This study focuses on the metabasite rocks of the Nemba Complex of the Mayombe belt, an African segment of Araçuaï-West Congo Orogen (A-WCO) extending from the southwest of Gabon to the northwest of ...This study focuses on the metabasite rocks of the Nemba Complex of the Mayombe belt, an African segment of Araçuaï-West Congo Orogen (A-WCO) extending from the southwest of Gabon to the northwest of Angola. These metabasite rocks outcrops are in southwestern Congo along the Loukounga river. The Nemba complex is of Neoproterozoic age and represents the lower part of the west congolian Supergroup. The objective of this study is to constrain the geodynamic context of the Nemba complex from the petrology and geochemistry of the metabasites sampled in the Loukounga River. The observed rocks are composed of amphibolites, metagabbros, epidotites and greenschists and are affected by folding accompanied by flux schistosity and crenulation schistosity. Geochemical analyzes show that the rocks have a basic to ultrabasic chemical composition with SiO<sub>2</sub> contents between 41.85% and 58.23%. The geochemical composition of the major and traces elements shows that the rocks are basalts, basaltic andesites and andesites. The magma shows enrichment in LREE, LILE and depletion in HREE and HFSE. The multielement spectra show negative anomalies in Nb-Ta, Ti and a relatively low Nb/La ratio which characterize a lithospheric source contaminated by continental crust. Traces elements discrimination plots show that Loukounga metabasites are emplaced in intraplate geodynamic context like that associated with the basalts of the trap-types continental shelves and are possibly derived from mantle plumes contemporaneous with or slightly prior to magmatism.展开更多
Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view ...Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.展开更多
This research addresses the performance challenges of ontology-based context-aware and activity recognition techniques in complex environments and abnormal activities,and proposes an optimized ontology framework to im...This research addresses the performance challenges of ontology-based context-aware and activity recognition techniques in complex environments and abnormal activities,and proposes an optimized ontology framework to improve recognition accuracy and computational efficiency.The method in this paper adopts the event sequence segmentation technique,combines location awareness with time interval reasoning,and improves human activity recognition through ontology reasoning.Compared with the existing methods,the framework performs better when dealing with uncertain data and complex scenes,and the experimental results show that its recognition accuracy is improved by 15.6%and processing time is reduced by 22.4%.In addition,it is found that with the increase of context complexity,the traditional ontology inferencemodel has limitations in abnormal behavior recognition,especially in the case of high data redundancy,which tends to lead to a decrease in recognition accuracy.This study effectively mitigates this problem by optimizing the ontology matching algorithm and combining parallel computing and deep learning techniques to enhance the activity recognition capability in complex environments.展开更多
文摘This study focuses on the metabasite rocks of the Nemba Complex of the Mayombe belt, an African segment of Araçuaï-West Congo Orogen (A-WCO) extending from the southwest of Gabon to the northwest of Angola. These metabasite rocks outcrops are in southwestern Congo along the Loukounga river. The Nemba complex is of Neoproterozoic age and represents the lower part of the west congolian Supergroup. The objective of this study is to constrain the geodynamic context of the Nemba complex from the petrology and geochemistry of the metabasites sampled in the Loukounga River. The observed rocks are composed of amphibolites, metagabbros, epidotites and greenschists and are affected by folding accompanied by flux schistosity and crenulation schistosity. Geochemical analyzes show that the rocks have a basic to ultrabasic chemical composition with SiO<sub>2</sub> contents between 41.85% and 58.23%. The geochemical composition of the major and traces elements shows that the rocks are basalts, basaltic andesites and andesites. The magma shows enrichment in LREE, LILE and depletion in HREE and HFSE. The multielement spectra show negative anomalies in Nb-Ta, Ti and a relatively low Nb/La ratio which characterize a lithospheric source contaminated by continental crust. Traces elements discrimination plots show that Loukounga metabasites are emplaced in intraplate geodynamic context like that associated with the basalts of the trap-types continental shelves and are possibly derived from mantle plumes contemporaneous with or slightly prior to magmatism.
文摘Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.
基金supported by the BK21 FOUR program of the National Research Foundation of Korea funded by the Ministry of Education(NRF5199991014091)Seok-Won Lee’s work was supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)under the Artificial Intelligence Convergence Innovation Human Resources Development(IITP-2024-RS-2023-00255968)grant funded by the Korea government(MSIT).
文摘This research addresses the performance challenges of ontology-based context-aware and activity recognition techniques in complex environments and abnormal activities,and proposes an optimized ontology framework to improve recognition accuracy and computational efficiency.The method in this paper adopts the event sequence segmentation technique,combines location awareness with time interval reasoning,and improves human activity recognition through ontology reasoning.Compared with the existing methods,the framework performs better when dealing with uncertain data and complex scenes,and the experimental results show that its recognition accuracy is improved by 15.6%and processing time is reduced by 22.4%.In addition,it is found that with the increase of context complexity,the traditional ontology inferencemodel has limitations in abnormal behavior recognition,especially in the case of high data redundancy,which tends to lead to a decrease in recognition accuracy.This study effectively mitigates this problem by optimizing the ontology matching algorithm and combining parallel computing and deep learning techniques to enhance the activity recognition capability in complex environments.
