Chocholáčová, D.: Mask - Face - Facial expression. Theme utilization in pedagogical practice. /Diploma thesis/ Prague 2014 - Charles University, Faculty of Education, department of art education,83 p. Diploma thesis is oriented as a theoretical study and research of mask in prezent form with context of history. In this work mask is understanded as a communication between whole world and one person, when the individuality of person meets uniformity of mass. It deals with phenomenom of masking as a everyday manifestation human being identify with social group with specific culture tradition. Mask contemplates between ritual and fun, by probe of traditions, ceremonials, rituals and carnivals, but also probe of contemporary theatre or art . Diploma thesis also thinks about present position of ritual. Goal of the work is specify everyday human being, his mask, face, facial expression, at the modern world. Pedagogical utilization offers implementation theme to space of nursery school and grammar school offer of topics, mostly realized and reflected. Part of work is together finding theme at preparation and realization gallery education for two exhibitions in Rudolfinum Gallery.

Eftersom att både GNSS GPS och GLONASS har många likheter så finns möjlighet att utnyttja systemen i kombination. Dock föreligger olikheter vilket gör att systemen inte är fullkomlig kompatibla med varandra. Diskrepans i koordinater och tidsram utgör ett stort hinder för att kombinera dessa system. Men lösningar för koordinatstransformering har tagits fram för att eliminera dessa divergenser (Roßbach, 2001) BeiDou GNSS system till skillnad från GNSS GPS/GLONASS är ett av det senaste etablerade navigationssystem, vilket ställer frågor för användare om systemets kvalitéer och brister. Denna studie behandlar väldigt översiktligt om hur BeiDou systemet tillkom och bakgrunden, karaktärer samt ambitionen som är framlagt för systemet. BeiDou som ursprungligen kallades för COMPASS hade inte samma ändamål som GLONASS och GPS att tillfredsställa sina användare med globalt navigationssystem, intentionen med systemet var mestadels för positioneringssystem som skulle användas regionalt och för militära ändamål, men med tiden ökade ambitionen hos tillverkaren och en ny plan alstrades. planen var att satsa på att bli en av världsledande positionering och navigationssystem, och det skulle etableras och utnyttjas världen över. GLONASS och NAVSTARs GPS vilka är stora konkurrenter av produktutveckling inom rymd teknologi, har framställt världens mest noggranna och effektiva satellitsystemen. Även om ändamålen för dessa systemen hade sin utgångspunkt för applikation inom det militära avseende, har de gjort tillgängliga för diverse civil användning. GNSS GPS/GLONASS kan i vissa fall visa brister på uppkopplingshastighet men också mätningsprecision vid användning på egen hand, detta p.g.a. att antalet synliga och uppnåbara satelliter är begränsande. Detta har gett upphov till vidare studier inom systemens karaktärer samt implementering av kombination GNSS GPS/GLONASS. Emedan både systemen tillsammans består av 48 satelliter, att hitta tillfredställande antal satelliter under alla omständigheter underlättas. Systemen innehöll implikationer i sina grundinställningar som försvårar tillämpning av dessa i kombination. Satelliterna skickar information om sina positioner på två olika metoder, PZ-90 för GLONASS och WGS-84 för GPS. Metoderna är väldigt lika varandra med skiljer sig någorlunda i sättet de utför sina beräkningar. Denna skiljaktighet skapades då systemen ej hade som avsikt att samarbeta och eventuellt integrera med varandra vilket gjorde att utvecklingen av båda GNSS gick isär. Detta innebär att transformation av satellitinformation är nödvändigt för att uppnå tillförlitliga lösningar, då GNSS ska sammanställas och användas integrerat.

Introduction: Instrumented gait analysis and inverse dynamics are commonly used in research and clinical practice to calculate lower extremity joint kinetics, such as power and work. However, multisegment foot (MSF) model kinetics have been limited by ground reaction force (GRF) measurements. New technology enables simultaneous capture of plantar pressure and shear stress distributions but has not yet been used with motion capture. Integrating MSF models and pressure/shear measurements will enhance the analysis of foot joint kinetics. The purpose of this study was to develop methodology to integrate these systems, then analyze the effects of speed on foot joint kinetics. Methods: Custom software was developed to synchronize motion capture and pressure/shear data using measured offsets between reference frame origins and time between events. Marker trajectories were used to mask pressure/shear data and construct segment specific GRFs. Inverse dynamics were done in commercial software. Demonstrative data was from 5 healthy adults walking unshod at 3 fixed speeds (1.0, 1.3, and 1.6 m/s, respectively) wearing retroreflective markers according to an MSF model. Plantar shear forces and ankle, midtarsal, and first metatarsophalangeal (MTP) joint kinetics were reported. Speed effects on joint net work were evaluated with a repeated measures ANOVA. Results: Plantar shear forces during stance showed some spreading effects (directionally opposing shear forces) that relatively were unaffected by walking speed. Midtarsal joint power seemed to slightly lag behind the ankle, particularly in late stance. Net work at the ankle (p = 0.024), midtarsal (p = 0.023), and MTP (p = 0.009) joints increased with speed. Conclusions: Functionally, the ankle and midtarsal joints became more motorlike with increasing speed by generating more energy than they absorbed, while the MTP joint became more damperlike by absorbing more energy than it generated. System integration appears to be an overall success. Limitations and suggestions for future work are presented.

