Semi-Automation in Video Editing

Semi-automasjon i video redigering Hvordan kan vi bruke kunstig intelligens (KI) og maskin læring til å gjøre videoredigering like enkelt som å redigere tekst? I denne avhandlingen vil jeg adressere problemet med å bruke KI i videoredigering fra et Menneskelig-KI interaksjons perspektiv, med fokus på å bruke KI til å støtte brukerne. Video er et audiovisuelt medium. Redigere videoer krever synkronisering av både det visuelle og det auditive med presise operasjoner helt ned på millisekund nivå. Å gjøre dette like enkelt som å redigere tekst er kanskje ikke mulig i dag. Men hvordan skal vi da støtte brukerne med KI og hva er utfordringene med å gjøre det? Det er fem hovedspørsmål som har drevet forskningen i denne avhandlingen. Hva er dagens "state-of-the-art" i KI støttet videoredigering? Hva er behovene og forventningene av fagfolkene om KI? Hva er påvirkningen KI har på effektiviteten og nøyaktigheten når det blir brukt på teksting? Hva er endringene i brukeropplevelsen når det blir brukt KI støttet teksting? Hvordan kan flere KI metoder bli brukt for å støtte beskjærings- og panoreringsoppgaver? Den første artikkelen av denne avhandlingen ga en syntese og kritisk gjennomgang av eksisterende arbeid med KI-baserte verktøy for videoredigering. Artikkelen ga også noen svar på hvordan og hva KI kan bli brukt til for å støtte brukere ved en undersøkelse utført av 14 fagfolk. Den andre studien presenterte en prototype av KI-støttet videoredigerings verktøy bygget på et eksisterende videoproduksjons program. I tillegg kom det en evaluasjon av både ytelse og brukeropplevelse på en KI-støttet teksting fra 24 nybegynnere. Den tredje studien beskrev et idiom-basert verktøy for å konvertere bredskjermsvideoer lagd for TV til smalere størrelsesforhold for mobil og sosiale medieplattformer. Den tredje studien utforsker også nye metoder for å utøve beskjæring og panorering ved å bruke fem forskjellige KI-modeller. Det ble også presentert en evaluering fra fem brukere. I denne avhandlingen brukte vi en brukeropplevelse og oppgave basert framgangsmåte, for å adressere det semi-automatiske i videoredigering.How can we use artificial intelligence (AI) and machine learning (ML) to make video editing as easy as "editing text''? In this thesis, this problem of using AI to support video editing is explored from the human--AI interaction perspective, with the emphasis on using AI to support users. Video is a dual-track medium with audio and visual tracks. Editing videos requires synchronization of these two tracks and precise operations at milliseconds. Making it as easy as editing text might not be currently possible. Then how should we support the users with AI, and what are the current challenges in doing so? There are five key questions that drove the research in this thesis. What is the start of the art in using AI to support video editing? What are the needs and expectations of video professionals from AI? What are the impacts on efficiency and accuracy of subtitles when AI is used to support subtitling? What are the changes in user experience brought on by AI-assisted subtitling? How can multiple AI methods be used to support cropping and panning task? In this thesis, we employed a user experience focused and task-based approach to address the semi-automation in video editing. The first paper of this thesis provided a synthesis and critical review of the existing work on AI-based tools for videos editing and provided some answers to how should and what more AI can be used in supporting users by a survey of 14 video professional. The second paper presented a prototype of AI-assisted subtitling built on a production grade video editing software. It is the first comparative evaluation of both performance and user experience of AI-assisted subtitling with 24 novice users. The third work described an idiom-based tool for converting wide screen videos made for television to narrower aspect ratios for mobile social media platforms. It explores a new method to perform cropping and panning using five AI models, and an evaluation with 5 users and a review with a professional video editor were presented.Doktorgradsavhandlin

Estimation on local transmission of malaria by serological approach under low transmission setting in Myanmar

