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  • 1
    Online Resource
    Online Resource
    Aberrant Driving Behavior Prediction for Urban Bus Drivers in Taiwan Using Heart Rate Variability and Various Machine Learning Approaches: A Pilot Study
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2677, No. 3 ( 2023-03), p. 1304-1320
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2677, No. 3 ( 2023-03), p. 1304-1320
    Abstract: Objective: Aberrant driving behavior (ADB) decreases road safety and is particularly relevant for urban bus drivers, who are required to drive daily shifts of considerable duration. Although numerous frameworks based on human physiological features have been applied to predict ADB, the research remains at an early stage. This study used heart rate variability (HRV) parameters to establish ADB occurrence prediction models with various machine learning approaches. Methods: Twelve Taiwanese urban bus drivers were recruited for four consecutive days of naturalistic driving data collection (from their routine routes) between March and April 2020; driving behaviors and physiological signals were obtained from provided devices. Weather and traffic congestion information was determined from public data, while sleep quality and professional driving experience were self-reported. To develop the ADB prediction model, several machine learning models—logistic regression, random forest, naive Bayes, support vector machine, and gated recurrent unit (GRU)—were trained and 10-fold cross-validated by using the testing data. Results: Most drivers with ADB reported deficient sleep quality (≤80%), with significantly higher mean scores on the Karolinska Sleepiness Scale and driver behavior questionnaire subcategory of lapses and errors than drivers without ADB. Next, HRV indices significantly differed between the measurement of a pre-ADB event and a baseline. The accuracy of the GRU models ranged from 78.84% ± 1.49% to 89.57% ± 1.31%. Conclusion: Drivers with ADB tend to have inadequate sleep quality, which may increase their fatigue levels and impair driving performance. The established time-series models can be considered for ADB occurrence prediction among urban bus drivers.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221123802
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2403378-9
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  • 2
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    Predicting Fatigue-Associated Aberrant Driving Behaviors Using a Dynamic Weighted Moving Average Model With a Long Short-Term Memory Network Based on Heart Rate Variability
    SAGE Publications ; 2023
    In:  Human Factors: The Journal of the Human Factors and Ergonomics Society
    Details
    In: Human Factors: The Journal of the Human Factors and Ergonomics Society, SAGE Publications
    Abstract: This study proposed a moving average (MA) approach to dynamically process heart rate variability (HRV) and developed aberrant driving behavior (ADB) prediction models by using long short-term memory (LSTM) networks. Background Fatigue-associated ADBs have traffic safety implications. Numerous models to predict such acts based on physiological responses have been developed but are still in embryonic stages. Method This study recorded the data of 20 commercial bus drivers during their routine tasks on four consecutive days and subsequently asked them to complete questionnaires, including subjective sleep quality, driver behavior questionnaire and the Karolinska Sleepiness Scale. Driving behaviors and corresponding HRV were determined using a navigational mobile application and a wristwatch. The dynamic-weighted MA (DWMA) and exponential-weighted MA were used to process HRV in 5-min intervals. The data were independently separated for training and testing. Models were trained with 10-fold cross-validation strategy, their accuracies were evaluated, and Shapley additive explanation (SHAP) values were used to determine feature importance. Results Significant increases in the standard deviation of NN intervals (SDNN), root mean square of successive heartbeat interval differences (RMSSD), and normalized spectrum of high frequency (nHF) were observed in the pre-event stage. The DWMA-based model exhibited the highest accuracy for both driver types (urban: 84.41%; highway: 80.56%). The SDNN, RMSSD, and nHF demonstrated relatively high SHAP values. Conclusion HRV metrics can serve as indicators of mental fatigue. DWMA-based LSTM could predict the occurrence of the level of fatigue associated with ADBs. Application The established models can be used in realistic driving scenarios.
