Готові списки джерел за темами / KFDV

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Добірка наукової літератури з теми "KFDV"

Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "KFDV"

1

Kandagalla, Shivananda, Bhimanagoud Kumbar, and Jurica Novak. "Structural Modifications Introduced by NS2B Cofactor Binding to the NS3 Protease of the Kyasanur Forest Disease Virus." International Journal of Molecular Sciences 24, no. 13 (June 30, 2023): 10907. http://dx.doi.org/10.3390/ijms241310907.

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Анотація:
Kyasanur Forest Disease virus (KFDV), a neglected human pathogenic virus, is a Flavivirus that causes severe hemorrhagic fever in humans. KFDV is transmitted to humans by the bite of the hard tick (Haemaphysalis spinigera), which acts as a reservoir of KFDV. The recent expansion of the endemic area of KFDV is of concern and requires the development of new preventive measures against KFDV. Currently, there is no antiviral therapy against KFDV, and the existing vaccine has limited efficacy. To develop a new antiviral therapy against KFDV, we focused on the nonstructural proteins NS2B and NS3 of KFDV, which are responsible for serine protease activity. Viral proteases have shown to be suitable therapeutic targets in the development of antiviral drugs against many diseases. However, success has been limited in flaviviruses, mainly because of the important features of the active site, which is flat and highly charged. In this context, the present study focuses on the dynamics of NS2B and NS3 to identify potential allosteric sites in the NS2B/NS3 protease of KDFV. To our knowledge, there are no reports on the dynamics of NS2B and NS3 in KFDV, and the crystal structure of the NS2B/NS3 protease of KFDV has not yet been solved. Overall, we created the structure of the NS2B/NS3 protease of KFDV using AlphaFold and performed molecular dynamics simulations with and without NS2B cofactor to investigate structural rearrangements due to cofactor binding and to identify alternative allosteric sites. The identified allosteric site is promising due to its geometric and physicochemical properties and druggability and can be used for new drug development. The applicability of the proposed allosteric binding sites was verified for the best-hit molecules from the virtual screening and MD simulations.
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2

Broeckel, Rebecca M., Friederike Feldmann, Kristin L. McNally, Abhilash I. Chiramel, Gail L. Sturdevant, Jacqueline M. Leung, Patrick W. Hanley, et al. "A pigtailed macaque model of Kyasanur Forest disease virus and Alkhurma hemorrhagic disease virus pathogenesis." PLOS Pathogens 17, no. 12 (December 2, 2021): e1009678. http://dx.doi.org/10.1371/journal.ppat.1009678.

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Анотація:
Kyasanur Forest disease virus (KFDV) and the closely related Alkhurma hemorrhagic disease virus (AHFV) are emerging flaviviruses that cause severe viral hemorrhagic fevers in humans. Increasing geographical expansion and case numbers, particularly of KFDV in southwest India, class these viruses as a public health threat. Viral pathogenesis is not well understood and additional vaccines and antivirals are needed to effectively counter the impact of these viruses. However, current animal models of KFDV pathogenesis do not accurately reproduce viral tissue tropism or clinical outcomes observed in humans. Here, we show that pigtailed macaques (Macaca nemestrina) infected with KFDV or AHFV develop viremia that peaks 2 to 4 days following inoculation. Over the course of infection, animals developed lymphocytopenia, thrombocytopenia, and elevated liver enzymes. Infected animals exhibited hallmark signs of human disease characterized by a flushed appearance, piloerection, dehydration, loss of appetite, weakness, and hemorrhagic signs including epistaxis. Virus was commonly present in the gastrointestinal tract, consistent with human disease caused by KFDV and AHFV where gastrointestinal symptoms (hemorrhage, vomiting, diarrhea) are common. Importantly, RNAseq of whole blood revealed that KFDV downregulated gene expression of key clotting factors that was not observed during AHFV infection, consistent with increased severity of KFDV disease observed in this model. This work characterizes a nonhuman primate model for KFDV and AHFV that closely resembles human disease for further utilization in understanding host immunity and development of antiviral countermeasures.
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3

Shah, Keerti V., Chandu N. Dandawate, and Pravin N. Bhatt. "Kyasanur forest disease virus: viremia and challenge studies in monkeys with evidence of cross-protection by Langat virus infection." F1000Research 1 (December 7, 2012): 61. http://dx.doi.org/10.12688/f1000research.1-61.v1.

