Search results for "C.1.4"

showing 4 items of 14 documents

Semi-supervised deep learning-driven anomaly detection schemes for cyber-attack detection in smart grids

2022

Modern power systems are continuously exposed to malicious cyber-attacks. Analyzing industrial control system (ICS) traffic data plays a central role in detecting and defending against cyber-attacks. Detection approaches based on system modeling require effectively modeling the complex behavior of the critical infrastructures, which remains a challenge, especially for large-scale systems. Alternatively, data-driven approaches which rely on data collected from the inspected system have become appealing due to the availability of big data that supports machine learning methods to achieve outstanding performance. This chapter presents an enhanced cyber-attack detection strategy using unlabeled…

Semi-supervised methods[SPI] Engineering Sciences [physics]Deep learningAnomaly detectionCyber-attack detectionProtocol IEC 104
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Practices in research, surveillance and control of neglected tropical diseases by One Health approaches: A survey targeting scientists from French-sp…

2021

One health (OH) approaches have increasingly been used in the last decade in the fight against zoonotic neglected tropical diseases (NTDs). However, descriptions of such collaborations between the human, animal and environmental health sectors are still limited for French-speaking tropical countries. The objective of the current survey was to explore the diversity of OH experiences applied to research, surveillance and control of NTDs by scientists from French-speaking countries, and discuss their constraints and benefits. Six zoonotic NTDs were targeted: echinococcoses, trypanosomiases, leishmaniases, rabies, Taenia solium cysticercosis and leptospiroses. Invitations to fill in an online q…

http://aims.fao.org/aos/agrovoc/c_8081RC955-962Psychological interventionSocial Scienceshttp://aims.fao.org/aos/agrovoc/c_431Computer-assisted web interviewingPolitical Aspects of HealthGlobal HealthSanté publique0302 clinical medicineMedical ConditionsArctic medicine. Tropical medicineSurveys and QuestionnairesPublic and Occupational Healthhttp://aims.fao.org/aos/agrovoc/c_6970media_commonMammalsSanté animaleNeglected DiseasesEukaryota3. Good healthÉpidémiologie[SDV] Life Sciences [q-bio]http://aims.fao.org/aos/agrovoc/c_1790medicine.drug_formulation_ingredientOne Healthhttp://aims.fao.org/aos/agrovoc/c_2085Veterinary Diseases[SDE]Environmental SciencesPublic aspects of medicinehttp://aims.fao.org/aos/agrovoc/c_4027http://aims.fao.org/aos/agrovoc/c_8068http://aims.fao.org/aos/agrovoc/c_8500medicine.medical_specialtyRabiesmedia_common.quotation_subjectPolitical ScienceLeptospiroseRage03 medical and health sciencesPolitical scienceTaenia soliumhttp://aims.fao.org/aos/agrovoc/c_3081HumansSurveillance épidémiologiquehttp://aims.fao.org/aos/agrovoc/c_8530Survey ResearchPublic Health Environmental and Occupational HealthOrganismsBiology and Life SciencesTropical Diseaseshttp://aims.fao.org/aos/agrovoc/c_7558http://aims.fao.org/aos/agrovoc/c_6349http://aims.fao.org/aos/agrovoc/c_4281Veterinary ScienceDiversity (politics)[SDE] Environmental SciencesViral DiseasesBiomedical Researchhttp://aims.fao.org/aos/agrovoc/c_2615[SDV]Life Sciences [q-bio]http://aims.fao.org/aos/agrovoc/c_870SurveysL73 - Maladies des animauxhttp://aims.fao.org/aos/agrovoc/c_875http://aims.fao.org/aos/agrovoc/c_16411http://aims.fao.org/aos/agrovoc/c_7988http://aims.fao.org/aos/agrovoc/c_6416ZoonosesTrypanosomoseMedicine and Health Sciences030212 general & internal medicinehttp://aims.fao.org/aos/agrovoc/c_3423http://aims.fao.org/aos/agrovoc/c_5164http://aims.fao.org/aos/agrovoc/c_4510http://aims.fao.org/aos/agrovoc/c_16415EchinococcoseInfectious DiseasesResearch DesignS50 - Santé humaineVertebrateshttp://aims.fao.org/aos/agrovoc/c_7979Neglected tropical diseasesRA1-1270Zone tropicaleResearch ArticleNeglected Tropical Diseaseszoonosehttp://aims.fao.org/aos/agrovoc/c_28665030231 tropical medicineMEDLINEResearch and Analysis Methodshttp://aims.fao.org/aos/agrovoc/c_259http://aims.fao.org/aos/agrovoc/c_35197DogsEnvironmental healthTropical MedicinemedicineLeishmanioseAnimalsCysticercosehttp://aims.fao.org/aos/agrovoc/c_5181Enquête pathologique[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologieTropical medicineAmniotes[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieZoology
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Report of the Scientific Committee of the Spanish Agency for Food Safety and Nutrition (AESAN) on the assessment of olive oil by its nutritional char…

2021

* This record is given in both English and Spanish. The Nutri-Score front-of-pack nutritional labelling system uses a code of letters and colours to inform consumers about the nutritional quality of foods and drinks. However, currently this system does not cover all the positive aspects of foods that possess a specific nutritional quality within the Mediterranean diet, as in the case of olive oil and extra-virgin olive oil. The AESAN Scientific Committee has suggested different possibilities for a more accurate assessment of olive oil and especially virgin olive oil, in the Nutri-Score front-of-pack labelling system, taking into consideration those compounds that are beneficial to the consu…

http://id.agrisemantics.org/gacs/C11447digestive oral and skin physiologyNutri-ScoreLabellingVirgin olive oilhttp://id.agrisemantics.org/gacs/C5160Olive oil
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Feromagnētiskas nanodaļiņas un to pielietojums mīkstu materiālu (dihidropiridīna tipa lipīdu organiski savienojumi, polimēri) funkcionalizācijai

2014

Elektroniskā versija nesatur pielikumus

magnētiskais šķidrumsmagnetic fluidelasticity of membraneĶīmija ķīmijas tehnoloģijas un biotehnoloģijakatjonais 14-dihidropiridīna atvasinājumsmembrānas elastībamaghemite and magnetite nanoparticlesĶīmijaChemistrymikrokonvekcijadzelzs oksīda nanodaļiņasmicroconvectioncationic 14-dihydropiridine derivativemagnētiskas liposomasmagnetic liposomes
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