Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart d...Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.展开更多
The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a cri...The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a critical review of six selected frameworks of community resilience building operationalized in Bangladesh over the span of years. In other words, this study aims to contribute to the understanding of resilience through a systematic analysis of the dimensions and indicators of community resilience frameworks. The analysis shows that comprehensive and effective community resilience frameworks should incorporate the missing components linked to fundamental elements of good governance, economic growth, environmental sustainability, social transformation, and capacity development. The paper concludes by highlighting a few other areas of grave concern that need more appropriate attention, considering the severe threats posed by climate change and natural disasters in line with sustainable development goals. Finally, this study recommends further research regarding the effectiveness of these frameworks in different climatic and disaster contexts that can lead the concept into a new dimension of community resilience and sustainability.展开更多
In recent decades,intelligent transportation systems(ITS)have improved drivers’safety and have shared information(such as traffic congestion and accidents)in a very efficient way.However,the privacy of vehicles and t...In recent decades,intelligent transportation systems(ITS)have improved drivers’safety and have shared information(such as traffic congestion and accidents)in a very efficient way.However,the privacy of vehicles and the security of event information is a major concern.The problem of secure sharing of event information without compromising the trusted third party(TTP)and data storage is the main issue in ITS.Blockchain technologies can resolve this problem.A work has been published on blockchain-based protocol for secure sharing of events and authentication of vehicles.This protocol addresses the issue of the safe storing of event information.However,authentication of vehicles solely depends on the cloud server.As a result,their scheme utilizes the notion of partially decentralized architecture.This paper proposes a novel decentralized architecture for the vehicular ad-hoc network(VANET)without the cloud server.This work also presents a protocol for securing event information and vehicle authentication using the blockchain mechanism.In this protocol,the registered user accesses the event information securely from the interplanetary file system(IPFS).We incorporate the IPFS,along with blockchain,to store the information in a fully distributed manner.The proposed protocol is compared with the state-of-the-art.The comparison provides desirable security at a reasonable cost.The evaluation of the proposed smart contract in terms of cost(GAS)is also discussed.展开更多
Biochar has potentials for soil fertility improvement, climate change mitigation and environmental reclamation, and charred biomass can be deliberately incorporated into soil for long-term carbon stabilization and soi...Biochar has potentials for soil fertility improvement, climate change mitigation and environmental reclamation, and charred biomass can be deliberately incorporated into soil for long-term carbon stabilization and soil amendment. Many different methods have been used for biochar production ranging from laboratory to industrial scales. However, in countryside of developing countries, biomass is generally used for cooking but not charred. Biochar production techniques at farmer scale have remained poorly developed. We developed and tested biochar production kilns for farmers with a dimension of 50.8 cm × 38.1 cm （height × diameter）, using three different setups for optimizing oxygen （02） limitation and syngas circulation： airtight with no syngas circulation （Model I）, semi-airtight with external syngas circulation （Model II） and semi-airtight with internal syngas circulation （Model III）. A comparative assessment of these biochar production kiln models was made considering biochar pyrolysis time, fuel to biomass ratio, biochar to feedstock ratio and thermogravimetric index （TGI）. Among the models, the best quality biochar （TGI ---- 0.15） was obtained from Model I kiln taking the longest time for pyrolysis （12.5 h） and the highest amount of fuel wood （1.22 kg kg-1 biomass）. Model III kiln produced comparatively good quality biochar （TGI = 0.11）, but with less fuel wood requirement （0.33 kg kg-1 biomass） and shorter pyrolysis time （8.5 h）. We also tested Model III kiln in a three times larger size under two situations （steel kiln and pit kiln）. The biochar to feedstock ratio （0.38） and quality （TGI =0.14） increased slightly for the larger kilns. Quality of biochar was found to be mainly related to pyrolysis time. The costs for the biochar stove and pit kiln were US$ 65-77, while it was US$ 154 for the large size steel kiln. Model III kiln can potentially be used for both cooking and biochar production at farmer scale.展开更多
基金supported by the Competitive Research Fund of the University of Aizu,Japan(Grant No.P-13).