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Анотація:
Kyasanur Forest Disease Virus (KFDV), discovered in 1957, is a member of the tick-borne encephalitis virus (TBEV) complex. Diseases caused by members of the TBEV complex occur in many parts of the world. KFDV produces a hemorrhagic fever in humans in South India and fatal illnesses in both species of monkeys in the area, the black faced langur (Presbytis entellus) and the bonnet macaque (Macaca radiata). Experimental infection of the langur and the bonnet macaque with early mouse passage KFDV strain P9605 resulted in a viremia of up to 11 days duration, peak viremia titers as high as 109, and death in 82 = 100% of the animals. Prolonged passage of the KFDV strain P9605 in monkey kidney tissue culture resulted in a markedly reduced virulence of the virus for both species; peak viremia titers in monkeys decreased by 2.5 to 4.0 log LD 50 (p= 0.001), and the mortality decreased to 10% (p= 0.001). In challenge experiments, monkeys previously infected with tissue-culture-adapted KFDV, or with the related Langat virus from Malaysia, were fully protected against virulent KFDV. These studies in non-human primates lend support to the idea that a live virus vaccine from a member of the TBEV complex may be broadly protective against infections by other members of the TBEV complex.
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4

Bhatia, Bharti, Heinz Feldmann, and Andrea Marzi. "Kyasanur Forest Disease and Alkhurma Hemorrhagic Fever Virus—Two Neglected Zoonotic Pathogens." Microorganisms 8, no. 9 (September 12, 2020): 1406. http://dx.doi.org/10.3390/microorganisms8091406.

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Анотація:
Kyasanur Forest disease virus (KFDV) and Alkhurma hemorrhagic fever virus (AHFV) are tick-borne flaviviruses that cause life-threatening hemorrhagic fever in humans with case fatality rates of 3–5% for KFDV and 1–20% for AHFV, respectively. Both viruses are biosafety level 4 pathogens due to the severity of disease they cause and the lack of effective countermeasures. KFDV was discovered in India and is restricted to parts of the Indian subcontinent, whereas AHFV has been found in Saudi Arabia and Egypt. In recent years, both viruses have spread beyond their original endemic zones and the potential of AHFV to spread through ticks on migratory birds is a public health concern. While there is a vaccine with limited efficacy for KFDV used in India, there is no vaccine for AHFV nor are there any therapeutic concepts to combat infections with these viruses. In this review, we summarize the current knowledge about pathogenesis, vector distribution, virus spread, and infection control. We aim to bring attention to the potential public health threats posed by KFDV and AHFV and highlight the urgent need for the development of effective countermeasures.
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5

Burthe, Sarah J., Stefanie M. Schäfer, Festus A. Asaaga, Natrajan Balakrishnan, Mohammed Mudasssar Chanda, Narayanaswamy Darshan, Subhash L. Hoti, et al. "Reviewing the ecological evidence base for management of emerging tropical zoonoses: Kyasanur Forest Disease in India as a case study." PLOS Neglected Tropical Diseases 15, no. 4 (April 1, 2021): e0009243. http://dx.doi.org/10.1371/journal.pntd.0009243.

