In this paper, by a nonlinear procedure of a eigenvalue problem, we get a Bargmann system and prove it is a completely in tegrable system in the meanning of Liouville. By the way, the involutive solutio n of the repr...In this paper, by a nonlinear procedure of a eigenvalue problem, we get a Bargmann system and prove it is a completely in tegrable system in the meanning of Liouville. By the way, the involutive solutio n of the representation equation is given.展开更多
Northeast India has a good deposit of sub-bituminous tertiary coal. The northeast Indian coals have unusual physico-chemical characteristics such as high sulfur, volatile matter and vitrinite content, and low ash cont...Northeast India has a good deposit of sub-bituminous tertiary coal. The northeast Indian coals have unusual physico-chemical characteristics such as high sulfur, volatile matter and vitrinite content, and low ash content. In addition, many environmental sensitive organic and mineral bound elements such as Fe, Mg, Bi, AI, V, Cu, Cd, Ni, Pb, and Mn etc. remain enriched in these coals. Such characteristics are associated with more severe environmental impacts due to mining and its utilization in coal based industries. Environmental challenges include large scale landscape damage, soil erosion, loss of forest ecosystem and wildlife habitat, air, water and soil pollution. Several physical and chemical methods are reported in literature for the removal of mineral matter, total sulfur and different forms of sulfur from high sulfur coal in northeast India. This paper may help different researchers and stakeholders to understand current state of research in the field. Initiatives may be taken towards sustainable use of coal resources by adopting innovative clean technologies and by implementing effective control measures and regulatory policies.展开更多
Arsenic （As） is one of the most important elemental pollutants in groundwater and drinking water because it causes health problem of arsenicosis after consumption of drinking arsenic-rich water more than 5-10 years....Arsenic （As） is one of the most important elemental pollutants in groundwater and drinking water because it causes health problem of arsenicosis after consumption of drinking arsenic-rich water more than 5-10 years. Arsenic contamination of groundwater is an emerging issue in Mekong Basin including Cambodia, Vietnam, and Thailand. In Thailand, information about arsenic contamination in drinking water resources are quite rare due to that arsenic is not the main element in water qualification assay. The objective of this study is to determine groundwater quality and arsenic contamination in rural Mekong Basin, Ubon Ratchathani. Groundwater samples were collected from 20 different sampling points, between August 2009 and February 2010 in Amphoe Khemmarat, Ubon Ratchathani, Thailand. Physical and chemical characteristics of groundwater were determined. It was observed that the groundwater was 27.9-30.3 ~C, pH 5.7-6.9. The conductivity was 707-767 p.S.cm＂. Dissolved oxygen was 2.04-5.12 mg.L-1 and TDS was 352-384 mg.L~. The samples showed soft- to very hardness-water properties. In some area, few parameters like CI, Fe, Mn, and As exceeded the WHO guideline limits. This result represents basic information for quality of groundwater and the arsenic contamination in rural Mekong Basin, Ubon Ratchathani. Thus, it is probably useful for arsenic standard level assignment and public health authorities. Moreover, it also leads to establish research activity in treatment of arsenic-contaminated groundwater for different purposes展开更多
By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfully applied to many optimization problems that are difficult to deal with using traditional methods. At present, t...By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfully applied to many optimization problems that are difficult to deal with using traditional methods. At present, there are many well-implemented algorithms, such as particle swarm optimization, genetic algorithm, artificial bee colony algorithm, and ant colony optimization. These algorithms have already shown favorable performances. However, with the objects becoming increasingly complex, it is becoming gradually more difficult for these algorithms to meet human＇s demand in terms of accuracy and time. Designing a new algorithm to seek better solutions for optimization problems is becoming increasingly essential. Dolphins have many noteworthy biological characteristics and living habits such as echolocation, information exchanges, cooperation, and division of labor. Combining these biological characteristics and living habits with swarm intelligence and bringing them into optimization problems, we propose a brand new algorithm named the ‘dolphin swarm algorithm＇ in this paper. We also provide the definitions of the algorithm and specific descriptions of the four pivotal phases in the algorithm, which are the search phase, call phase, reception phase, and predation phase. Ten benchmark functions with different properties are tested using the dolphin swarm algorithm, particle swarm optimization, genetic algorithm, and artificial bee colony algorithm. The convergence rates and benchmark function results of these four algorithms are compared to testify the effect of the dolphin swarm algorithm. The results show that in most cases, the dolphin swarm algorithm performs better. The dolphin swarm algorithm possesses some great features, such as first-slow-then-fast convergence, periodic convergence, local-optimum-free, and no specific demand on benchmark functions. Moreover, the dolphin swarm algorithm is particularly appropriate to optimization problems, with more calls of fitness functions and fewer individuals.展开更多
The convective heat transfer coefficient and surface emissivity before and after flame occurrence on a wood specimen surface and the flame heat flux were estimated using the repulsive particle swarm optimization algor...The convective heat transfer coefficient and surface emissivity before and after flame occurrence on a wood specimen surface and the flame heat flux were estimated using the repulsive particle swarm optimization algorithm and cone heater test results. The cone heater specified in the ISO 5660 standards was used, and six cone heater heat fluxes were tested. Preservative-treated Douglas fir 21 mm in thickness was used as the wood specimen in the tests. This study confirmed that the surface temperature of the specimen, which was calculated using the convective heat transfer coefficient, surface emissivity and flame heat flux on the wood specimen by a repulsive particle swarm optimization algorithm, was consistent with the measured temperature. Considering the measurement errors in the surface temperature of the specimen, the applicability of the optimization method considered in this study was evaluated.展开更多
文摘In this paper, by a nonlinear procedure of a eigenvalue problem, we get a Bargmann system and prove it is a completely in tegrable system in the meanning of Liouville. By the way, the involutive solutio n of the representation equation is given.
