A study was conducted to determine the influence of forest road on breeding of tits in artificial nest boxes in deciduous, coniferous and mixed forests in the Gwanak Arboretum （37° 25′ 05＂ N, 126° 56′ 85...A study was conducted to determine the influence of forest road on breeding of tits in artificial nest boxes in deciduous, coniferous and mixed forests in the Gwanak Arboretum （37° 25′ 05＂ N, 126° 56′ 85＂ E） of Seoul National University, Anyang, Korea from November 2002 to June 2003. Three tits species, varied tit （Parus varius）, marsh tit （P. palustris） and great tit （P. major）, breeding in artificial t nest boxes were investigated on number of breeding pairs, cultch size, and egg measurement. Resuls showed that the breeding pairs of varied tit was more in 75-150 m area than in 0-75m area from forest road for all the three study sites, and the clutch size and egg measurements （weight, Major axis and Minor axis） of varied tit was also higher in the area of 75-150 m than in the area of 0-75 m, while no differences in number of breeding pairs and clutch size were found for marsh tit and great tit between the two areas. Egg measurement of great tit was also higher in forest interior area than in forest edge area. It is concluded that varied tit were most significantly influenced by forest road, followed by great tit, whereas marsh tit were not influenced by forest road. Artificial nest box is roved to be good for cavity nester in disturbed areas by human activities. Supply of artificial nest can help population protection and management of bird species.展开更多
In this study, we examined the use of artificial nest boxes by Siberian flying squirrels (Pteromys volans) in three coniferous and mixed forests in Gangwon Province, South Korea. Six hundred and twelve boxes with diff...In this study, we examined the use of artificial nest boxes by Siberian flying squirrels (Pteromys volans) in three coniferous and mixed forests in Gangwon Province, South Korea. Six hundred and twelve boxes with different sized entry holes (ranging from 3 to 7 cm in diameter) were placed in the forests between 2004 and 2009. Pteromys volans used nine boxes in the coniferous forests and two boxes in the mixed forests. The squirrels only used boxes with entrance holes measuring 3.5, 4, and 5 cm in diameter, showing a strong and moderate preference for boxes with 5 and 4-cm holes, respectively, and a strong avoidance for boxes with 3- and 7-cm holes. Therefore, we suggest placing artificial nest boxes with entrance holes 5 cm in diameter to encourage breeding activity. Most nests made in the artificial boxes were composed of fibrous materials from woody vines. We recommend placing artificial nest boxes with holes of 5-cm diameter in coniferous forests, which support dense populations of P. volans, to survey whether this approach would positively affect the breeding habits and population maintenance of this species.展开更多
Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes th...Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes that simultaneously meet with multiple cryptographic criteria such as bijection,non-linearity,strict avalanche criterion（SAC）,bits independence criterion（BIC）,differential probability（DP） and linear probability（LP）.To deal with this problem,a chaotic S-box based on the artificial bee colony algorithm（CSABC） is designed.It uses the S-boxes generated by the six-dimensional compound hyperchaotic map as the initial individuals and employs ABC to improve their performance.In addition,it considers the nonlinearity and differential uniformity as the fitness functions.A series of experiments have been conducted to compare multiple cryptographic criteria of this algorithm with other algorithms.Simulation results show that the new algorithm has cryptographically strong S-box while meeting multiple cryptographic criteria.展开更多
Organic matters（OMs） and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the...Organic matters（OMs） and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol（EtO H）-mediated As（Ⅲ） adsorption onto Zn-loaded pinecone（PC） biochar through batch experiments conducted under Box–Behnken design. The effect of EtO H on As（Ⅲ） adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtO H and pH on As（Ⅲ） adsorption,whereas neural network revealed the stronger influence of Et OH（64.5%） followed by pH（20.75%）and As（Ⅲ） concentration（14.75%） on the adsorption phenomena. Besides, the interaction among process variables indicated that Et OH enhances As（Ⅲ） adsorption over a pH range of2 to 7, possibly due to facilitation of ligand–metal（Zn） binding complexation mechanism.Eventually, hybrid response surface model–genetic algorithm（RSM–GA） approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As（Ⅲ）（10.47 μg/g） is facilitated at 30.22 mg C/L of Et OH with initial As（Ⅲ） concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As（Ⅲ） species in the presence of OM.展开更多
