DeepRoom: A Deep Learning Rating System for Photography

This thesis explores integrating deep learning techniques into photography, aiming to automate the identification of good images within large datasets. The primary focus is developing a deep learning-based system called DeepRoom that rates and evaluates photographs based on photography-specific technical criteria. To accomplish this, the research methodology encompasses qualitative research alongside developing a system prototype. A section overviews deep learning, photography, and related work and emphasizes its relevance to the research objectives. Implementation details include describing development tools and processes employed to construct the deep learning models and curate the dataset. These models' performance is assessed in the following evaluation phase, and a comparative analysis is conducted against existing software solutions. Encouraging results are observed, particularly in object detection and exposure classification, while identifying areas for improvement, such as refining the blurry and skewed horizon models. In conclusion, this research highlights the contributions of DeepRoom and proposes future work, including dataset expansion and model refinement, to enhance its capabilities further

Raman spektroskopi for målinger av matkvalitet i prosesslinjen

A major challenge in the food industry is to effectively handle massive streams of food raw materials and products of different origin and quality. In-line sensor systems for food analysis can potentially measure and collect critical quality and safety parameters throughout the processes. This information can be used for sorting, product differentiation, process optimisation and product control. One emerging technology that shows great promise for future in-line food sensor systems is Raman spectroscopy. The overall goal of this thesis was to elucidate the feasibility of Raman spectroscopy as a tool for detailed quality evaluation of heterogeneous food raw materials, under in-line industrial conditions. To this end, two main application areas were chosen, including A1) in-line measurements of fatty acid features in salmon fillets and A2) in-line characterization of a poultry rest raw material stream. A central element in both application areas was the use of a Wide Area Illumination (WAI) Raman probe to obtain representative measurements of the heterogeneous raw materials and to tackle variations in working distance. Variations in working distance may easily happen in an industrial process line with samples of varying thicknesses and streams of varying production volumes. The limited measurement volume of the WAI probe was increased by scanning over the sample surface. We showed that this strategy was successful with respect to obtaining representative measurements. This was demonstrated through obtaining good performances for EPA+DHA estimation in salmon fillets of varying thickness (± 1 cm) and through characterization (fat, protein, bone and collagen) of poultry rest raw material with larger variations in working distances (± 3 cm). For the latter study, the method was also tested in-line at a real hydrolysis facility with promising results. For the study on salmon fillets, the varying fat deposition across the fillets was shown to have implication for choice of scanning strategy at shorter exposure times due to impact on signal-to-noise ratio (SNR). This illustrates the importance of considering the heterogeneity of the food product in a given application, and of optimizing measurement strategies accordingly. Another main objective was to elucidate the ability of Raman measurements to tackle short exposure times. This is of particular importance for measurements of single samples at a conveyor belt, where exposure time is strictly limited. This was investigated in paper I and II, where we measured single salmon and poultry samples at exposure times down to 1 s. While exposure times around 2-1 s in these cases did give acceptable performances, it was evident that these low exposure times reduced SNR and performance and that SNR was a critical parameter. This indicates that at shorter exposure times, the surface scanning with theWAI Raman probe might be less robust with respect to tackling samples of varying sample sizes or lower analyte concentrations. Therefore, for such single samples, WAI Raman spectroscopy is currently better suited for fast at-line or on-line measurements. However, such measurements could also have high value for the industry, as it represents a frequent quality feedback, which is currently lacking. Overall, it was found that further efforts on calibration development, SNR optimization and practical measurement setup are