Within the context of global climate change and rapid urbanization,increasing urban resilience(UR)is especially important in the arid region of Northwest China(ANC),where fragile ecosystems and an uneven water distrib...Within the context of global climate change and rapid urbanization,increasing urban resilience(UR)is especially important in the arid region of Northwest China(ANC),where fragile ecosystems and an uneven water distribution create significant sustainability challenges.In this study,a coupled UR-water ecosystem services(WESs)framework was developed on the basis of 1-km resolution remote sensing data for the 2000–2020 period obtained from the Landsat series,Defense Meteorological Satellite Program(DMSP)/Operational Linescan System(OLS),and Global Precipitation Measurement(GPM),among other sources.Within the framework,the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model was incorporated to provide a WES indicator system.Moreover,entropy weighting was employed to quantify both UR and WES indicators;the coupling coordination degree(CCD)model was used to measure the coupled relationship between UR and WESs;an extreme gradient boosting(XGBoost)-SHapley Additive exPlanations(SHAP)interpretation approach was adopted to identify key drivers and underlying mechanisms;and Geographically Weighted Regression(GWR)was applied to capture spatial distribution characteristics of major driving factors.The results indicated that UR steadily increased from 4.60×10^(-3) to 10.24×10^(-3),whereas WESs followed an inverted V-shaped trend,with a peak value observed in 2010(11.84×10^(-3)).The CCD remained consistently low(mean:0.0166–0.0246)and exhibited considerable spatial heterogeneity.Notably,the degree of coordination was greater in the oasis and mountain core areas but significantly lower at desert areas.XGBoost-SHAP model analysis revealed six key drivers influencing various states of the CCD between UR and WESs systems.The contributions of these factors could be ranked as follows:water yield(WY;24.30%)>farmland area per capita(FP;21.10%)>gross domestic product(GDP)per capita(GDPC;19.00%)>soil retention(SR;14.90%)>population density(PD;5.42%)>water purification(WP;4.40%).In contrast,in UR system,WP(53.66%)and SR(31.62%)served as the dominant drivers.Moreover,the dominant drivers shifted from a combination of natural and socioeconomic factors in StateⅠ(sustainable high resilience)to primarily socioeconomic factors in StateⅢ(unsustainable low resilience).SR and WP exerted positive moderating effects,whereas socioeconomic factors such as GDPC and PD exerted inhibitory effects on the coordination relationship.This research highlights that UR in the ANC region is limited mainly by water scarcity,weak feedback loops,and spatial variability,emphasizing the need for tailored intervention strategies.展开更多
With the growing aging population, age-related diseases have increased considerably over the years.In response to these, Ambient Assistive Living（AAL） systems are being developed and are continually evolving to enri...With the growing aging population, age-related diseases have increased considerably over the years.In response to these, Ambient Assistive Living（AAL） systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust Activity Recognition（AR）techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create Wireless Sensor Networks（WSNs） for real-time applications. The system architecture brings together the Service-Oriented Architecture（SOA）, semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems,including composite AR.展开更多
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01B109)the Tianchi Doctoral Program of Xinjiang Uygur Autonomous Region(BS2021007).
文摘Within the context of global climate change and rapid urbanization,increasing urban resilience(UR)is especially important in the arid region of Northwest China(ANC),where fragile ecosystems and an uneven water distribution create significant sustainability challenges.In this study,a coupled UR-water ecosystem services(WESs)framework was developed on the basis of 1-km resolution remote sensing data for the 2000–2020 period obtained from the Landsat series,Defense Meteorological Satellite Program(DMSP)/Operational Linescan System(OLS),and Global Precipitation Measurement(GPM),among other sources.Within the framework,the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model was incorporated to provide a WES indicator system.Moreover,entropy weighting was employed to quantify both UR and WES indicators;the coupling coordination degree(CCD)model was used to measure the coupled relationship between UR and WESs;an extreme gradient boosting(XGBoost)-SHapley Additive exPlanations(SHAP)interpretation approach was adopted to identify key drivers and underlying mechanisms;and Geographically Weighted Regression(GWR)was applied to capture spatial distribution characteristics of major driving factors.The results indicated that UR steadily increased from 4.60×10^(-3) to 10.24×10^(-3),whereas WESs followed an inverted V-shaped trend,with a peak value observed in 2010(11.84×10^(-3)).The CCD remained consistently low(mean:0.0166–0.0246)and exhibited considerable spatial heterogeneity.Notably,the degree of coordination was greater in the oasis and mountain core areas but significantly lower at desert areas.XGBoost-SHAP model analysis revealed six key drivers influencing various states of the CCD between UR and WESs systems.The contributions of these factors could be ranked as follows:water yield(WY;24.30%)>farmland area per capita(FP;21.10%)>gross domestic product(GDP)per capita(GDPC;19.00%)>soil retention(SR;14.90%)>population density(PD;5.42%)>water purification(WP;4.40%).In contrast,in UR system,WP(53.66%)and SR(31.62%)served as the dominant drivers.Moreover,the dominant drivers shifted from a combination of natural and socioeconomic factors in StateⅠ(sustainable high resilience)to primarily socioeconomic factors in StateⅢ(unsustainable low resilience).SR and WP exerted positive moderating effects,whereas socioeconomic factors such as GDPC and PD exerted inhibitory effects on the coordination relationship.This research highlights that UR in the ANC region is limited mainly by water scarcity,weak feedback loops,and spatial variability,emphasizing the need for tailored intervention strategies.
基金partially supported by EU H2020 Marie Sklodowska-Curie ActionsITNETN(ACROSSING Project ID:676157)Research Investment Fund,DMU
文摘With the growing aging population, age-related diseases have increased considerably over the years.In response to these, Ambient Assistive Living（AAL） systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust Activity Recognition（AR）techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create Wireless Sensor Networks（WSNs） for real-time applications. The system architecture brings together the Service-Oriented Architecture（SOA）, semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems,including composite AR.
