2018 MANY 110的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列各種有用的問答集和懶人包

Advanced Micro-Level Experimental Techniques for Food Drying and Processing Applications

為了解決2018 MANY 110的問題，作者Karim, Azharul,Fawzia, Sabrina,Rahman, Mohammad Mahbubur 這樣論述：

Dr Azharul Karim is currently working as an Associate Professor in the school of Mechanical, Medical and Process Engineering, Queensland University of Technology, Australia. He received his PhD degree from Melbourne University in 2007. Dr Karim has authored over 200+ peer-reviewed articles, includin

g 110 high quality journal papers, 13 peer-reviewed book chapters, and four books. His papers have attracted about 5000+ citations with h-index 38. His research has very high impact worldwide as demonstrated by his overall field weighted citation index (FWCI) of 2.10. He is editor/board member of si

x reputed journals including Drying Technology and Nature Scientific Reports and supervisor of 26 past and current PhD students. He has been keynote/distinguished speaker at scores of international conferences and invited/keynote speaker in seminars in many reputed universities worldwide. He has won

multiple international awards for his outstanding contributions in multidisciplinary fields. His research is directed towards solving acute food industry problems by advanced multiscale and multiphase food drying models of cellular water using theoretical/computational and experimental methodologie

s. He is the recipient numerous national and international competitive grants amounting ＄3.15 million.Dr Sabrina Fawzia is currently working as a senior lecturer in civil engineering at Queensland University of Technology, Australia. She is a structural engineering expert and research focuses on dev

elopment of the high performance structural members and structural strengthening/ retrofitting by using Fiber reinforced polymer (FRP) material technology. Through her scholarly, innovative, high quality research she has established her national and international standing. Dr Fawzia’s excellence in

research has been demonstrated by high quality refereed publications (98 publications: 1795 citations, h-index=21 Google Scholar), two ARC LIEF grants (＄1.9M), one international grant (＄80K), five QUT internal grants (＄79K), QUT’s SEF Award for Excellence in postgraduate research supervision, ten Ph

D’s and three Master’s by research completions, being invited by reputed universities for seminars and the establishment of national and international collaborative research relationships. Her recent research interest includes microstructural analysis of for structures.Dr. Mohammad Mahbubur Rahman r

eceived his Ph.D. degree from Queensland University of Technology (QUT), Australia, in 2018. Currently, he is working as a visiting research fellow at the Queensland University of Technology (QUT). He received his BSc Degree in Electrical and Electronic Engineering (EEE) from the Chittagong Universi

ty of Engineering and Technology (CUET), Bangladesh, in 2010 and Master of Engineering Science from the University of Malaya (UM), Malaysia in 2014. His research interest includes mathematical modelling, drying process optimization, and renewable energy.

2018 MANY 110進入發燒排行的影片

照顧者對於育兒APP使用經驗及滿意度之研究

為了解決2018 MANY 110的問題，作者張可橙 這樣論述：

自2020年COVID-19疫情延燒至今，對家庭帶來很大的生活改變，其中除了育兒日常之外，在防疫期間家庭互動型態也正悄悄地改變。因此，為了解家長育兒實際需求以及使用相關資源是重要的趨勢。家有嬰幼兒的父母需要紀錄各種嬰幼兒的生活紀錄，以確保嬰幼兒的健康狀況及健康檢查，如何善用各項育兒資源，將嬰兒照護資訊化，家長可以即時了解子女目前的狀況。隨著資訊科技進步，智慧型手機的流行，數位工具也愈來愈行動化及便利性，因此針對嬰幼兒各項活動的APP也蓬勃發展。目前市場上育兒APP種類眾多，但深入探討實際使用與功能是否滿足照顧者需求的研究較少。為了解照顧者對於使用育兒APP相關經驗及滿意度為何？研究首先依據文

獻探討嬰幼兒相關文獻，了解行動裝置在嬰幼兒保育相關之領域應用，再將市面上手持行動裝置平台皆有上架的育兒APP，將各個的功能做比較與統整，以問卷調查方式了解照顧者對於育兒APP實際使用情形以及滿意度。本研究採用科技接受模式為研究架構，加入受試者背景變項探討各構面關係，利用SPSS統計分析方法來驗證各項研究假設。研究結果如下：探討照顧者對於育兒APP的使用經驗之現況與差異。「認知有用性」及「認知易用性」會影響「使用意願」；「使用意願」會影響「滿意度」。根據研究結論，提出相對應研究建議，供未來建置應用程式系統可以擴充功能參考，讓使用者滿意度更加提升。

Computational Intelligence in Pattern Recognition: Proceedings of Cipr 2021

為了解決2018 MANY 110的問題，作者 這樣論述：

Prof. Asit Kumar Das is working as a Professor in the Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India. He has published more than 100 research papers in various international Journals and Conferences, 1 book a

nd 4 book chapters. He has worked as a Member of the Editorial / Reviewer Board of various international journals and Conferences. He has shared his research field of interest in many workshops and conferences through his invited speech in various Institutes in India. He acts as the general chair, p

rogram chair, and advisory member of committees of many international conferences. His research interest includes Data Mining and Pattern Recognition in various fields including Bioinformatics, Social networks, Text mining, Audio and Video data analysis, and Medical Data analysis. He has already gui

ded five Ph.D. scholars and is currently guiding six Ph.D. scholars. Dr. Janmenjoy Nayak is working as an Associate Professor, Aditya Institute of Technology and Management (AITAM), (An Autonomous Institution) Tekkali, K Kotturu, AP- 532201, India. He has published more than 110 research papers in v

arious reputed peer reviewed Referred Journals, International Conferences and Book Chapters. Being two times Gold Medallist in Computer Science in his career, he has been awarded with INSPIRE Research Fellowship from Department of Science & Technology, Govt. of India (both as JRF and SRF level) and