    Type of Medium: Online Resource
    ISSN: 0018-7208 , 1547-8181
    URL: Article
    DOI: 10.1177/00187208231183874
    RVK:
    CL 1000
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2066426-6
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  • 3
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    Proposing spacetime scale for space tourism economics
    SAGE Publications ; 2023
    In:  Tourism Economics Vol. 29, No. 6 ( 2023-09), p. 1671-1678
    Details
    In: Tourism Economics, SAGE Publications, Vol. 29, No. 6 ( 2023-09), p. 1671-1678
    Abstract: This research proposes the spacetime scale to derive a space tourism economic model based on the General Relativity Theory. The space curvature is considered in the economic model analogized to a physic theory to expand the horizons of tourism economics. The deductive reasoning and analogy methods were adopted to propose the spacetime scale for space tourism economics, accommodating the conventional economic models of near-flat space commodities on the earth. Conclusions suggest conquering our perception acceptance from linear time to curvilinear spacetime for space tourism economics.
    Type of Medium: Online Resource
    ISSN: 1354-8166 , 2044-0375
    URL: Article
    DOI: 10.1177/13548166221109666
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2026139-1
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  • 4
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    Image correction for cone-beam computed tomography simulator using neural network corrector
    SAGE Publications ; 2017
    In:  Advances in Mechanical Engineering Vol. 9, No. 2 ( 2017-02), p. 168781401769047-
    Details
    In: Advances in Mechanical Engineering, SAGE Publications, Vol. 9, No. 2 ( 2017-02), p. 168781401769047-
    Abstract: In this article, a neural network corrector is proposed to correct the image shift, yielding the degradation of three-dimensional image reconstruction, for each slice captured by cone-beam computed tomography simulator. There are 3 degrees of freedom in tube module of simulator; the central point of tube module should be aligned with the central point of detector module to guarantee the accurate image projection. However, the mechanism manufacturing and assembling tolerance will let the above aim cannot be met. Here, a standard kit is made to measure the image shift by 1° step from −10° to 10°. The measure data will be the input training data of proposed neural network corrector, and the corrected translation position will be the output of neural network corrector. The Levenberg–Marquardt learning algorithm adjusts the connected weights and biases of the neural network using a supervised gradient descent method, such that the defined error function can be minimized. To avoid the problem of overfitting and improve the generalized ability of the neural network, Bayesian regularization is added to the Levenberg–Marquardt learning algorithm. After the training of neural network corrector, the different target position commands are fed into the neural network corrector. Then, the corrected data from neural network corrector are fed to be the new position command to verify the image correction performance. Moreover, a phantom kit is made to check the corrected performance of the neural network corrector. Finally, the experimental results verify that the image shift can be reduced by the neural network corrector.
    Type of Medium: Online Resource
    ISSN: 1687-8140 , 1687-8140
    URL: Article
    DOI: 10.1177/1687814017690476
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2501620-9
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  • 5
    Online Resource
    Online Resource
    Validation of the Chinese Version of Family-Professional Partnership Scale in Early Intervention
    SAGE Publications ; 2020
    In:  Journal of Early Intervention Vol. 42, No. 4 ( 2020-12), p. 381-395
    Details
    In: Journal of Early Intervention, SAGE Publications, Vol. 42, No. 4 ( 2020-12), p. 381-395
    Abstract: The Chinese version of the Family-Professional Partnership Scale (FPPS-C) measures satisfaction with mutually established parent-professional partnerships. This study aimed to evaluate the measurement properties of the FPPS-C Family and Professional Versions. The participants comprised 167 parents who had a child enrolled in an early intervention program, and 200 early intervention professionals in Taiwan. Structural validity, internal consistency, test–retest reliability, and construct validity were examined. The Family Version denoted a single-dimensional scale with high internal consistency (α = .99) and adequate test–retest reliability (intraclass correlation coefficient [ICC] = 0.54). The Professional Version showed a three-factor structure with moderate to adequate internal consistency (α = .64–.90) and test–retest reliabilities (ICC = 0.60–0.77). Construct validity was evidenced through positive associations between parental and professional perceptions on partnerships and to family-centered service provision. The FPPS-C is a reliable and valid measure, and the study findings can influence research initiatives and practices that aim to ameliorate the provision of family-centered services by early intervention programs.
