Publications

Seven Journal Articles

Complex Network Analysis, Spatiotemporal Big Data Analysis, Artificial Intelligence, Clinical Data Analysis, Social Media Behavior, Starch Chemistry

  • [1] Wei Chien Benny Chin, Chun-Hsiang Chan* (2023). Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia. Tropical Medicine and Infectious Disease. Vol.8(2), 72. (SCI IF: 3.711; Q1 6/24 in Tropical Medicine) [View Paper]

    Abstracts: COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases.
    Keywords: Malaysia; COVID-19; human activities; travel restriction; travel willingness; time series

  • [2] Chun-Hsiang Chan, Wen-Chi Huang, Yi-Chien Lu, Hsing-Fen Hsiao, and Wing P. Chan (2021). BatchBMD as an Efficient and Accurate Dual-Energy X-ray Absorptiometry Report Generator. Diagnostics. Vol.11(12), 2403. (SCI IF: 3.992; Q2 60/172 in Medicine, General, and Internal) [View Paper]

    Abstracts: Dual-energy X-ray absorptiometry is the gold standard for evaluating Bone Mineral Density (BMD); however, a typical BMD report is generated in a time-inefficient manner and is prone to error. We developed a rule-based automated reporting system, BatchBMD, that accelerates DXA reporting while improving its accuracy over current systems. BatchBMD generates a structured report, customized to the specific clinical purpose. To compare BatchBMD to a Web-based Reporting (WBR) system for efficiency and accuracy, 500 examinations were randomly chosen from those performed at the Taipei Municipal Wanfang Hospital from January to March 2021. The final assessment included all 2326 examinations conducted from September 2020 to March 2021. The average reporting times were 6.7 and 10.8 minutes for BatchBMD and the WBR system, respectively, while accuracy was 99.4% and 98.2%, respectively. Most of the errors made by BatchBMD were digit errors in the appendicular skeletal muscle index. After correcting this, 100% accuracy across all 2326 examinations was validated. This automated and accurate BMD reporting system significantly reduces report production workload for radiologists and technicians while increasing productivity and quality. Additionally, the portable software, which employs a simple framework, can reduce deployment costs in clinical practice.
    Keywords: dual-energy X-ray absorptiometry; Bone Mineral Density; automated reporting system

  • [3] Chun-Hsiang Chan, Tzai-Hung Wen (2021). Revisiting the Effects of High-Speed Railway Transfers in the Early COVID-19 Cross-Province Transmission in Mainland China. International Journal of Environmental Research and Public Health. Vol.18(12), 6394. https://doi.org/10.3390/ijerph1812 6394 (SSCI IF: 4.614; Q1 45/182 in Public, Environmental & Occupational Health) [View Paper]