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Анотація:
Zoonoses disproportionately affect tropical communities and are associated with human modification and use of ecosystems. Effective management is hampered by poor ecological understanding of disease transmission and often focuses on human vaccination or treatment. Better ecological understanding of multi-vector and multi-host transmission, social and environmental factors altering human exposure, might enable a broader suite of management options. Options may include “ecological interventions” that target vectors or hosts and require good knowledge of underlying transmission processes, which may be more effective, economical, and long lasting than conventional approaches. New frameworks identify the hierarchical series of barriers that a pathogen needs to overcome before human spillover occurs and demonstrate how ecological interventions may strengthen these barriers and complement human-focused disease control. We extend these frameworks for vector-borne zoonoses, focusing on Kyasanur Forest Disease Virus (KFDV), a tick-borne, neglected zoonosis affecting poor forest communities in India, involving complex communities of tick and host species. We identify the hierarchical barriers to pathogen transmission targeted by existing management. We show that existing interventions mainly focus on human barriers (via personal protection and vaccination) or at barriers relating to Kyasanur Forest Disease (KFD) vectors (tick control on cattle and at the sites of host (monkey) deaths). We review the validity of existing management guidance for KFD through literature review and interviews with disease managers. Efficacy of interventions was difficult to quantify due to poor empirical understanding of KFDV–vector–host ecology, particularly the role of cattle and monkeys in the disease transmission cycle. Cattle are hypothesised to amplify tick populations. Monkeys may act as sentinels of human infection or are hypothesised to act as amplifying hosts for KFDV, but the spatial scale of risk arising from ticks infected via monkeys versus small mammal reservoirs is unclear. We identified 19 urgent research priorities for refinement of current management strategies or development of ecological interventions targeting vectors and host barriers to prevent disease spillover in the future.
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6

Yadav, Pooja, Shashi Sharma, Paban Kumar Dash, Suman Dhankher, Sandhya V. K., and S. K. Kiran. "Dry- down probe free qPCR for detection of KFD in resource limited settings." PLOS ONE 18, no. 5 (May 10, 2023): e0284559. http://dx.doi.org/10.1371/journal.pone.0284559.

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Анотація:
Kyasanur Forest Disease is a tick-borne flavivirus is endemic in the Southern India. The recent expansion and resurgence of sporadic outbreaks in southern parts of country is the most important concern. Although only formalin inactivated vaccine is available for treatment with limited efficacy the early detection and timely identification is a only way to prevent spread of cases. If the disease can be identified prior to infection in humans like in forest areas from ticks and vectors the disease spread supposed to be managed quickly. Here we have standardized a single tube ready to use dry-down probe free real time RT-PCR targeted against virus envelope gene for detection of KFDV infection. The assay was standardized in liquid format first, later it was converted into dry-down format with addition of stabilizers with a similar sensitivity and specificity (10RNA Copies/rxn). The sensitivity was comparable to the most widely used and accepted diagnostic platform i.e. TaqMan qRT-PCR. However as the reported assay here omit the need of probes makes it cost effective and dry-down reagents makes more stability to the developed assay in this study if compare to TaqMan qPCR. The assay was evaluated with KFD positive samples and healthy sample panel which revealed high concordance with TaqMan qRT-PCR. Stability was unaffected by temperature fluctuations during transportation even in cold chain free conditions, thus reduce the maintenance of strict cold storage. These findings demonstrated that the reported assay is convenient with 100% sensitivity and specificity to TaqMan qPCR. Thus this assay has the potential usefulness for diagnosis KFDV for routine surveillance in resource limited laboratory settings omitting the use costly and heat sensitive TaqMan qRT-PCR reagents without compromising the sensitivity and specificity of the diagnosis assay.
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7

Carpio, Kassandra L., Jill K. Thompson, Steven G. Widen, Jennifer K. Smith, Terry L. Juelich, David E. Clements, Alexander N. Freiberg, and Alan D. T. Barrett. "Differences in Genetic Diversity of Mammalian Tick-Borne Flaviviruses." Viruses 15, no. 2 (January 19, 2023): 281. http://dx.doi.org/10.3390/v15020281.

