Significance:Over 80%of cervical cancer cases occur in lower-to-middle income countries(LMIC’s).This is partly because current screening techniques lack affordability,accessibility,and/or reliability for use in LMIC...Significance:Over 80%of cervical cancer cases occur in lower-to-middle income countries(LMIC’s).This is partly because current screening techniques lack affordability,accessibility,and/or reliability for use in LMIC’s.Aim:To develop an optical technique for cervical cancer screening that is affordable,accessible,and reliable for use in LMIC’s.Approach:We developed a portable diffuse reflectance spectroscopy(DRS)system,which costs$<2500 USD to manufacture,and employs a Raspberry Pi to extract the absorption(μα)and reduced scattering(μ′s)coefficients of biological tissue.The system was subject to travel and intentional rough handling.It was further used to capture 320 DRS spectra taken from 64 tissue-mimicking phantoms.Two users collected phantom data,one“expert”,and one“novice”in biomedical optics.The system was also used to collect 335 spectra from colon,small intestine,and rectal tissue of a fresh ex vivo porcine specimen.A previously described artificial intelligence model was used to extract optical properties,and a GradientBoostingClassifier identified the organ of origin for ex vivo spectra.Results:System alignment was robust to intentional rough handling and travel.Phantomμαandμ′s were predicted with average root-mean square error of<10%,regardless of user.Regarding ex vivo data,the system predicted the organ of origin with 80–90%accuracy.Statistical differences between predicted wereμαobserved in all three organs(P<0.001–0.03),and betweenμ′s in two organs(P<0.001–0.07).Conclusions:The DRS system has the potential to be affordable,reliable,and accessible for cervical screening in LMIC’s.展开更多
Background:The aging global population necessitates innovative strategies to enhance older adults’health and quality of life.Physical activity(PA)is crucial for healthy aging,yet many older adults struggle to exercis...Background:The aging global population necessitates innovative strategies to enhance older adults’health and quality of life.Physical activity(PA)is crucial for healthy aging,yet many older adults struggle to exercise regularly.Artificial intelligence(AI)-powered social robots offer an interactive,engaging,and personalized solution to promote PA among this demographic.This systematic review investigated the role of AI-powered social robots in encouraging PA in older adults.Methods:We conducted a systematic literature search in databases including PubMed,IEEE Xplore,Scopus,Cochrane Library,and Web of Science,focusing on studies published until February 2024.We included peer-reviewed articles reporting empiricalfindings on designing,implementing,and evaluating AI-enabled social robots to promote PA among older adults.Studies were conducted in nursing homes,rehabilita-tion centers,community centers,and home environments.Results:A total of 19 studies were included in the review.Analysis reveals that AI-powered social robots effectively motivate older adults to engage in PAs,leading to increased exercise adherence,higher engagement levels,and extended training durations.Social robots have demon-strated effectiveness across various environments,including nursing homes,rehabilitation centers,community centers,home environments,and elder care facilities.In structured environments like nursing homes and rehabilitation centers,robots help maintain regular exercise routines,improving adherence and recovery outcomes.In community and elder care centers,robots promote PA and social engagement by facilitating group exercises and enhancing participation.In home environments,robots provide personalized support for daily activities,offering reminders and engagement,which fosters long-term activity engagement.User acceptance and satisfaction are high,with participantsfinding the robots engaging and enjoyable.Additionally,several studies indicate potential health benefits,such as improved medication adherence,better sleep patterns,and enhanced overall well-being.Nevertheless,additional research is imperative to address unresolved issues concerning the technolog-ical maintenance costs,design constraints,and adaptability of AI-powered social robots to specific user demographics.Conclusion:AI-powered social robots play a promising role in promoting PA among older adults,enhancing their health,well-being,and inde-pendence.This review provides insights for researchers,designers,and healthcare professionals developing AI-enabled social robotic systems for older adults.展开更多
1故障现象Siemens Artis Zee系列数字减影血管造影系统(digital subtraction angiography,DSA)在使用过程中,不能进行摄影采集,只能进行X线透视。同时,检查室内参考图像显示屏底侧区域的信息栏显示“Bypass”,控制室内实时图像显示屏右...1故障现象Siemens Artis Zee系列数字减影血管造影系统(digital subtraction angiography,DSA)在使用过程中,不能进行摄影采集,只能进行X线透视。同时,检查室内参考图像显示屏底侧区域的信息栏显示“Bypass”,控制室内实时图像显示屏右侧区域的各个曝光参数变灰,且不能被修改。展开更多
Rapid increase in the large quantity of industrial data,Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation,data sensing and collection,real-time data processing,and high request ar...Rapid increase in the large quantity of industrial data,Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation,data sensing and collection,real-time data processing,and high request arrival rates.The classical intrusion detection system(IDS)is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity.To resolve these issues,this paper designs a new Chaotic Cuckoo Search Optimiza-tion Algorithm(CCSOA)with optimal wavelet kernel extreme learning machine(OWKELM)named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform.The CCSOA-OWKELM technique focuses on the design of feature selection with classification approach to achieve minimum computation complex-ity and maximum detection accuracy.The CCSOA-OWKELM technique involves the design of CCSOA based feature selection technique,which incorpo-rates the concepts of chaotic maps with CSOA.Besides,the OWKELM technique is applied for the intrusion detection and classification process.In addition,the OWKELM technique is derived by the hyperparameter tuning of the WKELM technique by the use of sunflower optimization(SFO)algorithm.The utilization of CCSOA for feature subset selection and SFO algorithm based hyperparameter tuning leads to better performance.In order to guarantee the supreme performance of the CCSOA-OWKELM technique,a wide range of experiments take place on two benchmark datasets and the experimental outcomes demonstrate the promis-ing performance of the CCSOA-OWKELM technique over the recent state of art techniques.展开更多