    Abstracts: Dual-energy X-ray absorptiometry is the gold standard for evaluating Bone Mineral Density (BMD); however, a typical BMD report is generated in a time-inefficient manner and is prone to error. We developed a rule-based automated reporting system, BatchBMD, that accelerates DXA reporting while improving its accuracy over current systems. BatchBMD generates a structured report, customized to the specific clinical purpose. To compare BatchBMD to a Web-based Reporting (WBR) system for efficiency and accuracy, 500 examinations were randomly chosen from those performed at the Taipei Municipal Wanfang Hospital from January to March 2021. The final assessment included all 2326 examinations conducted from September 2020 to March 2021. The average reporting times were 6.7 and 10.8 minutes for BatchBMD and the WBR system, respectively, while accuracy was 99.4% and 98.2%, respectively. Most of the errors made by BatchBMD were digit errors in the appendicular skeletal muscle index. After correcting this, 100% accuracy across all 2326 examinations was validated. This automated and accurate BMD reporting system significantly reduces report production workload for radiologists and technicians while increasing productivity and quality. Additionally, the portable software, which employs a simple framework, can reduce deployment costs in clinical practice.Coronavirus disease 2019 (COVID-19) is an ongoing pandemic that was reported at the end of 2019 in Wuhan, China, and was rapidly disseminated to all provinces in around one month. The study aims to assess the changes in intercity railway passenger transport on the early spatial transmission of COVID-19 in mainland China. Examining the role of railway transport properties in disease transmission could help quantify the spatial spillover effects of large-scale travel restriction interventions. This study used daily high-speed railway schedule data to compare the differences in city-level network properties (destination arrival and transfer service) before and after the Wuhan city lockdown in the early stages of the spatial transmission of COVID-19 in mainland China. Bayesian multivariate regression was used to examine the association between structural changes in the railway origin-destination network and the incidence of COVID-19 cases. Our results show that the provinces with rising transfer activities after the Wuhan city lockdown had more confirmed COVID-19 cases, but changes in destination arrival did not have significant effects. The regions with increasing transfer activities were located in provinces neighboring Hubei in the widthwise and longitudinal directions. These results indicate that transfer activities enhance interpersonal transmission probability and could be a crucial risk factor for increasing epidemic severity after the Wuhan city lockdown. The destinations of railway passengers might not be affected by the Wuhan city lockdown, but their itinerary routes could be changed due to the replacement of an important transfer hub (Wuhan city) in the Chinese railway transportation network. As a result, transfer services in the high-speed rail network could explain why the provinces surrounded by Hubei had a higher number of confirmed COVID-19 cases than other provinces.
    Keywords: transfer service; COVID-19; Wuhan city lockdown; high-speed rail network; intercity population flow; spatial transmission

  • [4] Chun-Hsiang Chan, Ri-Gui Wu, Yi-Yuan Shao (2021). The Effects of Ultrasonic Treatment on Physicochemical Properties and in vitro Digestibility of Semigelatinized High Amylose Maize Starch. Food Hydrocolloids. Vol.119, 106831. https://doi.org/10.1016/j.foodhyd.2021.106831 (SCI IF: 11.504; Q1 3/73 in Applied Chemistry; Q1 5/144 in Food Science & Technology) [View Paper]

    Abstracts: This study aimed to observe and quantify the high- and low-temperature ultrasonication impact of semigelatinized high amylose maize starch on physicochemical properties and in vitro digestibility. High- and low-temperature ultrasonication did not increase the degree of gelatinization, but generated cracks and pores on the starch granule surface and enhanced the short-range ordered molecular structure and apparent amylose content (AAC). Compared with incubation treatments, high-temperature ultrasonication gradually increased the slowly digestible starch (SDS) and resistant starch (RS), whereas low-temperature ultrasonication only decreased RS. Principal component analysis (PCA) and multivariate linear regression results showed that SDS and RS were significantly affected by the long-range ordered molecular structure, a molecular weight distribution of amylopectin, enthalpy change and AAC, whereas the short-range ordered molecular structure further dominated RS. Our results improved the understanding of physicochemical property changes in low- and high-temperature ultrasonication on semigelatinized high amylose maize starch and differentiated the significant principal components of SDS and RS formation.
    Keywords: ultrasonication; in vitro digestibility; semigelatinization; high amylose maize starch

  • [5] Wei-Hsian Chi, Fei-Ying Kuo, Chang-Hui Chi, Shi-Chiang Lin, Chun-Hsiang Chan (2021). Spatial-temporal Analysis of Pilgrimage Network of Mazu-temples in Yunlin and Chiayi County: A Study on Geographical Distribution of Pilgrimage Group. Journal of Geographical Science. Vol.98, 45-82. https://doi.org/10.6161/jgs.202104_(98).0003 (TSSCI) [View Paper]