In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were in...In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were investigated. The experiments were carried out based on a 3-level, 4-variable Box–Behnken design. The amount of zinc was considered as a function of four independent variables, namely irradiation power, irradiation time, nitric acid concentration, and temperature. The RSM results showed the quadratic polynomial model can be used to describe the relationship between the various factors and the response. Using the ANN analysis, the optimal configuration of the ANN model was found to be 4-10-1. After predicting the model using RSM and ANN, two methodologies were then compared for their predictive capabilities. The results showed that the ANN model is much more accurate in prediction as compared to the RSM.展开更多
Artificial nest boxes are placed to attract birds to nest and breed in a specific location,and they are widely used in avian ecology research and in the attraction of insectivorous birds.There is evidence that artific...Artificial nest boxes are placed to attract birds to nest and breed in a specific location,and they are widely used in avian ecology research and in the attraction of insectivorous birds.There is evidence that artificial nest boxes can adversely affect breeding fitness but no great focus has been placed on this issue by researchers.Therefore,we retrieved 321 research papers regarding artificial nest boxes published from 2003 to 2022 and used the'Biblioshiny'program to extract and integrate keywords;we then summarized the adverse effects of artificial nest boxes on avian breeding success.The studies highlighted many drawbacks and misuses in the designing and placement of nest boxes;furthermore,bird attraction was decreased by their inappropriate selection,thus reducing breeding success.Regarding nest box production,there were shortcomings in the construction material,color,smell,and structural design of the boxes used.Nest boxes were also placed at inappropriate densities,locations,orientations,heights,and managed incorrectly.Finally,we propose suggestions for more efficient and safer artificial nest boxes for future use in avian ecology research and bird conservation.展开更多
A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU w...A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU was developed for Pakistani crudes from Zamzama and Kunnar fields.A hybrid methodology based on the integration of Taguchi method and genetic algorithm(GA)was employed to estimate the optimal cut point temperature for various sets of process variables.Optimised datasets were utilised to develop an artificial neural networks(ANN)model for the prediction of optimum values of cut points.The ANN model was then used to replace the hybrid framework of the Taguchi method and the GA.The integration of the ANN and FP model makes it a grey-box(GB)model.For the case of Zamama crude,the GB model helped in the decrease of up to 38.93%in energy required per kilo barrel of diesel and an 8.2%increase in diesel production compared to the stand-alone FP model under uncertainty.Similarly,for Kunnar crude,up to 18.87%decrease in energy required per kilo barrel of diesel and a 33.96%increase in diesel production was observed in comparison to the stand-alone FP model.展开更多
The role of the high mobility group box 1 （HMGB-1） in acute hepatic failure and the effect of artificial liver support system treatment on HMGB-1 level were investigated. Pig models of acute hepatic failure were ind...The role of the high mobility group box 1 （HMGB-1） in acute hepatic failure and the effect of artificial liver support system treatment on HMGB-1 level were investigated. Pig models of acute hepatic failure were induced by D-galactosamine and randomly divided into two groups with or without artificial liver support system treatment. Tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β） levels were detected by the enzyme linked immunosorbent assay （ELISA）, the expression of HMGB-1 by Western blot, and serum levels of HMGB-1, liver function and hepatic pathology were observed after artificial liver support system treatment. The levels of TNF-α and IL-1β were increased and reached the peak at 24th h in the acute hepatic failure group, then quickly decreased. The serum level of HMGB-1 was increased at 24th h in the acute hepatic failure group and reached the peak at 48th h, then kept a stable high level. Significant liver injury appeared at 24th h and was continuously getting worse in the pig models of acute hepatic failure. In contrast, the liver injury was significantly alleviated and serum level of HMGB-1 was significantly decreased in the group treated with artificial liver support system （P〈0.05）. It was suggested that HMGB-1 may participate in the inflammatory response and liver injury in the late stage of the acute liver failure. Artificial liver support system treatment can reduce serum HMGB-1 level and relieve liver pathological damage.展开更多
Some experimental results which support a new techniquefor detecting comb box assemblies are introduced.Therole which artificial intelligence(A.I.)can play in ex-tending this technique to real-time applications on com...Some experimental results which support a new techniquefor detecting comb box assemblies are introduced.Therole which artificial intelligence(A.I.)can play in ex-tending this technique to real-time applications on combbox of gill machine is also investigated.展开更多
Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron...Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron neural network, where the underlying software fault count data are transformed to the Gaussian data, by means of the well-known Box-Cox power transformation. More specially, we investigate the long-term behavior of software fault counts by the neural network, and perform the multi-stage look ahead prediction of the cumulative number of software faults detected in the future software testing. In numerical examples with two actual software fault data sets, we compare our neural network approach with the existing software reliability growth models based on nonhomogeneous Poisson process, in terms of predictive performance with average relative error, and show that the data transformation employed in this paper leads to an improvement in prediction accuracy.展开更多
文摘A study was conducted to determine the influence of forest road on breeding of tits in artificial nest boxes in deciduous, coniferous and mixed forests in the Gwanak Arboretum （37° 25′ 05＂ N, 126° 56′ 85＂ E） of Seoul National University, Anyang, Korea from November 2002 to June 2003. Three tits species, varied tit （Parus varius）, marsh tit （P. palustris） and great tit （P. major）, breeding in artificial t nest boxes were investigated on number of breeding pairs, cultch size, and egg measurement. Resuls showed that the breeding pairs of varied tit was more in 75-150 m area than in 0-75m area from forest road for all the three study sites, and the clutch size and egg measurements （weight, Major axis and Minor axis） of varied tit was also higher in the area of 75-150 m than in the area of 0-75 m, while no differences in number of breeding pairs and clutch size were found for marsh tit and great tit between the two areas. Egg measurement of great tit was also higher in forest interior area than in forest edge area. It is concluded that varied tit were most significantly influenced by forest road, followed by great tit, whereas marsh tit were not influenced by forest road. Artificial nest box is roved to be good for cavity nester in disturbed areas by human activities. Supply of artificial nest can help population protection and management of bird species.
基金supported by LG Evergreen Foundation,Republic of Korea
文摘In this study, we examined the use of artificial nest boxes by Siberian flying squirrels (Pteromys volans) in three coniferous and mixed forests in Gangwon Province, South Korea. Six hundred and twelve boxes with different sized entry holes (ranging from 3 to 7 cm in diameter) were placed in the forests between 2004 and 2009. Pteromys volans used nine boxes in the coniferous forests and two boxes in the mixed forests. The squirrels only used boxes with entrance holes measuring 3.5, 4, and 5 cm in diameter, showing a strong and moderate preference for boxes with 5 and 4-cm holes, respectively, and a strong avoidance for boxes with 3- and 7-cm holes. Therefore, we suggest placing artificial nest boxes with entrance holes 5 cm in diameter to encourage breeding activity. Most nests made in the artificial boxes were composed of fibrous materials from woody vines. We recommend placing artificial nest boxes with holes of 5-cm diameter in coniferous forests, which support dense populations of P. volans, to survey whether this approach would positively affect the breeding habits and population maintenance of this species.
基金supported by the National Natural Science Foundation of China(6060309260975042)
文摘Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes that simultaneously meet with multiple cryptographic criteria such as bijection,non-linearity,strict avalanche criterion（SAC）,bits independence criterion（BIC）,differential probability（DP） and linear probability（LP）.To deal with this problem,a chaotic S-box based on the artificial bee colony algorithm（CSABC） is designed.It uses the S-boxes generated by the six-dimensional compound hyperchaotic map as the initial individuals and employs ABC to improve their performance.In addition,it considers the nonlinearity and differential uniformity as the fitness functions.A series of experiments have been conducted to compare multiple cryptographic criteria of this algorithm with other algorithms.Simulation results show that the new algorithm has cryptographically strong S-box while meeting multiple cryptographic criteria.
基金supported by the research funds from the University of Ulsan in South Korea during the financial year 2012–2013
文摘Organic matters（OMs） and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol（EtO H）-mediated As（Ⅲ） adsorption onto Zn-loaded pinecone（PC） biochar through batch experiments conducted under Box–Behnken design. The effect of EtO H on As（Ⅲ） adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtO H and pH on As（Ⅲ） adsorption,whereas neural network revealed the stronger influence of Et OH（64.5%） followed by pH（20.75%）and As（Ⅲ） concentration（14.75%） on the adsorption phenomena. Besides, the interaction among process variables indicated that Et OH enhances As（Ⅲ） adsorption over a pH range of2 to 7, possibly due to facilitation of ligand–metal（Zn） binding complexation mechanism.Eventually, hybrid response surface model–genetic algorithm（RSM–GA） approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As（Ⅲ）（10.47 μg/g） is facilitated at 30.22 mg C/L of Et OH with initial As（Ⅲ） concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As（Ⅲ） species in the presence of OM.
