Stiffer optical tweezers through real-time feedback control

Using real-time re-programmable signal processing we connect acousto-optic steering and back-focal-plane interferometric position detection in optical tweezers to create a fast feedback controlled instrument. When trapping 3 µm latex beads in water we find that proportional-gain position-clamping increases the effective lateral trap stiffness ~13-fold. A theoretical power spectrum for bead fluctuations during position-clamped trapping is derived and agrees with the experimental data. The loop delay, ~19 µs in our experiment, limits the maximum achievable effective trap stiffness

Unintended consequences of changes in the regulatory landscape on the statutory audit processNie

We examine the effect of changes in the regulatory environment on the conduct of financial statement audits in a European setting. These changes include the adoption of risk-based auditing, new Audit Risk Standards and increased scrutiny of audit quality by a new, co-ordinated oversight body in each Member State. We investigate this by analysing the audit hours and fees and their determinants for clients of Big N audit firms in Finland in 1996 and 2010. Our results show that audit fees and audit effort by senior auditors were generally higher for high risk clients in 2010 than in 1996. Second, we find that the relationship in 1996 between the client being owner-managed and lower audit hours for both senior and junior auditors is absent in 2010. This supports our argument that the increased auditor scepticism has increased audit effort for owner-managed firms. Third, we find that the average number of junior staff hours increased between 1996 and 2010, but the variance across engagements declined. In contrast, senior auditor hours (and total audit hours) decreased, but the variance across engagements increased. This supports the view that risk-based auditing has increased the efficiency of audits. However, it suggests that the general increase in regulation and the tightening of audit standards, reinforced by the new quality inspections, have led to less emphasis on processes requiring professional judgment and more emphasis on compliance with rules. These unintended consequences should be of interest to the auditing profession and policy makers

Carbon dynamics in a Boreal land-stream-lake continuum during the spring freshet of two hydrologically contrasting years

We studied in 2013 and 2014 the spring carbon dynamics in a Boreal landscape consisting of a lake and 15 inflowing streams and an outlet. The first year had weather and a hydrological regime typical of past years with a distinct spring freshet connected with the thaw of the average snowpack. The latter year had higher air temperatures which did not permit snow accumulation, despite similar winter precipitation. As such, there was hardly any spring freshet in 2014, and stream discharge peaked in January, i.e., the conditions resembled those predicted in the future climate. Despite the hydrological differences between the years, there were only small interannual differences in the stream CO2 and DOC concentrations. The relationship between the concentrations and discharge was stronger in the typical year. CO2 concentrations in medium-sized streams correlated negatively with the discharge, indicating dilution effect of melting snowpacks, while in large-sized streams the correlation was positive, suggesting stronger groundwater influence. The DOC pathway to these streams was through the subsurface soil layers, not the groundwater. The total amount of carbon transported into the lake was ca. 1.5-fold higher in the typical year than in the year with warm winter. In 2013, most of the lateral inputs took place during spring freshet. In 2014, the majority of inputs occurred earlier, during the winter months. The lateral CO2 signal was visible in the lake at 1.5 m depth. DOC dominated the carbon transport, and in both years, 12% of the input C was in inorganic form.Peer reviewe

MinMax Radon Barcodes for Medical Image Retrieval

Content-based medical image retrieval can support diagnostic decisions by clinical experts. Examining similar images may provide clues to the expert to remove uncertainties in his/her final diagnosis. Beyond conventional feature descriptors, binary features in different ways have been recently proposed to encode the image content. A recent proposal is "Radon barcodes" that employ binarized Radon projections to tag/annotate medical images with content-based binary vectors, called barcodes. In this paper, MinMax Radon barcodes are introduced which are superior to "local thresholding" scheme suggested in the literature. Using IRMA dataset with 14,410 x-ray images from 193 different classes, the advantage of using MinMax Radon barcodes over \emph{thresholded} Radon barcodes are demonstrated. The retrieval error for direct search drops by more than 15\%. As well, SURF, as a well-established non-binary approach, and BRISK, as a recent binary method are examined to compare their results with MinMax Radon barcodes when retrieving images from IRMA dataset. The results demonstrate that MinMax Radon barcodes are faster and more accurate when applied on IRMA images.Comment: To appear in proceedings of the 12th International Symposium on Visual Computing, December 12-14, 2016, Las Vegas, Nevada, US