Background: As the prevalence of the malaria has been decreasing in many endemic countries including Myanmar, malaria elimination in Greater Mekong Region was targeted not later than 2030. The relevance of molecular and serological tools to identify residual transmission remains to be established in this setting. Methods: One-year cohort study was conducted and sera samples were collected in every 3 months with active and passive case detection for clinical malaria episodes by RDT, microscopy and molecular method. The sera were used to detect the malaria antibody against PfMSP1-19, PvAMA1, PvDBPII and PvMSP1-19 by protein microarray. Results: Among the recruited 1182 participants, there was no RDT positive case for malaria infection although two vivax infections were detected by microscopy in initial collection. Molecular methods detected the asymptomatic cases of 28/1182 (2.37%) in first, 5/894 (0.42%) in second, 12/944 (1.02%) in third, 6/889 (0.51%) in fourth collection, respectively. Seropositivity rates against the PfMSP1-19, PvMSP1-19, PvAMA1 and PvDBPII were 73/270 (27.0%), 85/270 (31.5%), 65/270 (24.1%) and 160/270 (59.3%), respectively. PfMSP1-19 and PvMSP1-19 showed high and stable antigenicity in acute and subacute samples but declining in 1-year history samples. No cross reactivity of PfMSP1-19 and PvMSP1-19 between the two species and higher seropositivity among the asymptomatic carriers were observed. Mapping data indicated serological surveillance can detect the geographical pattern of malaria infection under low transmission setting. Conclusions: These findings support that PfMSP1-19 and PvMSP1-19 are suggested for serosurveillance of the malaria especially in low transmission setting for further necessary actions have to be carried out to eliminate the malaria.Publisher PDFPeer reviewe

Semi-Automation in Video Editing

Semi-automasjon i video redigering Hvordan kan vi bruke kunstig intelligens (KI) og maskin læring til å gjøre videoredigering like enkelt som å redigere tekst? I denne avhandlingen vil jeg adressere problemet med å bruke KI i videoredigering fra et Menneskelig-KI interaksjons perspektiv, med fokus på å bruke KI til å støtte brukerne. Video er et audiovisuelt medium. Redigere videoer krever synkronisering av både det visuelle og det auditive med presise operasjoner helt ned på millisekund nivå. Å gjøre dette like enkelt som å redigere tekst er kanskje ikke mulig i dag. Men hvordan skal vi da støtte brukerne med KI og hva er utfordringene med å gjøre det? Det er fem hovedspørsmål som har drevet forskningen i denne avhandlingen. Hva er dagens "state-of-the-art" i KI støttet videoredigering? Hva er behovene og forventningene av fagfolkene om KI? Hva er påvirkningen KI har på effektiviteten og nøyaktigheten når det blir brukt på teksting? Hva er endringene i brukeropplevelsen når det blir brukt KI støttet teksting? Hvordan kan flere KI metoder bli brukt for å støtte beskjærings- og panoreringsoppgaver? Den første artikkelen av denne avhandlingen ga en syntese og kritisk gjennomgang av eksisterende arbeid med KI-baserte verktøy for videoredigering. Artikkelen ga også noen svar på hvordan og hva KI kan bli brukt til for å støtte brukere ved en undersøkelse utført av 14 fagfolk. Den andre studien presenterte en prototype av KI-støttet videoredigerings verktøy bygget på et eksisterende videoproduksjons program. I tillegg kom det en evaluasjon av både ytelse og brukeropplevelse på en KI-støttet teksting fra 24 nybegynnere. Den tredje studien beskrev et idiom-basert verktøy for å konvertere bredskjermsvideoer lagd for TV til smalere størrelsesforhold for mobil og sosiale medieplattformer. Den tredje studien utforsker også nye metoder for å utøve beskjæring og panorering ved å bruke fem forskjellige KI-modeller. Det ble også presentert en evaluering fra fem brukere. I denne avhandlingen brukte vi en brukeropplevelse og oppgave basert framgangsmåte, for å adressere det semi-automatiske i videoredigering

Effect of GSTP1 polymorphism on efficacy and safety of cyclophosphamide aggressive therapy in lupus nephropathy patients