    Type of Medium: Online Resource
    ISSN: 1053-8151 , 2154-3992
    URL: Article
    DOI: 10.1177/1053815120945025
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2416414-8
    SSG: 5,2
    SSG: 5,3
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  • 6
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    Promotion of Smoking Cessation Using the Transtheoretical Model: Short-Term and Long-Term Effectiveness for Workers in Coastal Central Taiwan
    SAGE Publications ; 2022
    In:  Tobacco Use Insights Vol. 15 ( 2022-01), p. 1179173X2211044-
    Details
    In: Tobacco Use Insights, SAGE Publications, Vol. 15 ( 2022-01), p. 1179173X2211044-
    Abstract: Smoking cessation reduces the risk of severe illnesses in the long run and contributes to improving health. This study evaluated the short-term and long-term effectiveness of workplace smoking cessation intervention implemented using the transtheoretical model. Methods Participants were assessed at baseline before the intervention and after 6 months and 4 years of follow-ups. Data on changes in participants’ perception of smoking prohibition in the workplace, knowledge of the hazards of smoking, attitude towards quitting smoking, and behavior related to tobacco harm prevention were collected. Results Results showed the prevalence of smoking cessation was 31.5% (95% CI: 25.4-38.1%) after 6 months and 10.7% (95% CI: 6.9-15.6%) after 4 years. At the abovementioned time points, the prevalence of second-hand smoke exposure, and the proportion of people who demonstrated correct knowledge of smoke hazards initially decreased and then increased. The proportion of participants who had seen or received information about tobacco harm prevention provided in the workplace increased from 75.6% at baseline to 95.6% (increased by 20.0%) after 6 months and finally to 97.2% (increased by 21.6%) after 4 years ( P 〈 .001). However, the percentage of participants who hoped their workplace continued to provide smoking cessation services rose from 80.0% at baseline to 93.6% (increased by 13.6%) after 6 months and then fell to 78.0% (decreased by 2.0%) after 4 years ( P 〈 .001). Conclusion The short-term effectiveness of the transtheoretical model in promoting workplace smoking cessation is substantial, but in the long-term, effectiveness weakens.
    Type of Medium: Online Resource
    ISSN: 1179-173X , 1179-173X
    URL: Article
    DOI: 10.1177/1179173X221104410
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2532401-9
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  • 7
    Online Resource
    Online Resource
    Screening the risk of obstructive sleep apnea by utilizing supervised learning techniques based on anthropometric features and snoring events
    SAGE Publications ; 2023
    In:  DIGITAL HEALTH Vol. 9 ( 2023-01), p. 205520762311527-
    Details
    In: DIGITAL HEALTH, SAGE Publications, Vol. 9 ( 2023-01), p. 205520762311527-
    Abstract: Obstructive sleep apnea (OSA) is typically diagnosed by polysomnography (PSG). However, PSG is time-consuming and has some clinical limitations. This study thus aimed to establish machine learning models to screen for the risk of having moderate-to-severe and severe OSA based on easily acquired features. Methods We collected PSG data on 3529 patients from Taiwan and further derived the number of snoring events. Their baseline characteristics and anthropometric measures were obtained, and correlations among the collected variables were investigated. Next, six common supervised machine learning techniques were utilized, including random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor (kNN), support vector machine (SVM), logistic regression (LR), and naïve Bayes (NB). First, data were independently separated into a training and validation dataset (80%) and a test dataset (20%). The approach with the highest accuracy in the training and validation phase was employed to classify the test dataset. Next, feature importance was investigated by calculating the Shapley value of every factor, which represented the impact on OSA risk screening. Results The RF produced the highest accuracy (of 〉 70%) in the training and validation phase in screening for both OSA severities. Hence, we employed the RF to classify the test dataset, and results showed a 79.32% accuracy for moderate-to-severe OSA and 74.37% accuracy for severe OSA. Snoring events and the visceral fat level were the most and second most essential features of screening for OSA risk. Conclusions The established model can be considered for screening for the risk of having moderate-to-severe or severe OSA.