needed to unlock the full potential for in-line measurements in the two application areas. Still, this thesis has shown that it is feasible to use a WAI Raman probe for detailed characterization of very heterogeneous streams of raw material, at industrially relevant speeds and in presence of moderate variations in working distance and probe tilt. It was shown that WAI Raman spectroscopy is promising, both for measurements of continuous raw material streams and single food products on a conveyor belt. This introduces many new application opportunities for Raman spectroscopy within quality documentation, sorting, process analysis and real-time process control in the food industry.En stor utfordring for matindustrien er å håndtere store strømmer av råvarer og produkter av forskjellig opprinnelse og kvalitet på en effektiv måte. Sensorsystemer som kan brukes direkte på prosesslinjene, såkalt ”in-line”, kan potensielt måle og samle kritisk informasjon om matkvalitet og mattrygghet. Resultatet er verktøy for sortering, produktdifferensiering, prosessoptimering og produktkontroll. Raman spektroskopi er en lovende teknologi under utvikling med stort potensiale som sensorsystem i matindustrien. Målet med dette doktorgradsprosjektet var å undersøke mulighetene for å bruke Raman-spektroskopi som et verktøy for kvalitetsmålinger av heterogene matråvarer direkte i prosesslinjen. For å nå dette målet ble to bruksområder valgt, inkludert A1) in-line målinger av fettsyreprofil i laksefileter og A2) in-line karakterisering av råvarestrømmer fra fjærfe-produksjon. Et sentralt tema for begge bruksområdene var bruken av en Raman-probe med bredt belysningsområde (WAI) for å oppnå representative målinger av heterogene råvarer og for å takle variasjoner i arbeidsavstand. Variasjoner i arbeidsavstand kan fort oppstå i en industriell prosesslinje med prøver av varierende tykkelse og for stømmer med varierende produksjonsvolum. Fokusvolumet til WAI-proben ble økt ved å skanne over prøveoverflaten. Vi viste at denne strategien fungerte godt for å oppnå representative målinger. Dette ble demonstrert ved å oppnå lave prediksjonsfeil for EPA + DHA-estimering i laksefileter med varierende tykkelse (± 1 cm) og for karakterisering (fett, protein, bein og kollagen) av kyllingråstoff med større variasjoner i arbeidsavstand (± 3 cm). For sistnevnte studie ble metoden også testet in-line på et industrielt hydrolyseanlegg, med lovende resultater. For studien på laksefileter ble det vist at det varierende fettinnholdet på filletoverflaten hadde betydning for valg av skannestrategi ved kortere eksponeringstider, grunnet effekten på signal-støy-forholdet. Dette illustrerer hvor viktig det er å gjøre nøye vurderinger av heterogeniteten til et gitt matprodukt, og å optimalisere målestrategien deretter. Et annet hovedmål var å undersøke hvordan Raman-målingene håndterte kortere eksponeringstider. Dette er av spesiell betydning for målinger av enkeltprøver på et transportbelte, der eksponeringstiden er sterkt begrenset. Dette ble undersøkt i artikkel I og II, der vi målte enkeltprøver av laks og fjærfe-restråstoff ved eksponeringstider ned til 1 s. Selv om eksponeringstider rundt 2-1 s i disse tilfellene ga akseptable prediksjonsfeil, var det tydelig at disse lave eksponeringstidene reduserte signal-støy-forholdet og dermed prediksjons-prestasjonen. Signalstøy- forholdet er altså en kritisk faktor, og dette indikerer at skanning med WAI Raman-proben kan være mindre robust når det gjelder å håndtere prøver med varierende prøvestørrelser eller lavere analytt-konsentrasjoner, ved slike korte eksponeringstider. Derfor er Raman-målingene foreløpig bedre egnet for hurtige målinger ved siden av produksjonslinjen (”at-line” eller ”on-line”), for enkeltprøver. Slike målinger kan også ha høy verdi for industrien, da det representerer et system som gir hyppig tilbakemelding på kvalitet, noe som det for øyeblikket ikke finnes løsninger for. En videre innsats innen kalibreringsutvikling, SNR-optimering og utvikling av praktisk måleoppsett er nødvendig for å realisere det fulle potensialet for in-line Raman-målinger i de to applikasjonsområdene. Likevel har dette doktorgradsprosjektet vist at det er mulig å bruke en Raman probe med bredt belysningsområde til detaljert karakterisering av av svært heterogene strømmer med råvaremateriale, ved industrielt relevante eksponeringstider og med moderat variasjon i arbeidsavstand. Det ble vist at WAI Raman spektroskopi er lovende både for målinger på kontinuerlige råvarestrømmer og enkeltprøver på et transportbelte. Dette muliggjør en rekke nye applikasjoner for WAI Raman spektroskopi innen kvalitetsdokumentasjon, sortering, prosessanalyse og sanntids prosesskontroll i matindustrien

