Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for ...Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for high recognition accuracy with datasets with problems such as scenes with blurred pictures,and inconsistent objects.To address this challenge,we proposed an effective,lightweight object detector method called the RFNet model(YOLO-FR).The YOLO-FR is a lightweight and effective model.Specifically,for efficient multi-scale feature extraction,effective feature pyramid shared convolutional(FPSC)was designed to improve the feature extract performance by leveraging convolutional layers with varying dilation rates from the input image in the backbone.Secondly,to address the problem of multi-scale variability in the scene,we design the Rep Ghost fusion Cross Stage Partial and Efficient Layer Aggregation Network(RGCSPELAN)to improve the network performance further and reduce the amount of computation and the number of parameters.In addition,by conducting experimental valuation on the SCB dataset3 and STBD-08 dataset.Experimental results indicate that,compared to the baseline model,the RFNet model has increased mean accuracy precision(mAP@50)from 69.6%to 71.0%on the SCB dataset3 and from 91.8%to 93.1%on the STBD-08 dataset.The RFNet approach has effectiveness precision at 68.6%,surpassing the baseline method(YOLOv11)at 3.3%and archieve the minimal size(4.9 M)on the SCB dataset3.Finally,comparing it with other algorithms,it accurately detects student behavior in complex classroom environments results confirmed that RFNet is well-suited for real-time and efficiently recognizing classroom behaviors.展开更多
Social responsibility investment(SRI)has attracted worldwide attention for its potential in promoting investment sustainability and stability.We developed a three-step framework by incorporating environmental,social,a...Social responsibility investment(SRI)has attracted worldwide attention for its potential in promoting investment sustainability and stability.We developed a three-step framework by incorporating environmental,social,and governance(ESG)performance into portfolio optimization.In comparison to studies using weighted ESG rating scores,we constructed a data envelopment analysis(DEA)model with quadratic and cubic terms to enhance the evidence of two or more aspects,as well as the interaction between the environmental,social,and governance attributes.We then combined the ESG scores with financial indicators to select assets based on a cross-efficiency analysis.The portfolio optimization model incorporating ESG scores with selected assets was constructed to obtain a social responsibility investment strategy.To illustrate the effectiveness of the proposed approach,we applied it in the United States industrial stock market from 2005 to 2017.The empirical results show that the obtained SRI portfolio may be superior to traditional investment strategies in many aspects and may simultaneously achieve the consistency of investment and social values.展开更多
This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs ...This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.展开更多
Developing efficient catalysts and photosensitizers is crucial for the construction of effective photocatalytic H2-evolving systems.Here,we report the facile preparation of Coumarin-modified Ir(III)complexes(PS-2 and ...Developing efficient catalysts and photosensitizers is crucial for the construction of effective photocatalytic H2-evolving systems.Here,we report the facile preparation of Coumarin-modified Ir(III)complexes(PS-2 and PS-3)and their utilization as chromophores to drive favorable photocatalytic H2 evolution using Ni-substituted polyoxometalate(Ni_(3)PW_(10))catalyst and triethanolamine(TEOA)as an electron donor.Compared with the commercially available unmodified Ir(III)complex(PS-1),both PS-2 and PS-3 displayed intensive absorption in the range of 400–550 nm with ε_(max) of 110,620 and 91,430 M^(−1) cm6(−1),respectively.Varying the substitutes on the bipyridine ligand affected their physicochemical properties and the corresponding photocatalytic activity dramatically.Under photocatalytic conditions,the quantity of H2 molecules generated by PS-2-and PS-3-containing systems were 13.1 and 2.1 times,respectively,that of the PS-1-containing system.When PS-2 was used as a photosensitizer,the highest turnover number(TON)of 19,739 was obtained versus Ni_(3)PW_(10) catalyst.Various spectroscopic and computational studies have revealed that factors such as strong and broad visible-light-absorbing ability,long-lived triplet state,suitable redox potential,opposed by using polyoxometalate(POM)catalyst,and large highest occupied molecular orbital(HOMO)–lowest unoccupied molecular orbital(LUMO)gap of PS-2 attributed to drastically enhanced photocatalytic activity.展开更多
基金suported by the Fundamental Research Grant Scheme(FRGS)of Universiti Sains Malaysia,Research Number:FRGS/1/2024/ICT02/USM/02/1.
