This paper proposes a framework for human action recognition based on procrustes analysis and Fisher vector coding(FVC).Firstly,we applied a pose feature extracted from silhouette image by employing Procrustes analysi...This paper proposes a framework for human action recognition based on procrustes analysis and Fisher vector coding(FVC).Firstly,we applied a pose feature extracted from silhouette image by employing Procrustes analysis and local preserving projection(LPP).Secondly,the extracted feature can preserve the discriminative shape information and local manifold structure of human pose and is invariant to translation,rotation and scaling.Finally,after the pose feature was extracted,a recognition framework based on FVC and multi-class supporting vector machine was employed to classify the human action.Experimental results on benchmarks demonstrate the effectiveness of the proposed method.展开更多
This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in t...This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in the province, namely the non-consideration of seismic action in the study of structures by both professionals and researchers. The main objective of the study is to show the importance of dynamic analysis of structures in South Kivu. It adopts a meta-analytical approach referring to previous researches on South Kivu and proposes an efficient and optimal method. To arrive at the results, we use Eurocode 7 and 8. In addition, we conducted static analysis using the Coulomb method and dynamic analysis using the Mononobe-Okabe method and compared the results. At Nyabibwe, the results showed that we have a deviation of 24.47% for slip stability, 12.038% for overturning stability and 9.677% for stability against punching through a weight wall.展开更多
The single and coupled photonic crystal nanocavity lasers are fabricated in the InGaAsP material system and their static and dynamic features are compared. The coupled-cavity lasers show a larger lasing e^ciency and g...The single and coupled photonic crystal nanocavity lasers are fabricated in the InGaAsP material system and their static and dynamic features are compared. The coupled-cavity lasers show a larger lasing e^ciency and generate an output power higher than the single-cavity lasers, results that are consistent with the theoretical results obtained by rate equations. In dynamic regime, the single-cavity lasers produce pulses as short as 113 ps, while the coupled-cavity lasers show a significantly longer lasing duration. These results indicate that the photonic crystal laser is a promising candidate for the light source in high-speed photonic integrated circuit.展开更多
Quayside container crane is a kind of huge dimension steel structure,which is the major equipment used for handling container at modern ports.With the aim to validate the safety and reliability of the crane under seis...Quayside container crane is a kind of huge dimension steel structure,which is the major equipment used for handling container at modern ports.With the aim to validate the safety and reliability of the crane under seismic loads,besides conventional analysis,elastic-plastic time history analysis under rare seismic intensity is carried out.An ideal finite element(FEM) elastic-plastic mechanical model of the quayside container crane is presented by using ANSYS codes.Furthermore,according to elastic-plastic time history analysis theory,deformation,stress and damage pattern of the structure under rare seismic intensity are investigated.Based on the above analysis,the established reliability model according to the reliability theory,together with seismic reliability analysis based on Monte-Carlo simulation is applied to practical analysis.The results show that the overall structure of the quayside container crane is generally unstable under rare seismic intensity,and the structure needs to be reinforced.展开更多
Climate Change Vulnerability Assessment(VA) tools for forest ecosystems and forest-dependent communities are important for making decisions and understanding the impact of climate change on both social and natural s...Climate Change Vulnerability Assessment(VA) tools for forest ecosystems and forest-dependent communities are important for making decisions and understanding the impact of climate change on both social and natural systems.However,the tools are poorly coordinated,making it difficult for policymakers to carry out VAs properly.The aim of this study was to analyze VA literature worldwide to find representative case studies in terms of methods and tools applied and which have been successful in performing VAs on forests and forest-dependent communities.All successful VA studies analyzed had common characteristics such as significant funding,data availability and technical capacity.An additional characteristic was the development of an integrated approach that considered the vulnerability of both ecosystems and communities by combining qualitative and quantitative methods.Community members and relevant stakeholders were significantly involved in a participatory process that concluded with the identification of adaptation measures.The case studies also revealed how policymakers need to choose suitable methods and tools to undertake efficient assessment of vulnerabilities.They need to consider several aspects of the VA process such as subject matter,availability of resources,time and scale.展开更多
Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodie...Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions.There are various related studies on the real-time classification of actions in an image.However,existing deep learning-based action classification models have prolonged response speeds,so there is a limit to real-time analysis.In addition,it has low accuracy of action of each object ifmultiple objects appear in the image.Also,it needs to be improved since it has a memory overhead in processing image data.Deep learning-based action classification using one-shot object detection is proposed to overcome the limitations of multiframe-based analysis technology.The proposed method uses a one-shot object detection model and a multi-object tracking algorithm to detect and track multiple objects in the image.Then,a deep learning-based pattern classification model is used to classify the body action of the object in the image by reducing the data for each object to an action vector.Compared to the existing studies,the constructed model shows higher accuracy of 74.95%,and in terms of speed,it offered better performance than the current studies at 0.234 s per frame.The proposed model makes it possible to classify some actions only through action vector learning without additional image learning because of the vector learning feature of the posterior neural network.Therefore,it is expected to contribute significantly to commercializing realistic streaming data analysis technologies,such as CCTV.展开更多
The unmanned aerial vehicles( UAV) has been becoming more and more important in the aviation industry.Despite the superior performance and advanced technology,major accident of UAV happens frequently due to the impact...The unmanned aerial vehicles( UAV) has been becoming more and more important in the aviation industry.Despite the superior performance and advanced technology,major accident of UAV happens frequently due to the impact of their systems,long distance of remote control and skill of manipulator technology.According to the application of engineering application,failure mode effects and criticality analysis( FMECA),failure reporting analysis and corrective action comprehensive analysis systems( FRACAS)and fault tree analysis( FTA)( 3 F) were combined.And also a set of user-friendly,more time,more efficient and accurate reliability analysis system were explored.展开更多
Objective:Excavate the compatibility rules of traditional Chinese medicine for preventing and treating postoperative complications of breast cancer,study the potential mechanism of prevention and treatment with tradit...Objective:Excavate the compatibility rules of traditional Chinese medicine for preventing and treating postoperative complications of breast cancer,study the potential mechanism of prevention and treatment with traditional Chinese medicine.Methods:Collate and analyze the relevant prescriptions collected from CNKI and the core drug combination and the new formula are obtained by adopting the traditional Chinese medicine inheritance auxiliary system(TCMISSV2.5).Use BATMAN-TCM online analysis tool to analyze KEGG pathways of high frequency drugs and predict the potential signal pathways.Results:Data mining has selected 10 pairs of core herb combinations and 5 new recipes of 133 prescriptions.In the network pharmacology analysis of bai zhu,huang qi,fu ling,the potential signaling pathways of its action are the neuroactive ligand-receptor interaction pathway and calcium signaling pathway.Conclusion:Herbs for invigorating spleen and qi and herbs for nourishing blood and activating blood are commonly used to prevent and treat postoperative complications of breast cancer.Core herbs may play their role by interfering with the neuroactive ligand-receptor interaction pathway and calcium signaling pathway.展开更多
Bupleurum has been used as traditional medicine in China,Japan,South Korea,and other Asian countries for more than 2,000 years.The crude extracts and pure compounds isolated from Bupleurum have a variety of biological...Bupleurum has been used as traditional medicine in China,Japan,South Korea,and other Asian countries for more than 2,000 years.The crude extracts and pure compounds isolated from Bupleurum have a variety of biological activities,such as anti-inflammatory,anti-cancer,antipyretic,antibacterial,anti-viral,liver protection,neuroprotection,and immune regxilation.The pharmacological effects of Bupleurum have been classified and summarized in this paper by consulting literatures at home and abroad.At the same time,the quality analysis methods of bupleurum,including high-performance liquid chromatography,thin layer chromatography,ultra-high-performance liquid chromatography mass spectrometry,UPLC-QTOF-MS,and so on,are discussed.This paper provides a reference for further research,development,and application of Bupleurum.展开更多
Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and auto...Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and automated analysis of video information is required.However,various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging.Video analysis technology applies object classification,detection,and relationship analysis to continuous 2D frame data,and the various meanings within the video are thus analyzed based on the extracted basic data.Motion recognition is key in this analysis.Motion recognition is a challenging field that analyzes human body movements,requiring the interpretation of complex movements of human joints and the relationships between various objects.The deep learning-based human skeleton detection algorithm is a representative motion recognition algorithm.Recently,motion analysis models such as the SlowFast network algorithm,have also been developed with excellent performance.However,these models do not operate properly in most wide-angle video environments outdoors,displaying low response speed,as expected from motion classification extraction in environments associated with high-resolution images.The proposed method achieves high level of extraction and accuracy by improving SlowFast’s input data preprocessing and data structure methods.The input data are preprocessed through object tracking and background removal using YOLO and DeepSORT.A higher performance than that of a single model is achieved by improving the existing SlowFast’s data structure into a frame unit structure.Based on the confusion matrix,accuracies of 70.16%and 70.74%were obtained for the existing SlowFast and proposed model,respectively,indicating a 0.58%increase in accuracy.Comparing detection,based on behavioral classification,the existing SlowFast detected 2,341,164 cases,whereas the proposed model detected 3,119,323 cases,which is an increase of 33.23%.展开更多
Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desir...Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.展开更多
How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable i...How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].展开更多
Nowadays, there is a great need to investigate the effects of fatigue on physical as well as mental performance. The issues that are generally associated with extreme fatigue are that one can easily lose one’s focus ...Nowadays, there is a great need to investigate the effects of fatigue on physical as well as mental performance. The issues that are generally associated with extreme fatigue are that one can easily lose one’s focus while performing any particular activity whether it is physical or mental and this decreases one’s motivation to complete the task at hand efficiently and successfully. In the same line of thought, myriads of research studies posited the negative effects of fatigue on mental performance, and most techniques to induce fatigue to require normally long-time and repetitive visual search tasks. In this study, a visual search algorithm task was devised and customized using performance measures such as <em>d</em>’ (<strong>d-prime</strong>) and Speed Accuracy Trade-Off (<strong>SATF</strong>) as well as <strong>ROC</strong> analysis for classifier performance. The visual search algorithm consisted of distractors (<strong>L</strong>) and a target (<strong>T</strong>) whereby human participants had to press the appropriate keyboard button as fast as possible if they notice a target or not upon presentation of a visual stimulus. It was administered to human participants under laboratory conditions, and the reaction times, as well as accuracy of the participants, were monitored. It was found that the test image Size35Int255 was the best image to be used in terms of sensitivity and AUC (Area under Curve). Therefore, ongoing researches can use these findings to create their visual stimuli in such a way that the target and distractor images follow the size and intensity characteristics as found in this research.展开更多
基金National Natural Science Foundation of China(No.61602148)Natural Science Foundation of Fujian Province,China(No.2016J01040)Xiamen University of Technology High Level Talents Project,China(No.YKJ15018R)
文摘This paper proposes a framework for human action recognition based on procrustes analysis and Fisher vector coding(FVC).Firstly,we applied a pose feature extracted from silhouette image by employing Procrustes analysis and local preserving projection(LPP).Secondly,the extracted feature can preserve the discriminative shape information and local manifold structure of human pose and is invariant to translation,rotation and scaling.Finally,after the pose feature was extracted,a recognition framework based on FVC and multi-class supporting vector machine was employed to classify the human action.Experimental results on benchmarks demonstrate the effectiveness of the proposed method.
文摘This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in the province, namely the non-consideration of seismic action in the study of structures by both professionals and researchers. The main objective of the study is to show the importance of dynamic analysis of structures in South Kivu. It adopts a meta-analytical approach referring to previous researches on South Kivu and proposes an efficient and optimal method. To arrive at the results, we use Eurocode 7 and 8. In addition, we conducted static analysis using the Coulomb method and dynamic analysis using the Mononobe-Okabe method and compared the results. At Nyabibwe, the results showed that we have a deviation of 24.47% for slip stability, 12.038% for overturning stability and 9.677% for stability against punching through a weight wall.
基金Supported by the National Key Basic Research Special Fund/CNKBRSF of China under Grant Nos 2012CB933501,2016YFA0301102,2016YFB0401804 and 2016YFB0402203the National Natural Science Foundation of China under Grant Nos61535013,61321063 and 61137003+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant Nos XDB24010100,XDB24010200,XDB24020100 and XDB24030100the One Hundred Person Project of the Chinese Academy of Sciences
文摘The single and coupled photonic crystal nanocavity lasers are fabricated in the InGaAsP material system and their static and dynamic features are compared. The coupled-cavity lasers show a larger lasing e^ciency and generate an output power higher than the single-cavity lasers, results that are consistent with the theoretical results obtained by rate equations. In dynamic regime, the single-cavity lasers produce pulses as short as 113 ps, while the coupled-cavity lasers show a significantly longer lasing duration. These results indicate that the photonic crystal laser is a promising candidate for the light source in high-speed photonic integrated circuit.