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Анотація:
The genetic diversities of mammalian tick-borne flaviviruses are poorly understood. We used next-generation sequencing (NGS) to deep sequence different viruses and strains belonging to this group of flaviviruses, including Central European tick-borne encephalitis virus (TBEV-Eur), Far Eastern TBEV (TBEV-FE), Langat (LGTV), Powassan (POWV), Deer Tick (DTV), Kyasanur Forest Disease (KFDV), Alkhurma hemorrhagic fever (AHFV), and Omsk hemorrhagic fever (OHFV) viruses. DTV, AHFV, and KFDV had the lowest genetic diversity, while POWV strains LEIV-5530 and LB, OHFV, TBEV-Eur, and TBEV-FE had higher genetic diversities. These findings are compatible with the phylogenetic relationships between the viruses. For DTV and POWV, the amount of genetic diversity could be explained by the number of tick vector species and amplification hosts each virus can occupy, with low diversity DTV having a more limited vector and host pool, while POWV with higher genetic diversities has been isolated from different tick species and mammals. It is speculated that high genetic diversity may contribute to the survival of the virus as it encounters these different environments.
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8

Flint, Mike, Laura K. McMullan, Kimberly A. Dodd, Brian H. Bird, Marina L. Khristova, Stuart T. Nichol, and Christina F. Spiropoulou. "Inhibitors of the Tick-Borne, Hemorrhagic Fever-Associated Flaviviruses." Antimicrobial Agents and Chemotherapy 58, no. 6 (March 24, 2014): 3206–16. http://dx.doi.org/10.1128/aac.02393-14.

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Анотація:
ABSTRACTNo antiviral therapies are available for the tick-borne flaviviruses associated with hemorrhagic fevers: Kyasanur Forest disease virus (KFDV), both classical and the Alkhurma hemorrhagic fever virus (AHFV) subtype, and Omsk hemorrhagic fever virus (OHFV). We tested compounds reported to have antiviral activity against members of theFlaviviridaefamily for their ability to inhibit AHFV replication. 6-Azauridine (6-azaU), 2′-C-methylcytidine (2′-CMC), and interferon alpha 2a (IFN-α2a) inhibited the replication of AHFV and also KFDV, OHFV, and Powassan virus. The combination of IFN-α2a and 2′-CMC exerted an additive antiviral effect on AHFV, and the combination of IFN-α2a and 6-azaU was moderately synergistic. The combination of 2′-CMC and 6-azaU was complex, being strongly synergistic but with a moderate level of antagonism. The antiviral activity of 6-azaU was reduced by the addition of cytidine but not guanosine, suggesting that it acted by inhibiting pyrimidine biosynthesis. To investigate the mechanism of action of 2′-CMC, AHFV variants with reduced susceptibility to 2′-CMC were selected. We used a replicon system to assess the substitutions present in the selected AHFV population. A double NS5 mutant, S603T/C666S, and a triple mutant, S603T/C666S/M644V, were more resistant to 2′-CMC than the wild-type replicon. The S603T/C666S mutant had a reduced level of replication which was increased when M644V was also present, although the replication of this triple mutant was still below that of the wild type. The S603 and C666 residues were predicted to lie in the active site of the AHFV NS5 polymerase, implicating the catalytic center of the enzyme as the binding site for 2′-CMC.
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9

Dodd, Kimberly A., Brian H. Bird, Marina L. Khristova, César G. Albariño, Serena A. Carroll, James A. Comer, Bobbie R. Erickson, Pierre E. Rollin, and Stuart T. Nichol. "Ancient Ancestry of KFDV and AHFV Revealed by Complete Genome Analyses of Viruses Isolated from Ticks and Mammalian Hosts." PLoS Neglected Tropical Diseases 5, no. 10 (October 4, 2011): e1352. http://dx.doi.org/10.1371/journal.pntd.0001352.