文摘Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for high recognition accuracy with datasets with problems such as scenes with blurred pictures,and inconsistent objects.To address this challenge,we proposed an effective,lightweight object detector method called the RFNet model(YOLO-FR).The YOLO-FR is a lightweight and effective model.Specifically,for efficient multi-scale feature extraction,effective feature pyramid shared convolutional(FPSC)was designed to improve the feature extract performance by leveraging convolutional layers with varying dilation rates from the input image in the backbone.Secondly,to address the problem of multi-scale variability in the scene,we design the Rep Ghost fusion Cross Stage Partial and Efficient Layer Aggregation Network(RGCSPELAN)to improve the network performance further and reduce the amount of computation and the number of parameters.In addition,by conducting experimental valuation on the SCB dataset3 and STBD-08 dataset.Experimental results indicate that,compared to the baseline model,the RFNet model has increased mean accuracy precision(mAP@50)from 69.6%to 71.0%on the SCB dataset3 and from 91.8%to 93.1%on the STBD-08 dataset.The RFNet approach has effectiveness precision at 68.6%,surpassing the baseline method(YOLOv11)at 3.3%and archieve the minimal size(4.9 M)on the SCB dataset3.Finally,comparing it with other algorithms,it accurately detects student behavior in complex classroom environments results confirmed that RFNet is well-suited for real-time and efficiently recognizing classroom behaviors.
基金supported by the National Natural Science Foundation of China(Nos.71771082,71801091)Hunan Provincial Natural Science Foundation of China(Nos.2017JJ1012 and 2020JJ5377)
文摘Social responsibility investment(SRI)has attracted worldwide attention for its potential in promoting investment sustainability and stability.We developed a three-step framework by incorporating environmental,social,and governance(ESG)performance into portfolio optimization.In comparison to studies using weighted ESG rating scores,we constructed a data envelopment analysis(DEA)model with quadratic and cubic terms to enhance the evidence of two or more aspects,as well as the interaction between the environmental,social,and governance attributes.We then combined the ESG scores with financial indicators to select assets based on a cross-efficiency analysis.The portfolio optimization model incorporating ESG scores with selected assets was constructed to obtain a social responsibility investment strategy.To illustrate the effectiveness of the proposed approach,we applied it in the United States industrial stock market from 2005 to 2017.The empirical results show that the obtained SRI portfolio may be superior to traditional investment strategies in many aspects and may simultaneously achieve the consistency of investment and social values.
基金the National Institute of Food and Agriculture,US Department of Agriculture,Evans-Alien project number SCX-313-04-18.
文摘This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.
基金The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China(nos.21871025 and 21831001)the Recruitment Program of Global Experts(Young Talents),and the BIT Teli Young Fellow Program.
文摘Developing efficient catalysts and photosensitizers is crucial for the construction of effective photocatalytic H2-evolving systems.Here,we report the facile preparation of Coumarin-modified Ir(III)complexes(PS-2 and PS-3)and their utilization as chromophores to drive favorable photocatalytic H2 evolution using Ni-substituted polyoxometalate(Ni_(3)PW_(10))catalyst and triethanolamine(TEOA)as an electron donor.Compared with the commercially available unmodified Ir(III)complex(PS-1),both PS-2 and PS-3 displayed intensive absorption in the range of 400–550 nm with ε_(max) of 110,620 and 91,430 M^(−1) cm6(−1),respectively.Varying the substitutes on the bipyridine ligand affected their physicochemical properties and the corresponding photocatalytic activity dramatically.Under photocatalytic conditions,the quantity of H2 molecules generated by PS-2-and PS-3-containing systems were 13.1 and 2.1 times,respectively,that of the PS-1-containing system.When PS-2 was used as a photosensitizer,the highest turnover number(TON)of 19,739 was obtained versus Ni_(3)PW_(10) catalyst.Various spectroscopic and computational studies have revealed that factors such as strong and broad visible-light-absorbing ability,long-lived triplet state,suitable redox potential,opposed by using polyoxometalate(POM)catalyst,and large highest occupied molecular orbital(HOMO)–lowest unoccupied molecular orbital(LUMO)gap of PS-2 attributed to drastically enhanced photocatalytic activity.