基金supported by National High Technology Research and Development Program 863 Plan (No. 2009AA043000)
文摘Quayside container crane is a kind of huge dimension steel structure,which is the major equipment used for handling container at modern ports.With the aim to validate the safety and reliability of the crane under seismic loads,besides conventional analysis,elastic-plastic time history analysis under rare seismic intensity is carried out.An ideal finite element(FEM) elastic-plastic mechanical model of the quayside container crane is presented by using ANSYS codes.Furthermore,according to elastic-plastic time history analysis theory,deformation,stress and damage pattern of the structure under rare seismic intensity are investigated.Based on the above analysis,the established reliability model according to the reliability theory,together with seismic reliability analysis based on Monte-Carlo simulation is applied to practical analysis.The results show that the overall structure of the quayside container crane is generally unstable under rare seismic intensity,and the structure needs to be reinforced.
基金the FAO Forestry Department for the opportunity to conduct the research and for their support
文摘Climate Change Vulnerability Assessment(VA) tools for forest ecosystems and forest-dependent communities are important for making decisions and understanding the impact of climate change on both social and natural systems.However,the tools are poorly coordinated,making it difficult for policymakers to carry out VAs properly.The aim of this study was to analyze VA literature worldwide to find representative case studies in terms of methods and tools applied and which have been successful in performing VAs on forests and forest-dependent communities.All successful VA studies analyzed had common characteristics such as significant funding,data availability and technical capacity.An additional characteristic was the development of an integrated approach that considered the vulnerability of both ecosystems and communities by combining qualitative and quantitative methods.Community members and relevant stakeholders were significantly involved in a participatory process that concluded with the identification of adaptation measures.The case studies also revealed how policymakers need to choose suitable methods and tools to undertake efficient assessment of vulnerabilities.They need to consider several aspects of the VA process such as subject matter,availability of resources,time and scale.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.NRF-2022R1I1A1A01069526).
文摘Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions.There are various related studies on the real-time classification of actions in an image.However,existing deep learning-based action classification models have prolonged response speeds,so there is a limit to real-time analysis.In addition,it has low accuracy of action of each object ifmultiple objects appear in the image.Also,it needs to be improved since it has a memory overhead in processing image data.Deep learning-based action classification using one-shot object detection is proposed to overcome the limitations of multiframe-based analysis technology.The proposed method uses a one-shot object detection model and a multi-object tracking algorithm to detect and track multiple objects in the image.Then,a deep learning-based pattern classification model is used to classify the body action of the object in the image by reducing the data for each object to an action vector.Compared to the existing studies,the constructed model shows higher accuracy of 74.95%,and in terms of speed,it offered better performance than the current studies at 0.234 s per frame.The proposed model makes it possible to classify some actions only through action vector learning without additional image learning because of the vector learning feature of the posterior neural network.Therefore,it is expected to contribute significantly to commercializing realistic streaming data analysis technologies,such as CCTV.
基金Naional Natural Science Foundntion of China(No.71761030)
文摘The unmanned aerial vehicles( UAV) has been becoming more and more important in the aviation industry.Despite the superior performance and advanced technology,major accident of UAV happens frequently due to the impact of their systems,long distance of remote control and skill of manipulator technology.According to the application of engineering application,failure mode effects and criticality analysis( FMECA),failure reporting analysis and corrective action comprehensive analysis systems( FRACAS)and fault tree analysis( FTA)( 3 F) were combined.And also a set of user-friendly,more time,more efficient and accurate reliability analysis system were explored.
基金funded by the National Natural Science Foundation of Hebei(No.H2018201179)Hebei University of Science and Technology(No.QN2016077)Health and Family Planning Commission of Hebei(No.20160388).