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10

Thashanamoorthy, G., and S. Ramalingam. "EXPRESSION OF RECOMBINANT ENVELOPE DOMAIN III PROTEIN IN PROKARYOTIC AND EUKARYOTIC HOST SYSTEM FOR THE FOR THE DIAGNOSIS OF KYASANUR FOREST DISEASE VIRUS (KFDV)." International Journal of Infectious Diseases 130 (May 2023): S91. http://dx.doi.org/10.1016/j.ijid.2023.04.226.

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Більше джерел

Дисертації з теми "KFDV"

1

羽根, 由紀奈. "<彙報>動的家族画 (KFD) にみられる親子関係についての基礎的研究 : 子どもと母親の描画を通して(平成 9 年度発達臨床学専攻修士学位論文概要)". 名古屋大学教育学部, 1998. http://hdl.handle.net/2237/2928.

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2

Abdallah, Fahed. "Noyaux reproduisants et critères de contraste pour l'élaboration de détecteurs à structure imposée." Troyes, 2004. http://www.theses.fr/2004TROY0002.

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Анотація:
Les travaux réalisés pendant cette thèse sont relatifs à la synthèse de détecteurs à partir d'une base d'exemples étiquetés. La théorie développée fait appel aux espaces de Hilbert à noyaux reproduisants pour l'élaboration de détecteurs linéaires généralisés dans des espaces transformés de dimension importante, voire infinie, sans qu'aucun calcul n'y soit effectué explicitement. Elle repose sur l'optimisation du meilleur critère de contraste pour le problème traité, après s'être assuré que de telles mesures de performance permettant l'obtention sous des conditions restrictives assez faibles, à une statistique équivalente au rapport de vraisemblance. Pour une meilleure prise en compte de phénomènes tels que la malédiction de la dimensionnalité, l'approche proposée s'appuie sur la théorie de l'apprentissage. Celle-ci lui permet d'offrir des garanties de performances en généralisation. On propose ainsi des méthodes qui permettent le contrôle de complexité des détecteurs obtenus. Les résultats obtenus sur des données synthétiques et réelles montrent que notre approche est en mesure de rivaliser avec les structures de décision les plus étudiées actuellement que sont les Support Vector Machines
In this thesis, we consider statistical learning machines with try to infer rules from a given set or observations in order to make correct predictions on unseen examples. Building upon the theory of reproducing kernels, we develop a generalized linear detector in transformed spaces of high dimension, without explicitly doing any calculus in these spaces. The method is based on the optimization of the best second-order criterion with respect to the problem to solve. In fact, theoretical results show that second-order criteria are able, under some mild conditions, to guarantee the best solution in the sense of classical detection theories. Achieving a good generalisation performance with a receiver requires matching its complexity to the amount of available training data. This problem, known as the curse of dimensionality, has been studied theoretically by Vapnik and Chervonenkis. In this dissertation, we propose complexity control procedures in order to improve the performance of these receivers when few training data are available. Simulation results on real and synthetic data show clearly the competitiveness of our approach compared with other state of the art existing kernel methods like Support Vector Machines
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3

BHARDWAJ, SHREYA. "T-CELL AND B-CELL EPITOPE PREDICTION FOR MULTI-EPITOPE PEPTIDE VACCINE AGAINST KYASANUR FOREST DISEASE VIRUS." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20003.

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Анотація:
Kyasanur Forest Disease Virus (KFDV) is a tick-borne flavivirus that is transmitted to humans through the bite of infected ticks, it endemics primarily in south-western regions of the Indian subcontinent, mainly Karnataka, Kerala, Tamil Nadu, Goa, and Maharashtra. The disease poses a significant public health challenge, with no licensed vaccines currently available for its prevention. KFDV is a seriously underreached virus, despite its high morbidity and mortality rates. This study aims to address this critical gap by employing an in-silico approach to design a peptide-based vaccine against KFDV. Through a systematic in-silico approach involving structural and antigenic analyses, B-cell and T-cell epitope prediction, as well as molecular docking studies, we identified four B-cell epitopes and 11 T-cell epitopes with desirable characteristics such as high affinity, low allergenicity, strong antigenicity, minimal toxicity, stability, and the ability to induce IFN-gamma. Furthermore, molecular docking analyses confirmed the robust binding of the epitopes with their respective MHC alleles. These findings provide valuable insights into potential targets for vaccine development against KFDV. However, further experimental validation and preclinical studies are warranted to evaluate the immunogenicity and protective efficacy of these epitopes. The development of an effective vaccine against KFDV would be crucial in controlling the spread of this disease and safeguarding vulnerable populations at risk of infection.
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4