Best researcher award from Jawaharlal Nehru University of Technology, Kakinada, Andhra Pradesh for the AY: 2018-19 and many more awards to his credit. He has Edited 12 Books and 8 Special Issues in various topics including Data Science, Machine Learning, and Soft Computing with reputed International

Publishers like Springer, Elsevier, Inderscience etc. His area of interest includes data mining, nature inspired algorithms and soft computing. Dr. Bighnaraj Naik is an Assistant Professor in the Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Odisha, India. H

e has edited 11 books in various reputed publishers like Springer, Elsevier etc. He has published more than 110 research papers in various reputed peer reviewed International Conferences, Referred Journals and Book Chapters. He is the life member of some of the reputed societies like IEEE, IAENG (Ho

ngkong) etc. He has more than ten years of teaching experience in the field of Computer Science and Information Technology. His area of interest includes Data Mining, Soft Computing, etc.Dr. Soumi Dutta is an Associate at the Institute of Engineering & Management, India. She has completed her Ph.D.

from the Department of CST, IIEST, Shibpur. She received her B.Tech. in IT and her M.Tech. in CSE securing 1st position(Gold medalist), both from Techno India Group. Her research interests Data Mining, Information Retrieval, Online Social Media Analysis, Micro-Blog Summarization, Spam Filtering Sent

iment Analysis, and Clustering of Micro-Blogging Data. She was the editor in CIPR2019, IEMIS2018, IEMIS 2020 and CIPR 2020 Springer Conferences, special issue 2 volumes in IJWLTT. She is TPC member in various international conferences such as - SEAHF, DSMLA, ARIAM, CIPR. She is peer reviewer in diff

erent international journal such as - Journal of King Saud University - Computer and Information Sciences, Springer, Elsevier etc. She is the member of several technical functional bodies such as IEEE, MACUL, SDIWC, ISOC, ICSES, IEEE WIE. She has published several papers in reputed journals and conf

erences. She has recently published 3 patents.Dr. Danilo Pelusi received his Ph.D. degree in Computational Astrophysics from the University of Teramo, Teramo, Italy, in 2006. He is an Assistant Professor of the Faculty of Communication Sciences at the University of Teramo. His current research inter

ests include Information Theory, Fuzzy Logic, Neural Networks and Evolutionary Algorithms. Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence and IEEE Access, he served as keynote speaker at several conferences and guest editor for Inderscience and Springer journa

ls.

An Integrated Approach For Uncovering Novel DNA Methylation Biomarkers For Non-small Cell Lung Carcinoma

為了解決2018 MANY 110的問題，作者VAIBHAV KUMAR SUNKARIA 這樣論述：

Introduction - Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a proportion of 85%. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD) and Lung Small Cell Carcinoma (LUS

C). Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, a major portion of 75% subjects have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce wide

spread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands, many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type.Structure - This research work took advantage of publicly avai

lable methylation profiling resources and relevant comorbidities for lung cancer patients extracted from meta-analysis of scientific review and journal available at PubMed and CNKI search which were combined systematically to explore effective DNA methylation markers for NSCLC. We also tried to iden

tify common CpG loci between Caucasian, Black and Asian racial groups for identifying ubiquitous candidate genes thoroughly. Statistical analysis and GO ontology were also conducted to explore associated novel biomarkers. These novel findings could facilitate design of accurate diagnostic panel for

practical clinical relevance.Methodology - DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. Standard pipeline was conducted to discover significant differentially methylated sites as prim

ary biomarkers. Secondary biomarkers were extracted by incorporating genes associated with comorbidities from meta-analysis of research articles. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix fo

r all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using the gene distance matrix. There were 35 CpG loci identified by comparing TCGA training cohort with GEO testing cohort from these functional groups, and 4 gene-based pa

nel was devised after finding highly discriminatory diagnostic panel through combinatorial validation of each functional cluster.Results – To evaluate the gene panel for NSCLC, the methylation levels of SCT(Secritin), FOXD3(Forkhead Box D3), TRIM58(Tripartite Motif Containing 58) and TAC1(Tachikinin

1) were tested. Individually each gene showed significant methylation difference between LUAD and LUSC training cohort. Combined 4-gene panel AUC, sensitivity/specificity were evaluated with 0.9596, 90.43%/100% in LUAD; 0.949, 86.95%/98.21% in LUSC TCGA training cohort; 0.94, 85.92%/97.37 in GEO 66

836; 0.91,89.17%/100% in GEO 83842 smokers; 0.948, 91.67%/100% in GEO83842 non-smokers independent testing cohort. Our study validates SCT, FOXD3, TRIM58 and TAC1 based gene panel has great potential in early recognition of NSCLC undetermined lung nodules. The findings can yield universally accurate

and robust markers facilitating early diagnosis and rapid severity examination.