Dezheng Zhang^1,2, Qi Jia^1,2, Shibing Yang^1,2, Xinliang Han², Cong Xu³, Xin Liu^1,4, Yonghong Xie^1,2,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 159-170, 2022, DOI:10.32604/cmc.2022.017295 - 03 November 2021

Abstract Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine (TCM). We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in TCM. We analyze the reasoning path patterns from symptom to syndromes on the knowledge graph. There are two kinds of path patterns in the knowledge graph: one-hop and two-hop. The one-hop path pattern maps the symptom to syndromes immediately. The two-hop path pattern maps the symptom to syndromes through the nature of disease, etiology, and pathomechanism to support the diagnostic reasoning. Considering the… More >

Sabin C. Buraga^1,*, Daniel Amariei¹, Octavian Dospinescu²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5537-5550, 2022, DOI:10.32604/cmc.2022.021714 - 11 October 2021

Abstract In the context of a proliferation of Database Management Systems (DBMSs), we have envisioned and produced an OWL 2 ontology able to provide a high-level machine-processable description of the DBMSs domain. This conceptualization aims to facilitate a proper execution of various software engineering processes and database-focused administration tasks. Also, it can be used to improve the decision-making process for determining/selecting the appropriate DBMS, subject to specific requirements. The proposed model describes the most important features and aspects regarding the DBMS domain, including the support for various paradigms (relational, graph-based, key-value, tree-like, etc.), query languages, platforms… More >

Anitha Velu^*, Menakadevi Thangavelu

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4707-4724, 2022, DOI:10.32604/cmc.2022.020095 - 11 October 2021

Abstract The drastic growth of coastal observation sensors results in copious data that provide weather information. The intricacies in sensor-generated big data are heterogeneity and interpretation, driving high-end Information Retrieval (IR) systems. The Semantic Web (SW) can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval. This paper focuses on exploiting the SW base system to provide interoperability through ontologies by combining the data concepts with ontology classes. This paper presents a 4-phase weather data model: data processing, ontology creation, SW processing, and query engine. The developed Oceanographic Weather More >

MAURA BENEDETTI, MARIA ELISA GIULIANI, MARICA MEZZELANI, ALESSANDRO NARDI, LUCIA PITTURA, STEFANIA GORBI, FRANCESCO REGOLI

BIOCELL, Vol.46, No.1, pp. 37-49, 2022, DOI:10.32604/biocell.2022.017507 - 28 September 2021

Abstract Oxidative stress is a critical condition derived from the imbalance between the generation of reactive oxygen species and the sophisticated network of antioxidant mechanisms. Several pollutants and environmental factors can affect this system through connected mechanisms, indirect relationships, and cascade effects from pre-transcriptional to catalytic level, by either enhancing intracellular ROS formation or impairing antioxidant defenses. This review summarizes the current knowledge on the pro-oxidant challenges from emerging environmental stressors threatening marine organisms, such as pharmaceuticals, microplastics and climate-related ocean changes. Emphasis will be placed on oxidative pathways, including signaling proteins and transcription factors involved More >

Jibran Mir¹, Azhar Mahmood^2,*, Shaheen Khatoon³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3491-3509, 2022, DOI:10.32604/cmc.2022.019952 - 27 September 2021

Abstract Aspect's extraction is a critical task in aspect-based sentiment analysis, including explicit and implicit aspects identification. While extensive research has identified explicit aspects, little effort has been put forward on implicit aspects extraction due to the complexity of the problem. Moreover, existing research on implicit aspect identification is widely carried out on product reviews targeting specific aspects while neglecting sentences’ dependency problems. Therefore, in this paper, a multi-level knowledge engineering approach for identifying implicit movie aspects is proposed. The proposed method first identifies explicit aspects using a variant of BiLSTM and CRF (Bidirectional Long Short… More >

B. T. Shobana^1,*, G. A. Sathish Kumar²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1007-1021, 2022, DOI:10.32604/csse.2022.019523 - 24 September 2021

Abstract Electronic learning (e-learning) has become one of the widely used modes of pedagogy in higher education today due to the convenience and flexibility offered in comparison to traditional learning activities. Advancements in Information and Communication Technology have eased learner connectivity online and enabled access to an extensive range of learning materials on the World Wide Web. Post covid-19 pandemic, online learning has become the most essential and inevitable medium of learning in primary, secondary and higher education. In recent times, Massive Open Online Courses (MOOCs) have transformed the current education strategy by offering a technology-rich… More >

Muhammad Younas^1,2,*, Ahmad Shukri Mohd Noor², Muhammad Arshad¹

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 83-99, 2022, DOI:10.32604/iasc.2022.018332 - 03 September 2021

Abstract The education sector is now necessitated to align itself with the latest innovative technological trends in the industry to be competitive while transforming database management practices. The Higher Education Institutions (HEIs) are currently using cloud-based applications at varied implementation levels while others are following the shifting trends. On-demand availability of consolidated information is a critical success factor to perform decision-making activities; as a result, quite a bit of research work has been performed in this realm. The study is aimed to propose an efficient framework that is capable of extracting the desired information from an More >

Sheng Huang, Chuanle Liu^*

Journal on Artificial Intelligence, Vol.3, No.4, pp. 153-162, 2021, DOI:10.32604/jai.2021.025175 - 07 February 2022

Abstract Knowledge graph technology play a more and more important role in various fields of industry and academia. This paper firstly introduces the general framework of the knowledge graph construction, which includes three stages: information extraction, knowledge fusion and knowledge processing. In order to improve the efficiency of quality and safety supervision of transportation engineering construction, this paper constructs a knowledge graph by acquiring multi-sources heterogeneous data from supervision of transportation engineering quality and safety. It employs a bottom-up construction strategy and some natural language processing methods to solve the problems of the knowledge extraction for… More >

Chuanrong Wu^1,*, Haotian Cui¹, Zhi Lu², Xiaoming Yang³, Mark E. McMurtrey⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3275-3287, 2021, DOI:10.32604/cmc.2021.019969 - 24 August 2021

Abstract Big data knowledge, such as customer demands and consumer preferences, is among the crucial external knowledge that firms need for new product development in the big data environment. Prior research has focused on the profit of big data knowledge providers rather than the profit and pricing schemes of knowledge recipients. This research addresses this theoretical gap and uses theoretical and numerical analysis to compare the profitability of two pricing schemes commonly used by knowledge recipients: subscription pricing and pay-per-use pricing. We find that: (1) the subscription price of big data knowledge has no effect on… More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069 - 24 August 2021

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need… More >