文摘Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.
文摘The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a critical review of six selected frameworks of community resilience building operationalized in Bangladesh over the span of years. In other words, this study aims to contribute to the understanding of resilience through a systematic analysis of the dimensions and indicators of community resilience frameworks. The analysis shows that comprehensive and effective community resilience frameworks should incorporate the missing components linked to fundamental elements of good governance, economic growth, environmental sustainability, social transformation, and capacity development. The paper concludes by highlighting a few other areas of grave concern that need more appropriate attention, considering the severe threats posed by climate change and natural disasters in line with sustainable development goals. Finally, this study recommends further research regarding the effectiveness of these frameworks in different climatic and disaster contexts that can lead the concept into a new dimension of community resilience and sustainability.
文摘In recent decades,intelligent transportation systems(ITS)have improved drivers’safety and have shared information(such as traffic congestion and accidents)in a very efficient way.However,the privacy of vehicles and the security of event information is a major concern.The problem of secure sharing of event information without compromising the trusted third party(TTP)and data storage is the main issue in ITS.Blockchain technologies can resolve this problem.A work has been published on blockchain-based protocol for secure sharing of events and authentication of vehicles.This protocol addresses the issue of the safe storing of event information.However,authentication of vehicles solely depends on the cloud server.As a result,their scheme utilizes the notion of partially decentralized architecture.This paper proposes a novel decentralized architecture for the vehicular ad-hoc network(VANET)without the cloud server.This work also presents a protocol for securing event information and vehicle authentication using the blockchain mechanism.In this protocol,the registered user accesses the event information securely from the interplanetary file system(IPFS).We incorporate the IPFS,along with blockchain,to store the information in a fully distributed manner.The proposed protocol is compared with the state-of-the-art.The comparison provides desirable security at a reasonable cost.The evaluation of the proposed smart contract in terms of cost(GAS)is also discussed.
基金supported by Patuakhali Science and Technology University (PSTU),Bangladesh
文摘Biochar has potentials for soil fertility improvement, climate change mitigation and environmental reclamation, and charred biomass can be deliberately incorporated into soil for long-term carbon stabilization and soil amendment. Many different methods have been used for biochar production ranging from laboratory to industrial scales. However, in countryside of developing countries, biomass is generally used for cooking but not charred. Biochar production techniques at farmer scale have remained poorly developed. We developed and tested biochar production kilns for farmers with a dimension of 50.8 cm × 38.1 cm （height × diameter）, using three different setups for optimizing oxygen （02） limitation and syngas circulation： airtight with no syngas circulation （Model I）, semi-airtight with external syngas circulation （Model II） and semi-airtight with internal syngas circulation （Model III）. A comparative assessment of these biochar production kiln models was made considering biochar pyrolysis time, fuel to biomass ratio, biochar to feedstock ratio and thermogravimetric index （TGI）. Among the models, the best quality biochar （TGI ---- 0.15） was obtained from Model I kiln taking the longest time for pyrolysis （12.5 h） and the highest amount of fuel wood （1.22 kg kg-1 biomass）. Model III kiln produced comparatively good quality biochar （TGI = 0.11）, but with less fuel wood requirement （0.33 kg kg-1 biomass） and shorter pyrolysis time （8.5 h）. We also tested Model III kiln in a three times larger size under two situations （steel kiln and pit kiln）. The biochar to feedstock ratio （0.38） and quality （TGI =0.14） increased slightly for the larger kilns. Quality of biochar was found to be mainly related to pyrolysis time. The costs for the biochar stove and pit kiln were US$ 65-77, while it was US$ 154 for the large size steel kiln. Model III kiln can potentially be used for both cooking and biochar production at farmer scale.