Background Lupus nephritis (LN) occurs in up to 60% of adults with systemic lupus erythematosus (SLE) and is a predictor of poor survival. Cyclophosphamide (CYC) is regarded as the most effective immunosuppressive medication to improve survival for patients with LN. Objective This prospective hospital-based study was conducted to identify the effect of glutathione S transferase Pi-1 (GSTP1) genotypes on the efficacy and safety of CYC aggressive therapy. Methods We enrolled SLE nephropathy patients admitted to the Department of Rheumatology of the 500-bed Yangon Specialty Hospital (YSH), Yangon, Myanmar, who received CYC aggressive therapy for 6 months according to treatment guidelines for SLE patients with renal involvement. The frequencies of I/I, I/V and V/V GSTP1 genotypes were determined using the polymerase chain reaction-restriction fragment length polymorphism method. The efficacy of CYC aggressive therapy between LN patients with wild GSTP1 (I/I) and those with polymorphic GSTP1 (I/V or V/V) genotypes was evaluated by comparing 24-h urinary protein levels and assessing the remission rates at 3 and 6 months after initiation of CYC. CYC-related myelotoxicity was assessed by reviewing complete blood picture results on the 10th day after CYC treatment. Results In total, 95 eligible patients were recruited. The frequencies of I/I, I/V and V/V GSTP1 genotypes were 54.7, 41.1 and 4.2%, respectively. At 3 and 6 months after CYC treatment, mean 24-h urinary protein had significantly decreased from baseline in both wild and polymorphic genotype groups (p &lt; 0.001). No significant differences were seen between the wild and polymorphic genotype groups with regard to changes in 24-h urinary protein levels, remission at 3 and 6 months or myelotoxicity. Conclusion CYC aggressive therapy had similar efficacy and caused no significant differences in myelotoxicity in wild GSTP1 (I/I) and polymorphic GSTP1 (I/V or V/V) genotypes in patients treated according to YSH guidelines for SLE patients with renal involvement.</p

Additional file 2: Table S2. of Genetic diversity of Plasmodium falciparum populations in southeast and western Myanmar

Allele sizes and types of Msp1, Msp2 and Glurp genes. (XLS 83 kb

Genetic diversity of Plasmodium falciparum populations in southeast and western Myanmar

Abstract Background The genetic diversity of malaria parasites reflects the complexity and size of the parasite populations. This study was designed to explore the genetic diversity of Plasmodium falciparum populations collected from two southeastern areas (Shwekyin and Myawaddy bordering Thailand) and one western area (Kyauktaw bordering Bangladesh) of Myanmar. Methods A total of 267 blood samples collected from patients with acute P. falciparum infections during 2009 and 2010 were used for genotyping at the merozoite surface protein 1 (Msp1), Msp2 and glutamate-rich protein (Glurp) loci. Results One hundred and eighty four samples were successfully genotyped at three genes. The allelic distributions of the three genes were all significantly different among three areas. MAD20 and 3D7 were the most prevalent alleles in three areas for Msp1 and Msp2, respectively. The Glurp allele with a bin size of 700–750 bp was the most prevalent both in Shwekyin and Myawaddy, whereas two alleles with bin sizes of 800–850 bp and 900–1000 bp were the most prevalent in the western site Kyauktaw. Overall, 73.91% of samples contained multiclonal infections, resulting in a mean multiplicity of infection (MOI) of 1.94. Interestingly, the MOI level presented a rising trend with the order of Myawaddy, Kyauktaw and Shwekyin, which also paralleled with the increasing frequencies of Msp1 RO33 and Msp2 FC27 200–250 bp alleles. Msp1 and Msp2 genes displayed higher levels of diversity and higher MOI rates than Glurp. PCR revealed four samples (two from Shwekyin and two from Myawaddy) with mixed infections of P. falciparum and P. vivax. Conclusions This study genotyped parasite clinical samples from two southeast regions and one western state of Myanmar at the Msp1, Msp2 and Glurp loci, which revealed high levels of genetic diversity and mixed-strain infections of P. falciparum populations at these sites. The results indicated that malaria transmission intensity in these regions remained high and more strengthened control efforts are needed. The genotypic data provided baseline information for monitoring the impacts of malaria elimination efforts in the region

Additional file 2: Table S2. of Genetic diversity of Plasmodium falciparum populations in southeast and western Myanmar

Allele sizes and types of Msp1, Msp2 and Glurp genes. (XLS 83 kb