文摘Significance:Over 80%of cervical cancer cases occur in lower-to-middle income countries(LMIC’s).This is partly because current screening techniques lack affordability,accessibility,and/or reliability for use in LMIC’s.Aim:To develop an optical technique for cervical cancer screening that is affordable,accessible,and reliable for use in LMIC’s.Approach:We developed a portable diffuse reflectance spectroscopy(DRS)system,which costs$<2500 USD to manufacture,and employs a Raspberry Pi to extract the absorption(μα)and reduced scattering(μ′s)coefficients of biological tissue.The system was subject to travel and intentional rough handling.It was further used to capture 320 DRS spectra taken from 64 tissue-mimicking phantoms.Two users collected phantom data,one“expert”,and one“novice”in biomedical optics.The system was also used to collect 335 spectra from colon,small intestine,and rectal tissue of a fresh ex vivo porcine specimen.A previously described artificial intelligence model was used to extract optical properties,and a GradientBoostingClassifier identified the organ of origin for ex vivo spectra.Results:System alignment was robust to intentional rough handling and travel.Phantomμαandμ′s were predicted with average root-mean square error of<10%,regardless of user.Regarding ex vivo data,the system predicted the organ of origin with 80–90%accuracy.Statistical differences between predicted wereμαobserved in all three organs(P<0.001–0.03),and betweenμ′s in two organs(P<0.001–0.07).Conclusions:The DRS system has the potential to be affordable,reliable,and accessible for cervical screening in LMIC’s.
基金supported by the Ministry of Education of Humanities and Social Science project(Grant No.22YJC890024).
文摘Background:The aging global population necessitates innovative strategies to enhance older adults’health and quality of life.Physical activity(PA)is crucial for healthy aging,yet many older adults struggle to exercise regularly.Artificial intelligence(AI)-powered social robots offer an interactive,engaging,and personalized solution to promote PA among this demographic.This systematic review investigated the role of AI-powered social robots in encouraging PA in older adults.Methods:We conducted a systematic literature search in databases including PubMed,IEEE Xplore,Scopus,Cochrane Library,and Web of Science,focusing on studies published until February 2024.We included peer-reviewed articles reporting empiricalfindings on designing,implementing,and evaluating AI-enabled social robots to promote PA among older adults.Studies were conducted in nursing homes,rehabilita-tion centers,community centers,and home environments.Results:A total of 19 studies were included in the review.Analysis reveals that AI-powered social robots effectively motivate older adults to engage in PAs,leading to increased exercise adherence,higher engagement levels,and extended training durations.Social robots have demon-strated effectiveness across various environments,including nursing homes,rehabilitation centers,community centers,home environments,and elder care facilities.In structured environments like nursing homes and rehabilitation centers,robots help maintain regular exercise routines,improving adherence and recovery outcomes.In community and elder care centers,robots promote PA and social engagement by facilitating group exercises and enhancing participation.In home environments,robots provide personalized support for daily activities,offering reminders and engagement,which fosters long-term activity engagement.User acceptance and satisfaction are high,with participantsfinding the robots engaging and enjoyable.Additionally,several studies indicate potential health benefits,such as improved medication adherence,better sleep patterns,and enhanced overall well-being.Nevertheless,additional research is imperative to address unresolved issues concerning the technolog-ical maintenance costs,design constraints,and adaptability of AI-powered social robots to specific user demographics.Conclusion:AI-powered social robots play a promising role in promoting PA among older adults,enhancing their health,well-being,and inde-pendence.This review provides insights for researchers,designers,and healthcare professionals developing AI-enabled social robotic systems for older adults.
文摘1故障现象Siemens Artis Zee系列数字减影血管造影系统(digital subtraction angiography,DSA)在使用过程中,不能进行摄影采集,只能进行X线透视。同时,检查室内参考图像显示屏底侧区域的信息栏显示“Bypass”,控制室内实时图像显示屏右侧区域的各个曝光参数变灰,且不能被修改。
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP1/338/40)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R237)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Rapid increase in the large quantity of industrial data,Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation,data sensing and collection,real-time data processing,and high request arrival rates.The classical intrusion detection system(IDS)is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity.To resolve these issues,this paper designs a new Chaotic Cuckoo Search Optimiza-tion Algorithm(CCSOA)with optimal wavelet kernel extreme learning machine(OWKELM)named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform.The CCSOA-OWKELM technique focuses on the design of feature selection with classification approach to achieve minimum computation complex-ity and maximum detection accuracy.The CCSOA-OWKELM technique involves the design of CCSOA based feature selection technique,which incorpo-rates the concepts of chaotic maps with CSOA.Besides,the OWKELM technique is applied for the intrusion detection and classification process.In addition,the OWKELM technique is derived by the hyperparameter tuning of the WKELM technique by the use of sunflower optimization(SFO)algorithm.The utilization of CCSOA for feature subset selection and SFO algorithm based hyperparameter tuning leads to better performance.In order to guarantee the supreme performance of the CCSOA-OWKELM technique,a wide range of experiments take place on two benchmark datasets and the experimental outcomes demonstrate the promis-ing performance of the CCSOA-OWKELM technique over the recent state of art techniques.
