Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for...Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.展开更多
Technological advances in computer science and their application in our daily life allow us to improve our understanding of problems and solve them effectively.A system design to detect people with fever and determine...Technological advances in computer science and their application in our daily life allow us to improve our understanding of problems and solve them effectively.A system design to detect people with fever and determine highrisk areas using infrared thermography and big data is presented.In order to detect people with fever,face detection algorithms of Viola-Jones and Kanade-Lucas are investigated,and comparison between them is presented using a training set of 406 thermal images and a test set of 2072 thermal images.Thermography analysis is performed on detected faces to obtain the temperature level on Celsius scale.With this information a sample database is created.To perform big data experimental analysis,Power Bi tool is used to determine the high-risk area.The experimental results show that Viola-Jones algorithm has a higher performance recognizing faces of thermal images than KanadeLucas,having a high detection rate,less false-positives rate and false-negatives rate.展开更多
The Torgiovannetto quarry(Assisi municipality,central Italy) is an example of a site where the natural equilibrium was altered by human activity,causing current slope instability phenomena which threaten two roadways ...The Torgiovannetto quarry(Assisi municipality,central Italy) is an example of a site where the natural equilibrium was altered by human activity,causing current slope instability phenomena which threaten two roadways important for the local transportation.The quarry front,having a height of about 140 m,is affected by a 182,000 m3 rockslide developed in intensely fractured limestone and is too large to be stabilized.In 2003 some tension cracks were detected in the vegetated area above the quarry upper sector.From then on,several monitoring campaigns were carried out by means of different instrumentations(topographic total station,extensometers,inclinometers,ground-based interferometric radar,laser scanner and infrared thermal camera),allowing researchers to accurately define the landslide area and volume.The latter's major displacements are localized in the eastern sector.The deformational field appears to be related to the seasonal rainfall.The landslide hazard associated with the worst case scenario was evaluated in terms of magnitude,intensity and triggering mechanism.For the definition of the possible runout process the DAN 3D code was employed.The simulation results were used in order to design and construct a retaining embankment.Furthermore,in order to preserve both the safety of the personnelinvolved in its realization and of the roadways users,an early warning system was implemented.The early warning system is based on daily-averaged displacement velocity thresholds.The alarm level is reached if the prediction based on the methods of Saito(1969) and Fukuzono(1985) forecasts an imminent rupture.展开更多
Monitoring telomerase activity with high sensitive and reliable is of great importance to cancer analysis. In this paper, we report a sensitive and facile method to detect telomerase activity using AIEgens mod- ified ...Monitoring telomerase activity with high sensitive and reliable is of great importance to cancer analysis. In this paper, we report a sensitive and facile method to detect telomerase activity using AIEgens mod- ified probe （TPE-Py-DNA） as a fluorescence reporter and exonuclease llI （Exo lIl） as a signal amplifier. With the aid of telomerase, repeat units （TrAGGG）n are extended from the end of template substrate oligonucleotides （TS primer） that form duplex DNAs with TPE-Py-DNA. Then, Exo llI catalyzes the diges- tion of duplex DNAs, liberating elongation product and releasing hydrophobic TPE-Py. The released hydrophobic TPE-Py aggregate together and produce a telomerase-activity-related fluorescence signal. The liberated product hybridizes with another TPE-Py-DNA probe, starting the second cycle. Finally, we obtain the target-to-signal amplification ratio of 1 ：N2. This strategy exhibits good performance for detecting clinical urine samples （distinguishing 15 cancer patients＇ samples from 8 healthy ones） and checking intracellular telomerase activity （differentiating cell lines including HeLa, MDA-MB-231, MCF-7, A375, HLF and MRC-5 from the cells pretreated with telomerase-related drug）, which shows its potential in clinical diagnosis as well as therapeutic monitoring of cancer.展开更多
基金supported in part by the National Key Research and Development Program of China(No. 2018YFC0309104)the Construction System Science and Technology Project of Jiangsu Province (No.2021JH03)。
文摘Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.
文摘Technological advances in computer science and their application in our daily life allow us to improve our understanding of problems and solve them effectively.A system design to detect people with fever and determine highrisk areas using infrared thermography and big data is presented.In order to detect people with fever,face detection algorithms of Viola-Jones and Kanade-Lucas are investigated,and comparison between them is presented using a training set of 406 thermal images and a test set of 2072 thermal images.Thermography analysis is performed on detected faces to obtain the temperature level on Celsius scale.With this information a sample database is created.To perform big data experimental analysis,Power Bi tool is used to determine the high-risk area.The experimental results show that Viola-Jones algorithm has a higher performance recognizing faces of thermal images than KanadeLucas,having a high detection rate,less false-positives rate and false-negatives rate.
基金the National Department of Civil Protection, the Perugia Province and the Umbria Region for funding the work behind this research
文摘The Torgiovannetto quarry(Assisi municipality,central Italy) is an example of a site where the natural equilibrium was altered by human activity,causing current slope instability phenomena which threaten two roadways important for the local transportation.The quarry front,having a height of about 140 m,is affected by a 182,000 m3 rockslide developed in intensely fractured limestone and is too large to be stabilized.In 2003 some tension cracks were detected in the vegetated area above the quarry upper sector.From then on,several monitoring campaigns were carried out by means of different instrumentations(topographic total station,extensometers,inclinometers,ground-based interferometric radar,laser scanner and infrared thermal camera),allowing researchers to accurately define the landslide area and volume.The latter's major displacements are localized in the eastern sector.The deformational field appears to be related to the seasonal rainfall.The landslide hazard associated with the worst case scenario was evaluated in terms of magnitude,intensity and triggering mechanism.For the definition of the possible runout process the DAN 3D code was employed.The simulation results were used in order to design and construct a retaining embankment.Furthermore,in order to preserve both the safety of the personnelinvolved in its realization and of the roadways users,an early warning system was implemented.The early warning system is based on daily-averaged displacement velocity thresholds.The alarm level is reached if the prediction based on the methods of Saito(1969) and Fukuzono(1985) forecasts an imminent rupture.
基金supported by the National Natural Science Foundation of China(21375042,21405054,21525523,21574048,and21404028)the National Basic Research Program of China(2015CB932600,2013CB933000,and 2016YFF0100800)+1 种基金the Special Fund for Strategic New Industry Development of Shenzhen,China(JCYJ20150616144425376)1000 Young Talent Program(to F.Xia)
文摘Monitoring telomerase activity with high sensitive and reliable is of great importance to cancer analysis. In this paper, we report a sensitive and facile method to detect telomerase activity using AIEgens mod- ified probe （TPE-Py-DNA） as a fluorescence reporter and exonuclease llI （Exo lIl） as a signal amplifier. With the aid of telomerase, repeat units （TrAGGG）n are extended from the end of template substrate oligonucleotides （TS primer） that form duplex DNAs with TPE-Py-DNA. Then, Exo llI catalyzes the diges- tion of duplex DNAs, liberating elongation product and releasing hydrophobic TPE-Py. The released hydrophobic TPE-Py aggregate together and produce a telomerase-activity-related fluorescence signal. The liberated product hybridizes with another TPE-Py-DNA probe, starting the second cycle. Finally, we obtain the target-to-signal amplification ratio of 1 ：N2. This strategy exhibits good performance for detecting clinical urine samples （distinguishing 15 cancer patients＇ samples from 8 healthy ones） and checking intracellular telomerase activity （differentiating cell lines including HeLa, MDA-MB-231, MCF-7, A375, HLF and MRC-5 from the cells pretreated with telomerase-related drug）, which shows its potential in clinical diagnosis as well as therapeutic monitoring of cancer.