Miao, Chuxiong. "A support vector machine model for pipe crack size classification." Master's thesis, 2009. http://hdl.handle.net/10048/400.

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Thesis (M. Sc.)--University of Alberta, 2009.
Title from pdf file main screen (viewed on July 16, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Mechanical Engineering, University of Alberta." Includes bibliographical references.
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Книги з теми "KFDV"

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Korea (South). Sikpʻum Ŭiyakpʻum Anjŏnchʻŏng., ed. KFDA, OECD, FDA, EPA, GLP kyujŏng pigyo. Sŏul Tʻŭkpyŏlsi: Sikpʻum Ŭiyakpʻum Anjŏnchʻŏng, 2005.

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2

Mitra, Amit. Oxfam support project Uttara Kannada: An evaluation of the first phase of work in support of the KFD/DFID western Ghats Forestry Project. New Delhi: Oxfam (India) Trust, 1997.

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3

Mahatma Gandhi University (Kottayam, India). School of Social Sciences. An independent evaluation of participatory forest management (PFM): The case of the Vana Samrakshana Samiti-s (VSS) and the Kerala Forest Dept. (KFD). [Kottayam: School of Social Sciences, Mahatma Gandhhi University], 2003.

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4

Project, Western Ghats Forestry. Social impact assessment of the Western Ghats Forestry Project (KFD/DFID) in Karnataka with a focus on the JFPM programme: A study report. Bangalore: Outreach, 1998.

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5

Schock, Randy. Nelson Wayne Schock Book Four: Remembering KFDI. Independently Published, 2019.

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6

Kaufman, S. Harvard, and Robert C. Burns. Action, Styles, and Symbols in Kinetic Family Drawings Kfd. Taylor & Francis Group, 2013.

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7

Burns, Robert C., and S. Harvard Kaufman. Action, Styles, And Symbols In Kinetic Family Drawings Kfd. Routledge, 2013. http://dx.doi.org/10.4324/9780203765531.

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8

Burns, Robert C., and S. Harvard Kaufman. Action, Styles, and Symbols in Kinetic Family Drawings Kfd. Taylor & Francis Group, 2013.

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9

Burns, Robert C., and S. Harvard Kaufman. Action, Styles, and Symbols in Kinetic Family Drawings Kfd. Taylor & Francis Group, 2013.

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10

Kaufman, S. Harvard, and Robert C. Burns. Action, Styles, and Symbols in Kinetic Family Drawings Kfd. Taylor & Francis Group, 2016.

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Частини книг з теми "KFDV"

1

Wang, Guoqiang, and Guoqiang Ding. "Face Recognition Using KFDA-LLE." In Advanced Intelligent Computing, 420–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24728-6_57.

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2

Zhang, Qing, and Jianwu Li. "Constructing Sparse KFDA Using Pre-image Reconstruction." In Lecture Notes in Computer Science, 658–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17534-3_81.

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3

Wang, GuoQiang, and ChunLing Gao. "Robust Face Recognition Based on KFDA-LLE and SVM Techniques." In Advances in Computer Science, Environment, Ecoinformatics, and Education, 581–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23321-0_91.

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4

Zhang, Qing, Jianwu Li, and Zhiping Zhang. "Efficient Semantic Kernel-Based Text Classification Using Matching Pursuit KFDA." In Neural Information Processing, 382–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24958-7_45.

