficient training data is challenging, and improving model generalization is necessary.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Chemistry, Analytical
Sayyed Mudassar Shah, Zhaoyun Sun, Khalid Zaman, Altaf Hussain, Inam Ullah, Yazeed Yasin Ghadi, Muhammad Abbas Khan, Rashid Nasimov
Summary: This research introduces a novel neighbor-based energy-efficient routing protocol (NBEER) tailored for underwater wireless sensor networks (UWSNs). NBEER aims to optimize neighbor selection and cooperative mechanisms to achieve load balancing and enhance network performance. Through comprehensive MATLAB simulations, NBEER outperforms existing protocols in various metrics.
Article
Chemistry, Analytical
Shahid Basir, Ubaid Ur Rahman Qureshi, Fazal Subhan, Muhammad Asghar Khan, Syed Agha Hassnain Mohsan, Yazeed Yasin Ghadi, Khmaies Ouahada, Habib Hamam, Fazal Noor
Summary: This study presents a monopole 4 x 4 UWB-MIMO antenna system with a novel structure and excellent performance. The proposed design features triple-notched characteristics achieved by CSRR etching and a C-shaped curve. The design achieves notching at 4.5 GHz, 5.5 GHz, and 8.8 GHz frequencies in the C-band, WLAN band, and satellite network, respectively. CSRR etching at the feed line and ground plane, along with the use of a C-shaped curve, reduces interference and enables high isolation and polarization diversity. The small prototype dimensions of (60.4 x 60.4) mm(2) make it suitable for wireless communication and portable systems.
Article
Multidisciplinary Sciences
Muhammad Haris, Atiq Ur Rehman, Sheeraz Iqbal, Syed Owais Athar, Hossam Kotb, Kareem M. AboRas, Abdulaziz Alkuhayli, Yazeed Yasin Ghadi, Kitmo
Summary: This paper proposes an optimized heliostat field layout based on annual efficiency and power, and uses a genetic algorithm to optimize different design points. The results show that the number of heliostats and efficiency are improved through optimization in both radial staggered and Fermat's spiral configurations.
Article
Computer Science, Information Systems
Syed Muhammad Ahmed Hassan Shah, Muhammad Qasim Khan, Yazeed Yasin Ghadi, Sana Ullah Jan, Olfa Mzoughi, Monia Hamdi
Summary: Vision Transformers (ViT) are commonly used in image recognition and related applications. This study modifies the patch encoding module of ViT to produce heterogeneous embedding using new types of weighted encoding. Additionally, a Divergent Knowledge Dispersion (DKD) mechanism is proposed to propagate previous latent information in the transformer network. Experimental results show that the proposed model, named SWEKP-based ViT, achieves improved performance on benchmark datasets compared to traditional ViT models.
Article
Computer Science, Information Systems
Muhammad Adnan, Yazeed Ghadi, Ijaz Ahmed, Mansoor Ali
Summary: In order to reduce CO2 emissions and manage load demands, utility companies need to strive for 100% renewable electricity generation. Europe plans to achieve this goal by developing a super smart grid (SSG) based on renewable energy resources (RERs) by 2050. However, there are challenges associated with RERs, such as load flow balancing and transient stability. This research paper proposes probabilistic modeling and cooperative control strategies to address these challenges and enhance load flow balancing and transient stability in SSGs.
Article
Computer Science, Information Systems
Latif Jan, Ghassan Husnain, Waleed Tariq Sethi, Ihtisham Ul Haq, Yazeed Yasin Ghadi, Hend Khalid Alkahtani
Summary: This research examines the reliability of a wireless communication system that uses a hybrid RF and underwater optical wireless communication in a dual-hop system. The proposed system consists of a single source node, a relay node, and a destination node. The statistical analysis of the system is evaluated using MIMO and AF techniques. The paper provides mathematical expressions for each channel model.
Article
Computer Science, Information Systems
Tanzeel Zaidi, Muhammad Usman, Muhammad Umar Aftab, Hanan Aljuaid, Yazeed Yasin Ghadi
Summary: The Internet of Things (IoT) has connected many objects, but its expansion has raised concerns about data security and access control. Traditional access control mechanisms face challenges in managing access rights and have performance overhead. This study proposes a framework that uses blockchain technology and role-based access control to address these challenges, introducing a role management system to resolve conflicts and improve system security and response time.