文摘Northeast India has a good deposit of sub-bituminous tertiary coal. The northeast Indian coals have unusual physico-chemical characteristics such as high sulfur, volatile matter and vitrinite content, and low ash content. In addition, many environmental sensitive organic and mineral bound elements such as Fe, Mg, Bi, AI, V, Cu, Cd, Ni, Pb, and Mn etc. remain enriched in these coals. Such characteristics are associated with more severe environmental impacts due to mining and its utilization in coal based industries. Environmental challenges include large scale landscape damage, soil erosion, loss of forest ecosystem and wildlife habitat, air, water and soil pollution. Several physical and chemical methods are reported in literature for the removal of mineral matter, total sulfur and different forms of sulfur from high sulfur coal in northeast India. This paper may help different researchers and stakeholders to understand current state of research in the field. Initiatives may be taken towards sustainable use of coal resources by adopting innovative clean technologies and by implementing effective control measures and regulatory policies.
文摘Arsenic （As） is one of the most important elemental pollutants in groundwater and drinking water because it causes health problem of arsenicosis after consumption of drinking arsenic-rich water more than 5-10 years. Arsenic contamination of groundwater is an emerging issue in Mekong Basin including Cambodia, Vietnam, and Thailand. In Thailand, information about arsenic contamination in drinking water resources are quite rare due to that arsenic is not the main element in water qualification assay. The objective of this study is to determine groundwater quality and arsenic contamination in rural Mekong Basin, Ubon Ratchathani. Groundwater samples were collected from 20 different sampling points, between August 2009 and February 2010 in Amphoe Khemmarat, Ubon Ratchathani, Thailand. Physical and chemical characteristics of groundwater were determined. It was observed that the groundwater was 27.9-30.3 ~C, pH 5.7-6.9. The conductivity was 707-767 p.S.cm＂. Dissolved oxygen was 2.04-5.12 mg.L-1 and TDS was 352-384 mg.L~. The samples showed soft- to very hardness-water properties. In some area, few parameters like CI, Fe, Mn, and As exceeded the WHO guideline limits. This result represents basic information for quality of groundwater and the arsenic contamination in rural Mekong Basin, Ubon Ratchathani. Thus, it is probably useful for arsenic standard level assignment and public health authorities. Moreover, it also leads to establish research activity in treatment of arsenic-contaminated groundwater for different purposes
基金Project supported by the National Key Technology R&D Program of China(No.2014BAD10B02)
文摘By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfully applied to many optimization problems that are difficult to deal with using traditional methods. At present, there are many well-implemented algorithms, such as particle swarm optimization, genetic algorithm, artificial bee colony algorithm, and ant colony optimization. These algorithms have already shown favorable performances. However, with the objects becoming increasingly complex, it is becoming gradually more difficult for these algorithms to meet human＇s demand in terms of accuracy and time. Designing a new algorithm to seek better solutions for optimization problems is becoming increasingly essential. Dolphins have many noteworthy biological characteristics and living habits such as echolocation, information exchanges, cooperation, and division of labor. Combining these biological characteristics and living habits with swarm intelligence and bringing them into optimization problems, we propose a brand new algorithm named the ‘dolphin swarm algorithm＇ in this paper. We also provide the definitions of the algorithm and specific descriptions of the four pivotal phases in the algorithm, which are the search phase, call phase, reception phase, and predation phase. Ten benchmark functions with different properties are tested using the dolphin swarm algorithm, particle swarm optimization, genetic algorithm, and artificial bee colony algorithm. The convergence rates and benchmark function results of these four algorithms are compared to testify the effect of the dolphin swarm algorithm. The results show that in most cases, the dolphin swarm algorithm performs better. The dolphin swarm algorithm possesses some great features, such as first-slow-then-fast convergence, periodic convergence, local-optimum-free, and no specific demand on benchmark functions. Moreover, the dolphin swarm algorithm is particularly appropriate to optimization problems, with more calls of fitness functions and fewer individuals.
基金support from the research fund of the National Emergency Management Agency.(NEMA- Infra-2014-103)
文摘The convective heat transfer coefficient and surface emissivity before and after flame occurrence on a wood specimen surface and the flame heat flux were estimated using the repulsive particle swarm optimization algorithm and cone heater test results. The cone heater specified in the ISO 5660 standards was used, and six cone heater heat fluxes were tested. Preservative-treated Douglas fir 21 mm in thickness was used as the wood specimen in the tests. This study confirmed that the surface temperature of the specimen, which was calculated using the convective heat transfer coefficient, surface emissivity and flame heat flux on the wood specimen by a repulsive particle swarm optimization algorithm, was consistent with the measured temperature. Considering the measurement errors in the surface temperature of the specimen, the applicability of the optimization method considered in this study was evaluated.