    Type of Medium: Online Resource
    ISSN: 2055-2076 , 2055-2076
    URL: Article
    DOI: 10.1177/20552076231152751
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2819396-9
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  • 8
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    Online Resource
    Clinical predictors for biochemical failure in patients with positive surgical margin after robotic-assisted radical prostatectomy
    SAGE Publications ; 2022
    In:  Tumori Journal Vol. 108, No. 3 ( 2022-06), p. 270-277
    Details
    In: Tumori Journal, SAGE Publications, Vol. 108, No. 3 ( 2022-06), p. 270-277
    Abstract: Patients with positive surgical margins (PSMs) after radical prostatectomy for localized prostate cancer have a higher risk of biochemical failure (BCF). We investigated the risk factors of BCF in patients with PSMs after robotic-assisted radical prostatectomy (RARP). Methods: We evaluated 462 patients who underwent RARP in a single medical center from 2006 through 2013. Of them, 61 with PSMs did not receive any treatment before BCF. Kaplan-Meier curve and Cox regression analysis were used to compare patients with (n = 19) and without (n = 41) BCF. Results: Overall, 13.2% of patients had PSMs, and of those, 31.7% experienced BCF during follow-up. The mean follow-up duration was 43.7 months (42.4 [non-BCF] vs 46.35 (BCF] , p = 0.51). In univariant analyses, the platelet to lymphocyte ratio (6.26 [non-BCF] vs 8.02 [BCF] , p = 0.04) differed statistically. When patients were grouped by pathologic grade ≦2 or ≧3 ( p = 0.004), the BCF-free survival rates differed significantly. Seminal vesicle invasion also differed significantly (5 [non-BCF] vs 7 [BCF] , p = 0.005). Patients with undetectable nadir prostate-specific antigen (PSA) after RARP (BCF rate 4/34) differed statistically from those with detectable PSA after RARP (BCF rate 15/26) ( p 〈 0.001). In the multivariate analysis, the platelet/lymphocyte (P/L) ratio, pathologic grade, and undetectable nadir PSA remained statistically significant. Conclusions: In patients who undergo RARP and have PSMs, P/L ratio 〉 9 preoperatively, pathologic grade ⩾3, and detectable nadir PSA after RARP should be considered adverse features. Early intervention such as salvage radiation therapy or androgen deprivation therapy should be offered to these patients.
    Type of Medium: Online Resource
    ISSN: 0300-8916 , 2038-2529
    URL: Article
    DOI: 10.1177/03008916211007928
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 280962-X
    detail.hit.zdb_id: 2267832-3
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  • 9
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    Adipose-derived Stem Cells Stimulated with n -Butylidenephthalide Exhibit Therapeutic Effects in a Mouse Model of Parkinson’s Disease
    SAGE Publications ; 2018
    In:  Cell Transplantation Vol. 27, No. 3 ( 2018-03), p. 456-470
    Details
    In: Cell Transplantation, SAGE Publications, Vol. 27, No. 3 ( 2018-03), p. 456-470
    Abstract: Parkinson’s disease (PD) causes motor dysfunction and dopaminergic cell death. Drug treatments can effectively reduce symptoms but often cause unwanted side effects. Stem cell therapies using cell replacement or indirect beneficial secretomes have recently emerged as potential therapeutic strategies. Although various types of stem cells have been proposed as possible candidates, adipose-derived stem cells (ADSCs) are easily obtainable, more abundant, less ethically disputed, and able to differentiate into multiple cell lineages. However, treatment of PD using adult stem cells is known to be less efficacious than neuron or embryonic stem cell transplantation. Therefore, improved therapies are urgently needed. n-Butylidenephthalide (BP), which is extracted from Angelica sinensis, has been shown to have anti-inflammatory and neuroprotective effects. Indeed, we previously demonstrated that BP treatment of ADSCs enhances the expression of neurogenesis and homing factors such as nuclear receptor related 1 protein, stromal-derived factor 1, and brain-derived neurotrophic factor. In the present study, we examined the ability of BP-pretreated ADSC transplantation to improve PD motor symptoms and protect dopamine neurons in a mouse model of PD. We evaluated the results using neuronal behavior tests such as beam walking, rotarod, and locomotor activity tests. ADSCs with or without BP pretreatment were transplanted into the striatum. Our findings demonstrated that ADSC transplantation improved motor abilities with varied efficacies and that BP stimulation improved the therapeutic effects of transplantation. Dopaminergic cell numbers returned to normal in ADSC-transplanted mice after 22 d. In summary, stimulating ADSCs with BP improved PD recovery efficiency. Thus, our results provide important new strategies to improve stem cell therapies for neurodegenerative diseases in future studies.
    Type of Medium: Online Resource
    ISSN: 0963-6897 , 1555-3892
    URL: Article
    DOI: 10.1177/0963689718757408
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 2020466-8
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