文摘In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were investigated. The experiments were carried out based on a 3-level, 4-variable Box–Behnken design. The amount of zinc was considered as a function of four independent variables, namely irradiation power, irradiation time, nitric acid concentration, and temperature. The RSM results showed the quadratic polynomial model can be used to describe the relationship between the various factors and the response. Using the ANN analysis, the optimal configuration of the ANN model was found to be 4-10-1. After predicting the model using RSM and ANN, two methodologies were then compared for their predictive capabilities. The results showed that the ANN model is much more accurate in prediction as compared to the RSM.
基金supported by the National Natural Science Foundation of China(Grant No.32170485,31501867)the Fundamental Research Funds for the Central Universities(Grant No.2572022BE02)。
文摘Artificial nest boxes are placed to attract birds to nest and breed in a specific location,and they are widely used in avian ecology research and in the attraction of insectivorous birds.There is evidence that artificial nest boxes can adversely affect breeding fitness but no great focus has been placed on this issue by researchers.Therefore,we retrieved 321 research papers regarding artificial nest boxes published from 2003 to 2022 and used the'Biblioshiny'program to extract and integrate keywords;we then summarized the adverse effects of artificial nest boxes on avian breeding success.The studies highlighted many drawbacks and misuses in the designing and placement of nest boxes;furthermore,bird attraction was decreased by their inappropriate selection,thus reducing breeding success.Regarding nest box production,there were shortcomings in the construction material,color,smell,and structural design of the boxes used.Nest boxes were also placed at inappropriate densities,locations,orientations,heights,and managed incorrectly.Finally,we propose suggestions for more efficient and safer artificial nest boxes for future use in avian ecology research and bird conservation.
基金Higher Education Commission,Pakistan,under the National Research Program for Universities Project,Grant/Award Number:NBU-FPEJ-2024-1243-02。
文摘A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU was developed for Pakistani crudes from Zamzama and Kunnar fields.A hybrid methodology based on the integration of Taguchi method and genetic algorithm(GA)was employed to estimate the optimal cut point temperature for various sets of process variables.Optimised datasets were utilised to develop an artificial neural networks(ANN)model for the prediction of optimum values of cut points.The ANN model was then used to replace the hybrid framework of the Taguchi method and the GA.The integration of the ANN and FP model makes it a grey-box(GB)model.For the case of Zamama crude,the GB model helped in the decrease of up to 38.93%in energy required per kilo barrel of diesel and an 8.2%increase in diesel production compared to the stand-alone FP model under uncertainty.Similarly,for Kunnar crude,up to 18.87%decrease in energy required per kilo barrel of diesel and a 33.96%increase in diesel production was observed in comparison to the stand-alone FP model.
文摘The role of the high mobility group box 1 （HMGB-1） in acute hepatic failure and the effect of artificial liver support system treatment on HMGB-1 level were investigated. Pig models of acute hepatic failure were induced by D-galactosamine and randomly divided into two groups with or without artificial liver support system treatment. Tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β） levels were detected by the enzyme linked immunosorbent assay （ELISA）, the expression of HMGB-1 by Western blot, and serum levels of HMGB-1, liver function and hepatic pathology were observed after artificial liver support system treatment. The levels of TNF-α and IL-1β were increased and reached the peak at 24th h in the acute hepatic failure group, then quickly decreased. The serum level of HMGB-1 was increased at 24th h in the acute hepatic failure group and reached the peak at 48th h, then kept a stable high level. Significant liver injury appeared at 24th h and was continuously getting worse in the pig models of acute hepatic failure. In contrast, the liver injury was significantly alleviated and serum level of HMGB-1 was significantly decreased in the group treated with artificial liver support system （P〈0.05）. It was suggested that HMGB-1 may participate in the inflammatory response and liver injury in the late stage of the acute liver failure. Artificial liver support system treatment can reduce serum HMGB-1 level and relieve liver pathological damage.
文摘Some experimental results which support a new techniquefor detecting comb box assemblies are introduced.Therole which artificial intelligence(A.I.)can play in ex-tending this technique to real-time applications on combbox of gill machine is also investigated.
文摘Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron neural network, where the underlying software fault count data are transformed to the Gaussian data, by means of the well-known Box-Cox power transformation. More specially, we investigate the long-term behavior of software fault counts by the neural network, and perform the multi-stage look ahead prediction of the cumulative number of software faults detected in the future software testing. In numerical examples with two actual software fault data sets, we compare our neural network approach with the existing software reliability growth models based on nonhomogeneous Poisson process, in terms of predictive performance with average relative error, and show that the data transformation employed in this paper leads to an improvement in prediction accuracy.