Analyzing Spring Freeze Impacts on Deciduous Forest Productivity Using MODIS Satellite Imagery

The impacts of an April 2007 spring freeze event on the productivity of deciduous broadleaf forest were analyzed using geographic information system (GIS) tools. Forest productivity was modeled using the Enhanced Vegetation Index (EVI), as recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. Measures of spatial autocorrelation were used to quantify the degree of spatial congruence between a map depicting the severity of the freeze event, and maps modeling forest productivity throughout the year. The results show a geographic correlation between the unseasonably low minimum temperatures sustained during the freeze and the unusually low forest productivity that followed. Discussion also includes the influence on freeze damage of premature growth onset triggered by an unusually warm March 2007, the seemingly paradoxical relationship between spring frost damage and climate change, and the potential for practical applications of this study with regard to predictive modeling and ecological forecasting

Hvordan mestrer sykepleiere over tid å stå i situasjoner med verbale trusler og fysiske angrep i sin arbeidshverdag på en voksenpsykiatrisk akuttavdeling?

Bakgrunn: Forskning viser at det er sykepleiere ved akuttpsykiatriske avdelinger som er mest utsatt for aggresjon og aggressive angrep i sin arbeidshverdag. Forskningsspørsmålet i denne undersøkelsen er derfor: ”Hvordan mestrer sykepleiere over tid å stå i situasjoner med verbale trusler og fysiske angrep i sin arbeidshverdag på en voksenpsykiatrisk akuttavdeling?” Dette for dels å undersøke hva sykepleierne selv oppgir som grunnlag for mestring, og dels for å kartlegge fremtidige tiltak som kan fremme mestring hos denne gruppen. Design: Kvalitativ intervjuundersøkelse av fire sykepleiere med over fire års erfaring i fagfeltet. Det ble utformet en tematisk intervjuguide med spørsmål om arbeidslivshistorie, arbeidserfaring, arbeidssituasjoner, mestring og tilrettelegging på arbeidsplassen. Intervjuene ble tatt opp som lydfil, transkribert og analysert ved å trekke ut meningsbærende enheter, kodet og delt inn i kategorier ut fra funn i teksten. Funn: Informantene oppga viktige faktorer for mestring: De hadde gode kolleger å støtte seg til, ved utvikling av innsikt i seg selv, og høy grad av mestringstro og håndterbarhet i de situasjonene som oppstod og som de var en del av. Konklusjon: Det som førte til mestring hos informantene i denne undersøkelsen er at de gjennom erfaring og kompetanse hadde utviklet stor grad av innsikt i seg selv og av sin rolle i samhandlingen. Informantene viste til høy grad av mestringstro og håndterbarhet i de ulike situasjonene som oppstod. De hadde tro på at deres måte å løse situasjonene på, var den mest hensiktsmessige metoden. Informantene ga uttrykk for at kollegastøtten var uvurderlig, og at ros og anerkjennelse fra kollegene bidro til økt mestring. Kollegene ble oppgitt som motivasjon til å holde ut i jobben.Background: Research has shown that nurses in acute psychiatric wards are those most exposed to aggression and aggressive attacks in their everyday work. The research question of this study is:”How do nurses cope over time in situations with verbal abuse and physical assault in their everyday work at an adult psychiatric acute ward?” The purpose was on one hand to examine what the nurses themselves stated as their basis for coping, and on the other hand to make a survey of possible future interventions that could promote coping in this group. Design: A qualitative interview study of four nurses with more than four years’ experience in the field. A thematic interview guide was developed with questions on work life history, work experience, coping and organization in the workplace. The interviews were recorded digitally, transcribed and analyzed by extracting meaning bearing units, coding and division into categories based on findings in the text. Findings: The informants stated important factors for coping: Good work colleagues for support; development of self-insight; and a high degree of self-efficacy and feeling of manageability in situations that arose and that they were a part of. Conclusion: What lead to coping in the informants of this study was that they had developed a high degree of self-insight and insight in their own role in interaction with patients. The informants indicated a high degree of self-efficacy and feeling of manageability in the different situations that arose. They also had faith in that the way they solved problems was the most appropriate method. The informants stated that support from colleagues was invaluable, and that praise and recognition from colleagues contributed to increased coping. The work colleagues were a motive for staying in the same job.Master i psykisk helsearbei

In-line Raman spectroscopy for characterization of an industrial poultry raw material stream

publishedVersio

Asset Building: Increasing Capacity for Performance Measurement and Effects+B200

Asset Building: Increasing Capacity for Performance Measurement and Effect

Raman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon fillets

Raman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2CV = 0.96 for Raman at 2s exposure and R2CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.publishedVersio

(E)-3-(1-Naphthyl­amino)­methyl­ene-(+)-camphor

In the crystal structure of the title ketoamine {systematic name: (E)-1,7,7-trimethyl-3-[(1-naphthyl­amino)­methyl­idene]bicyclo­[2.2.1]heptan-2-one}, C21H23NO, there are two independent mol­ecules in the asymmetric unit. Both mol­ecules have an E configuration about the alkene function. The main conformational difference between the mol­ecules is in the orientation of the plane of the naphthyl rings with respect to the camphor fragment. The torsion angle about the enamine C—N bond is 21.3 (7)° for mol­ecule A, but −24.4 (8)° for mol­ecule B. Inter­molecular N—H⋯O hydrogen bonds between the amino and ketone groups of adjacent independent mol­ecules sustain the crystal, and the resulting extended chains, containing an alternating sequence of the two independent mol­ecules, run parallel to the [001] direction and can be described by a graph-set motif of C 2 2(12)

The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.publishedVersio

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC). The optimal preprocessing was selected based on the quality of classification models established by partial least squares discriminant analysis for discriminating healthy and damaged cartilage samples. The best results for the sparse data were obtained by preprocessing using a baseline offset correction at 1800 cm−1, followed by peak normalization at 850 cm−1 and preprocessing by MSC.publishedVersio