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RISS 인기검색어
- 검색키워드
- 저자 : Khan Niamat Ali (검색결과 3 건)
- 무료
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Type-2 fuzzy ontology–aided recommendation systems for IoT–based healthcare
Ali, Farman,Islam, S.M. Riazul,Kwak, Daehan,Khan, Pervez,Ullah, Niamat,Yoo, Sang-jo,Kwak, K.S. Elsevier 2018 Journal of Computer Communications Vol.119 No.-
<P><B>Abstract</B></P> <P>The number of people with a chronic disease is rapidly increasing, giving the healthcare industry more challenging problems. To date, there exist several ontology and IoT-based healthcare systems to intelligently supervise the chronic patients for long-term care. The central purposes of these systems are to reduce the volume of manual work in recommendation systems. However, due to the increase of risk and uncertain factors of the diabetes patients, these healthcare systems cannot be utilized to extract precise physiological information about patient. Further, the existing ontology-based approaches cannot extract optimal membership value of risk factors; thus, it provides poor results. In this regards, this paper presents a type-2 fuzzy ontology–aided recommendation systems for IoT-based healthcare to efficiently monitor the patient's body while recommending diets with specific foods and drugs. The proposed system extracts the values of patient risk factors, determines the patient's health condition via wearable sensors, and then recommends diabetes-specific prescriptions for a smart medicine box and food for a smart refrigerator. The combination of type-2 Fuzzy Logic (T2FL) and the fuzzy ontology significantly increases the prediction accuracy of a patient's condition and the precision rate for drug and food recommendations. Information about the patient's disease history, foods consumed, and drugs prescribed is designed in the ontology to deliver decision-making knowledge using Protégé Web Ontology Language (OWL)-2 tools. Semantic Web Rule Language (SWRL) rules and fuzzy logic are employed to automate the recommendation process. Moreover, Description Logic (DL) and Simple Protocol and RDF Query Language (SPARQL) queries are used to evaluate the ontology. The experimental results show that the proposed system is efficient for patient risk factors extraction and diabetes prescriptions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The available healthcare systems are imperfect to extract precise physiological information of patients. </LI> <LI> The classical ontologies are unable to recommend diets without knowing the current condition of a patient. </LI> <LI> Wearable sensors with type-2 fuzzy logic efficiently monitor the patient's body. </LI> <LI> Fuzzy ontology-based knowledge precisely suggests diabetes-specific prescriptions. </LI> <LI> Type-2 fuzzy ontology significantly increases the prediction accuracy of a patient's condition. </LI> </UL> </P>
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Designer nanoparticle: nanobiotechnology tool for cell biology
Thimiri Govinda Raj Deepak B.,Khan Niamat Ali 나노기술연구협의회 2016 Nano Convergence Vol.3 No.22
This article discusses the use of nanotechnology for subcellular compartment isolation and its application towards subcellular omics. This technology review significantly contributes to our understanding on use of nanotechnology for subcellular systems biology. Here we elaborate nanobiotechnology approach of using superparamagnetic nanoparticles (SPMNPs) optimized with different surface coatings for subcellular organelle isolation. Using pulse-chase approach, we review that SPMNPs interacted differently with the cell depending on its surface functionalization. The article focuses on the use of functionalized-SPMNPs as a nanobiotechnology tool to isolate high quality (both purity and yield) plasma membranes and endosomes or lysosomes. Such nanobiotechnology tool can be applied in generating subcellular compartment inventories. As a future perspective, this strategy could be applied in areas such as immunology, cancer and stem cell research.
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Thimiri Govinda Raj Deepak B.,Khan Niamat Ali 나노기술연구협의회 2018 Nano Convergence Vol.5 No.4
In this article, we elaborate the application of thermal decomposition based synthesis of Fe3O4 superparamagnetic nanoparticle (SPMNP) in subcellular fractionation context. Here, we performed surface functionalization of SPMNP with phospholipids and dimercaptosuccinic acid. Surprisingly, we observed surface functionalization dependent SPMNP localization in subcellular compartments such as plasma membrane, endosomes and lysosomes. By using SPMNP based subcellular localization with pulse–chase methodology, we could use SPMNP for high pure-high yield organelle (plasma membrane, endosomes and lysosome) fractionation. Further, SPMNP that are distinctly localized in subcellular compartments can be used as technology for subcellular fractionation that can complement existing tools for cell biology research. As a future perspective, isolated magnetic organelles can be extended to protein/protein complex purification for biochemical and structural biology studies.
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