    Abstracts: Both pilgrimage to mother temple and the other form of pilgrimage, which focuses on visiting historic or famous temples, have grown significantly since 2000. Due to the specific historical background of some Mazu temples in Yunlin and Chiayi, where many people from the agricultural area migrated to the metropolitan area during the period of industrialization in 1980s, the two counties have become the major destination areas for the Mazu-pilgrimage, with even more pilgrimage visitors than older areas like Tainan and Kaohsiung. Yet, no quantitative investigations have been conducted on the Mazu-pilgrimage in Taiwan. This study performs such a quantitative research, establish networks of pilgrim groups visiting more than one target temple from data collected from all Mazu-temples in Yunlin and Chiayi for three consecutive years. Using network analysis methods, including community detection and hierarchical clustering analysis, this study explores the characteristics of network structures with reference to different temporal and spatial conditions. The concept of a “co-constructed pilgrimage circle” is proposed as the basic structure for explaining the changes in network structure under different time and space conditions. This novel concept is expected to join the theories of worshipping circles and belief circles in related studies in enriching academic imagination of the modern development of Taiwanese popular religion.
    Keywords: pilgrimage; co-constructed pilgrimage group; network analysis; community detection; Mazu

  • [6] Chun-Hsiang Chan, Tzu-How Chu, Jiun-Huei Proty Wu, Tzai-Hung Wen (2021). Spatially Characterizing Major Airline Alliances: A Network Analysis. ISPRS International Journal of Geo-Information (IJGI). Vol.10(1), 38. https://doi.org/10.3390/ijgi10010038 (SCI IF: 3.088; Q2 24/50 in Geography; Q3 88/164 in Computer Science, Information Systems) [View Paper]

    Abstracts: An airline alliance is a group of member airlines that seek to achieve the same goals through routes and airports. Hence, airports’ connectivity plays an essential role in understanding the linkage between different markets, especially the impact of neighboring airports on focal airports. An airline alliance airport network (AAAN) comprises airports as nodes and routes as edges. It could reflect a clear collaborative proportion within AAAN and competitive routes between AAANs. Recent studies adopted an airport- or route-centric perspective to evaluate the relationship between airline alliances and their member airlines; meanwhile, they mentioned that an airport community could provide valuable air transportation information because it considers the entire network structure, including the impacts of the direct and indirect routes. The objectives are to identify spatial patterns of market region in an airline alliance and characterize the differences among airline alliances (Oneworld, Star Alliance, and SkyTeam), including regions of collaboration, competition, and dominance. Our results show that Star Alliance has the highest collaboration and international market dominance among three airline alliances. The most competitive regions are Asia-Pacific, West Asia, Europe, and North and Central America. The network approach we proposed identifies market characteristics, highlights the region of market advantages in the airline alliance, and also provides more insights for airline and airline alliances to extend their market share or service areas.
    Keywords: airline alliance airport network; airport community; market characteristics

  • [7] Yuan-Fang Tsai, Chun-Hsiang Chan, Keng-Han Lin, Wen-Ray Su, Jinn-Chyi Chen (2017). New Debris Flow Critical Rainfall Line Setting via Cluster Analysis and Support Vector Machine After the Chi-Chi Huge Earthquake. 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (EI). 970-975. [View Paper]

    Abstracts: The Chi-Chi huge earthquake occurred in Taiwan in 1999 and it caused tremendous landslides that triggered many debris flows, which resulted in considerable loss of life and damage to property. To help prevent damage by debris flows, it is necessary to establish a new critical rainfall line for each debris flow stream. Following the Chi-Chi huge earthquake, the critical rainfall line of several debris flow streams in Taiwan was ostensibly reduced. To comprehend these changes, this study used a four-year (1999–2003) dataset of 79 debris flow events, and it adopted the family competition genetic algorithm as a clustering method to merge rainfall data of streams based on similar characteristics. In addition, 8 predisposing factors for debris flows were used to cluster 377 streams with similar predisposing factors into 7 groups via the genetic algorithm. Then, the support vector machine (SVM) was applied to establish the critical rainfall lines for debris flows. Experimental results confirmed that the SVM method performed well in setting a new critical rainfall line for each group of debris flow streams.
    Keywords: cluster analysis; support vector machine; debris flow; critical rainfall line; earthquake