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5

Zhao, Yue, and Jinwen Ma. "Kernel Parameter Optimization for KFDA Based on the Maximum Margin Criterion." In Advances in Neural Networks – ISNN 2014, 330–37. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12436-0_37.

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6

Xu, Yong, Chuancai Liu, and Chongyang Zhang. "Determine the Kernel Parameter of KFDA Using a Minimum Search Algorithm." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 418–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74205-0_46.

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7

Bon-Woo, Hwang, Hyeran Byun, Roh Myoung-Cheol, and Lee Seong-Whan. "Performance Evaluation of Face Recognition Algorithms on the Asian Face Database, KFDB." In Lecture Notes in Computer Science, 557–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44887-x_66.

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8

Zou, Jin, and Feng Sun. "Face Recognition Using Block-Based DCT and Weighted Generalized KFD." In Advances in Intelligent and Soft Computing, 243–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27866-2_30.

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9

Zhang, David, Xiao-Yuan Jing, and Jian Yang. "Complete Kernal Fisher Discrimination Analysis." In Computational Intelligence and its Applications, 235–57. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-830-7.ch010.

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Анотація:
This chapter introduces a complete kernel Fisher discriminant analysis (KFD) that is a useful statistical technique applied to biometric application. We first describe theoretical perspective of KPCA. Then, a new KFD algorithm framework, KPCA plus LDA, is given. Afterwards, we discuss the complete KFD algorithm. Finally, the experimental results and chapter summary are given.
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"Kyasanur Forest Disease (KFD)." In Lexikon der Infektionskrankheiten des Menschen, 466. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-39026-8_589.

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Тези доповідей конференцій з теми "KFDV"

1

Cai, Zheng, Fu-Long Wang, and Ai-Hui Xu. "A new image distance for KFDA." In 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5647901.

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2

Yu-Xin Wei and Mu-Qing Wu. "KFDA-waveletcluster based intrusion detection technology." In 2007 International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/icwapr.2007.4421766.

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3

Wang, Zhifang, Qiong Li, Xiamu Niu, and Christoph Busch. "Multimodal Biometric Recognition Based on Complex KFDA." In 2009 Fifth International Conference on Information Assurance and Security. IEEE, 2009. http://dx.doi.org/10.1109/ias.2009.68.

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4

Rui-Fan Li, Hong-Wei Hao, Xu-Yan Tu, and Cong Wang. "Face recognition using KFD-Isomap." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1527739.

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5

Xiuqin Pan, Yongcun Cao, Xiaona Xu, Yong Lu, and Yue Zhao. "Ear and face based multimodal recognition based on KFDA." In 2008 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2008. http://dx.doi.org/10.1109/icalip.2008.4590072.

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6

Luo, De-Jiang. "A KFDA Based on Regularization Method for Multi-classification." In 2013 Fourth International Conference on Emerging Intelligent Data and Web Technologies (EIDWT). IEEE, 2013. http://dx.doi.org/10.1109/eidwt.2013.35.

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7

Ni, Jian, and Libo Liang. "A Gait Recognition Method Based on KFDA and SVM." In 2009 International Workshop on Intelligent Systems and Applications. IEEE, 2009. http://dx.doi.org/10.1109/iwisa.2009.5072621.

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Yucheng Wang and Dongmei Sun. "Feature fusion of palmprint and face based on KFDA." In 2008 9th International Conference on Signal Processing (ICSP 2008). IEEE, 2008. http://dx.doi.org/10.1109/icosp.2008.4697557.

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9

Lin, Qing, Zheng Liu, and Huixia Sun. "A HRRP Recognition Method Based on KFD." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.345836.

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10

Yongchun Liang, Xiaoyun Sun, Qingrui Liu, Jianpeng Bian, and Yanming Li. "Fault Diagnosis Model of Power Transformer Based on Combinatorial KFDA." In 2008 International Conference on Condition Monitoring and Diagnosis, CMD 2008. IEEE, 2008. http://dx.doi.org/10.1109/cmd.2008.4580441.

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