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| 1 | Prevalence, bacterial causes, and antimicrobial susceptibility profile of mastitis isolates from cows in large-scale dairy farms of Northern Ethiopia显示文摘 | Rgbe Haftu Habtamu Taddele Getachew Gugsa Shewit Kalayou | 2012 | Tropical Animal Health and Production2012，，7： | 1 |
| 2 | FedDiSC:A computation-efficient federated learning framework for power systems disturbance and cyber attack discrimination显示文摘With the growing concern about the security and privacy of smart grid systems,cyberattacks on critical power grid components,such as state estimation,have proven to be one of the top-priority cyber-related issues and have received significant attention in recent years.However,cyberattack detection in smart grids now faces new challenges,including privacy preservation and decentralized power zones with strategic data owners.To address these technical bottlenecks,this paper proposes a novel Federated Learning-based privacy-preserving and communication-efficient attack detection framework,known as FedDiSC,that enables Discrimination between power System disturbances and Cyberattacks.Specifically,we first propose a Federated Learning approach to enable Supervisory Control and Data Acquisition subsystems of decentralized power grid zones to collaboratively train an attack detection model without sharing sensitive power related data.Secondly,we put forward a representation learning-based Deep Auto-Encoder network to accurately detect power system and cybersecurity anomalies.Lastly,to adapt our proposed framework to the timeliness of real-world cyberattack detection in SGs,we leverage the use of a gradient privacy-preserving quantization scheme known as DP-SIGNSGD to improve its communication efficiency.Extensive simulations of the proposed framework on publicly available Industrial Control Systems datasets demonstrate that the proposed framework can achieve superior detection accuracy while preserving the privacy of sensitive power grid related information.Furthermore,we find that the gradient quantization scheme utilized improves communication efficiency by 40%when compared to a traditional federated learning approach without gradient quantization which suggests suitability in a real-world scenario. | Muhammad Akbar Husnoo Adnan Anwar Haftu Tasew Reda Nasser Hosseinzadeh Shama Naz Islam Abdun Naser Mahmood Robin Doss | 2023 | Energy and AI2023，14，4： | 0 |
| 3 | Data-driven Approach for State Prediction and Detection of False Data Injection Attacks in Smart Grid显示文摘In a smart grid,state estimation(SE)is a very important component of energy management system.Its main functions include system SE and detection of cyber anomalies.Recently,it has been shown that conventional SE techniques are vulnerable to false data injection(FDI)attack,which is a sophisticated new class of attacks on data integrity in smart grid.The main contribution of this paper is to propose a new FDI attack detection technique using a new data-driven SE model,which is different from the traditional weighted least square based SE model.This SE model has a number of unique advantages compared with traditional SE models.First,the prediction technique can better maintain the inherent temporal correlations among consecutive measurement vectors.Second,the proposed SE model can learn the actual power system states.Finally,this paper shows that this SE model can be effectively used to detect FDI attacks that otherwise remain stealthy to traditional SE-based bad data detectors.The proposed FDI attack detection technique is evaluated on a number of standard bus systems.The performance of state prediction and the accuracy of FDI attack detection are benchmarked against the state-ofthe-art techniques.Experimental results show that the proposed FDI attack detection technique has a higher detection rate compared with the existing techniques while reducing the false alarms significantly. | Haftu Tasew Reda Adnan Anwar Abdun Mahmood Naveen Chilamkurti | 2023 | Journal of Modern Power Systems and Clean Energy2023，11，2： | 0 |
| 4 | Factors that influence the implementation of sustainable land management practices by rural households in Tigrai region, Ethiopia显示文摘Background:Sustainable land management is considered as one of the useful approaches to combat the threat of various forms of land degradation in Ethiopia.Despite this,there is scant information regarding households’decision towards the implementation of sustainable land management practices.This paper,therefore,looks into the determinants for the continued use and choice of the sustainable land management practices by smallholder farmers and its productivity effect in three randomly chosen districts in Tigrai region,Ethiopia.The study uses data from household survey and key informant interviews.The paper employs a binary logit to analyze the determinants for the decision of continued use of sustainable land management practices,and a multivariate probit to analyze the simultaneous adoption decision of sustainable land management practices using cross sectional data collected from 230 randomly selected households.The impact of sustainable land management practices was also evaluated using propensity score matching.Results:Farming techniques,wealth status,agro-ecological variations,and plot level characteristics were found to be associated with the implementation decision of sustainable land management practices by rural households.Besides,institutional supports and access to basic infrastructures influenced the overall continued use of sustainable land management practices and the preference of households toward these practices.The study also finds that the value of crop production of sustainable land management users was on average 77–100%higher than that of nonusers.Conclusions:The results of the current study confirm that the implementation of various sustainable land management practices are influenced by farming technologies deployed by rural households,agro-ecological variations,plot characteristics,and institutional supports.The findings also affirm that most of the sustainable land management practices are complementary to one another,and implementing two or more sustainable land management practices on a given plot is highly associated with higher value of crop production.Such complementarity highlights that the productivity effect of a given sustainable land management practice is enhanced by the use of the other ones. | Haftu Etsay Teklay Negash Metkel Aregay | 2019 | Ecological Processes2019，8，1： | 0 |
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