文摘Objective:Excavate the compatibility rules of traditional Chinese medicine for preventing and treating postoperative complications of breast cancer,study the potential mechanism of prevention and treatment with traditional Chinese medicine.Methods:Collate and analyze the relevant prescriptions collected from CNKI and the core drug combination and the new formula are obtained by adopting the traditional Chinese medicine inheritance auxiliary system(TCMISSV2.5).Use BATMAN-TCM online analysis tool to analyze KEGG pathways of high frequency drugs and predict the potential signal pathways.Results:Data mining has selected 10 pairs of core herb combinations and 5 new recipes of 133 prescriptions.In the network pharmacology analysis of bai zhu,huang qi,fu ling,the potential signaling pathways of its action are the neuroactive ligand-receptor interaction pathway and calcium signaling pathway.Conclusion:Herbs for invigorating spleen and qi and herbs for nourishing blood and activating blood are commonly used to prevent and treat postoperative complications of breast cancer.Core herbs may play their role by interfering with the neuroactive ligand-receptor interaction pathway and calcium signaling pathway.
文摘Bupleurum has been used as traditional medicine in China,Japan,South Korea,and other Asian countries for more than 2,000 years.The crude extracts and pure compounds isolated from Bupleurum have a variety of biological activities,such as anti-inflammatory,anti-cancer,antipyretic,antibacterial,anti-viral,liver protection,neuroprotection,and immune regxilation.The pharmacological effects of Bupleurum have been classified and summarized in this paper by consulting literatures at home and abroad.At the same time,the quality analysis methods of bupleurum,including high-performance liquid chromatography,thin layer chromatography,ultra-high-performance liquid chromatography mass spectrometry,UPLC-QTOF-MS,and so on,are discussed.This paper provides a reference for further research,development,and application of Bupleurum.
基金supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1A6A1A03040583)supported by Kyonggi University’s Graduate Research Assistantship 2023.
文摘Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and automated analysis of video information is required.However,various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging.Video analysis technology applies object classification,detection,and relationship analysis to continuous 2D frame data,and the various meanings within the video are thus analyzed based on the extracted basic data.Motion recognition is key in this analysis.Motion recognition is a challenging field that analyzes human body movements,requiring the interpretation of complex movements of human joints and the relationships between various objects.The deep learning-based human skeleton detection algorithm is a representative motion recognition algorithm.Recently,motion analysis models such as the SlowFast network algorithm,have also been developed with excellent performance.However,these models do not operate properly in most wide-angle video environments outdoors,displaying low response speed,as expected from motion classification extraction in environments associated with high-resolution images.The proposed method achieves high level of extraction and accuracy by improving SlowFast’s input data preprocessing and data structure methods.The input data are preprocessed through object tracking and background removal using YOLO and DeepSORT.A higher performance than that of a single model is achieved by improving the existing SlowFast’s data structure into a frame unit structure.Based on the confusion matrix,accuracies of 70.16%and 70.74%were obtained for the existing SlowFast and proposed model,respectively,indicating a 0.58%increase in accuracy.Comparing detection,based on behavioral classification,the existing SlowFast detected 2,341,164 cases,whereas the proposed model detected 3,119,323 cases,which is an increase of 33.23%.
文摘Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.
文摘How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].
文摘Nowadays, there is a great need to investigate the effects of fatigue on physical as well as mental performance. The issues that are generally associated with extreme fatigue are that one can easily lose one’s focus while performing any particular activity whether it is physical or mental and this decreases one’s motivation to complete the task at hand efficiently and successfully. In the same line of thought, myriads of research studies posited the negative effects of fatigue on mental performance, and most techniques to induce fatigue to require normally long-time and repetitive visual search tasks. In this study, a visual search algorithm task was devised and customized using performance measures such as <em>d</em>’ (<strong>d-prime</strong>) and Speed Accuracy Trade-Off (<strong>SATF</strong>) as well as <strong>ROC</strong> analysis for classifier performance. The visual search algorithm consisted of distractors (<strong>L</strong>) and a target (<strong>T</strong>) whereby human participants had to press the appropriate keyboard button as fast as possible if they notice a target or not upon presentation of a visual stimulus. It was administered to human participants under laboratory conditions, and the reaction times, as well as accuracy of the participants, were monitored. It was found that the test image Size35Int255 was the best image to be used in terms of sensitivity and AUC (Area under Curve). Therefore, ongoing researches can use these findings to create their visual stimuli in such a way that the target and distractor images follow the size and intensity characteristics as found in this research.