Digitalisaation hyödyntäminen syöpäpotilaan ohjaamisessa

Tiivistelmä. Tämän tutkielman tarkoituksena on kuvata, millaisin menetelmin digitalisaatiota voidaan hyödyntää syöpäpotilaan ohjaamisessa. Tutkielman tavoitteena on tuottaa tietoa syöpäpotilaan hoitotyötä varten eri menetelmistä hyödyntää digitalisaatiota potilasohjauksessa. Tutkielma toteutettiin kuvailevana kirjallisuuskatsauksena ja tutkielman aineiston tiedonhaku toteutettiin maaliskuussa 2020 neljään eri tietokantaan: CINAHL, Medic, Scopus ja ProQuest. Sisäänottokriteerien perusteella tutkielmaan valikoitui aineistoksi viisi kansainvälistä vertaisarvioitua artikkelia. Aineisto analysoitiin aineistolähtöisellä sisällönanalyysilla ja tulokset esiteltiin narratiivisen synteesin avulla. Tutkimustulosten mukaan digitalisaatiota voidaan hyödyntää syöpäpotilaan ohjaamisessa videoiden, internetsivustojen ja mobiilisovellusten avulla. Digitalisaation avulla syöpäpotilaan ohjaamista voidaan tehostaa ja yhtenäistää. Sen avulla voidaan myös säästää hoitajien aikaa muuhun hoitotyöhön. Tieto syövästä ja sen hoidosta tulisi olla luotettavaa ja näyttöön perustuvaa. Sekä potilaat että hoitohenkilökunta kokivat tarpeelliseksi sen, että tieto on helposti saatavilla. Videot ovat mukautuva ohjauskeino sallien toiston ja kotona katselun ja ne vastaavat syöpäpotilaiden yksilöllisiin tarpeisiin. Videoita pystyttiin katsomaan sairaalan osastoilla, poliklinikalla ja kotona. Syöpäaiheinen opetuksellinen sisältö tulisi olla terveydenhuollon organisaatioiden ja syöpäjärjestöjen internetsivuilla. Potilaiden ohjaaminen luotettavan tiedon pariin parantaa potilasohjauksen sisältöä ja potilaiden tyytyväisyyttä saadusta tiedosta. Vaikka tutkimuksista saatiin positiivisia kokemuksia digitalisaation hyödyntämisestä syöpäpotilaan ohjaamisessa, syöpäpotilaat yhä arvostivat kasvokkain saatua ohjausta. Syöpäpotilaiden määrän kasvaminen sekä syöpähoitojen siirtyminen yhä enemmän poliklinikoille edellyttää potilaiden vastuun lisäämistä ja osallistumista päätöksentekoon hoidoistaan. Hoitoaikojen lyhentyessä syöpäpotilaan ohjaamista on tehostettava. Tämä vaatii hoitajilta ohjaamiskeinojen päivittämistä sekä digitaalisten teknologioiden ottamista osaksi ohjausta

The administration of an inter-disciplinary feasibility study, designed as a performance based dissertation in educational administration.

Abstract not availabl

Expanding the Family of Grassmannian Kernels: An Embedding Perspective

Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean geometry, but lie on a special type of Riemannian manifolds known as Grassmannian. To leverage the techniques developed for Euclidean spaces (e.g, support vector machines) with subspaces, several recent studies have proposed to embed the Grassmannian into a Hilbert space by making use of a positive definite kernel. Unfortunately, only two Grassmannian kernels are known, none of which -as we will show- is universal, which limits their ability to approximate a target function arbitrarily well. Here, we introduce several positive definite Grassmannian kernels, including universal ones, and demonstrate their superiority over previously-known kernels in various tasks, such as classification, clustering, sparse coding and hashing

Face Detection with Effective Feature Extraction

There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for frontal face detection. In this work, we show that simple features other than Haar-like features can also be applied for training an effective face detector. Since, single feature is not discriminative enough to separate faces from difficult non-faces, we further improve the generalization performance of our simple features by introducing feature co-occurrences. We demonstrate that our proposed features yield a performance improvement compared to Haar-like features. In addition, our findings indicate that features play a crucial role in the ability of the system to generalize.Comment: 7 pages. Conference version published in Asian Conf. Comp. Vision 201

A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page