In traditional industrial manufacturing, due to the limitations of science and technology, manual inspection methods are still used to detect product surface defects. This method is slow and inefficient due to manual limitations and backward technology. The aim of this thesis is to research whether it is possible to automate this using modern computer hardware and image classification of defects using different deep learning methods. The report concludes, based on results from controlled experiments, that it is possible to achieve a dice coefficient of more than 81%.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19342号 / 情博第594号 / 新制||情||103(附属図書館) / 32344 / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 石井 信, 教授 杉江 俊治, 教授 大塚 敏之 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Den här expositionen visar mitt projekt från utbildningen Master i skådespelarkonst 2021-2023 på SKH i Stockholm. Uppsatsen heter "När vi ses" och den performativa delen "Hur gör vi med publikinsläppet?" Jag har som skådespelare och clown jobbat i många olika rum och med många olika publiköverenskommelser. Allt från scen-salong situationer där publiken vet exakt hur de ska bete sig och hur deras deltagande ser ut, till att spela för endast en person i en sjukhussäng eller i en liten roddbåt, där deltagandet tydligt måste förhandlas och kommuniceras. Jag har mött vuxna som är världsmästare i teateretikett, men inte kan svara på en fråga om den ställs från scenen, och jag har mött barn som är sjövilda förstagångsbesökare som har en intensiv dialog med oss på scenen. Jag är intresserad av dialogen mellan skådespelare och publik och av publikens delaktighet. Vilka normer och överenskommelser regleras det av? Hur påverkar rädslan att göra fel, bryta mot normen, upplevelsen av scenkonstverket? Begränsar den rädslan för skam det som är möjligt på teatern? Jag har också undrat över vilka roller publiken kan ha, vad i ett verk som kommunicerar denna roll, och om publiken kan byta roll i samma verk. I "Hur gör vi med publikinsläppet?" kan du läsa om arbetet med Eva och Margaretha, två halvmasker som båda är skådespelare men i vars konstnärsskap publiken spelar väldigt olika roller. / The essay is called "When we meet" and the performative part "How do we let the audience in?" As an actor and clown, I have worked in many different rooms and with many different audience agreements. Everything from stage-salon situations where the audience knows exactly how to behave and what their participation looks like, to playing for only one person in a hospital bed or in a small rowing boat, where participation must be clearly negotiated and communicated. I've met adults who are world masters of theater etiquette, but can't answer a question if asked from the stage, and I've met children who are wild first-timers who engage in intense dialogue with us on stage. I am interested in the dialogue between actors and audience and in audience participation. What standards and agreements are they regulated by? How does the fear of making a mistake, breaking the norm, affect the experience of the performance? Does that fear of shame limit what is possible in the theater? I have also wondered what roles the audience can have, what in a work communicates this role, and whether the audience can change roles in the same work. In "How do we let the audience in?" you can read about the work with Eva and Margaretha, two half-masks who are both actors but in whose artistry the audience plays very different roles.

The password is the first line of defence in most modern web services, it is therefore critical to choose a strong password. Many previous studies have found patterns to improve in global users password creation but none have researched the patterns of Swedish users in particular. In this project, passwords of Swedish users were gathered from underground forums and analyzed to find if Swedish users create passwords differently from global users and if there are any weak patterns in their passwords. We found that Swedish users often use words or names found in a Swedish NLP corpus in their passwords as well as using lowercase letters more frequently than global users. We also found that several of the most popular Swedish websites use weak password policies which might contribute to Swedish users choosing weak passwords. / Lösenordet är den första försvarslinjen i de flesta moderna nät tjänsterna, det är därför kritiskt att välja ett starkt lösenord. Många tidigare studier har upptäckt mönster som kan förbättras i globala användares lösenord men ingen har tidigare forskat på mönster hos just svenska användare. I det här projektet har vi samlat lösenord av svenska användare från olika undergroundforum och analyserat dem för att ta reda på om svenska användare skapar sina lösenord annorlunda från globala användare och ifall det finns några svaga mönster i lösenorden. Vi fann att svenska användare ofta använder ord eller namn från en svensk NLP korpus i sina lösenord och även att svenska användare använder små bokstäver i högre grad än globala användare. Vi fann även att flera av de mest populära svenska hemsidorna har svaga lösenordspolicys vilken kan bidra till att svenska användare väljer svaga lösenord.

Pest inventory of a field is a way of knowing when the thresholds for pest controlis reached. It is of increasing interest to use machine learning to automate thisprocess, however, many challenges arise with detection of small insects both intraps and on plants.This thesis investigates the prospects of developing an automatic warning system for notifying a user of when certain pests are detected in a trap. For this, sliding window with histogram of oriented gradients based support vector machinewere implemented. Trap detection with neural network models and a check sizefunction were tested for narrowing the detections down to pests of a certain size.The results indicates that with further refinement and more training images thisapproach might hold potential for fungus gnat and rape beetles.Further, this thesis also investigates detection performance of Mask R-CNNand YOLOv5 on different insects in fields for the purpose of automating thedata gathering process. The models showed promise for detection of rape beetles. YOLOv5 also showed promise as a multi-class detector of different insects,where sizes ranged from small rape beetles to larger bumblebees.

Ceramic manufacturing is an expensive process with long lead times between the initial design and final manufactured part. This limits the use of ceramic as a viable material unless there is a large project budget or high production volume associated with the part. Ceramic stereolithography is an alternative to producing low cost parts through the mixing of a photo curable resin and ceramic particles. This is an additive manufacturing process in which each layer is built upon the previous to produce a green body that can be sintered for a fully dense ceramic part. This thesis introduces a new approach to ceramic stereolithography with a top mask projection light source which is much more economical compared to current vector scanning methods. The research goes through the design and development of a stereolithography printer prototype capable of handling ceramics and the testing of different mixtures to provide the best printing results with varying viscosities. The initial testing of this printer has created a starting point for top mask projection as an economical alternative to current ceramic manufacturing techniques.

Background. This Thesis addresses the critical issue of disease management in ricecrops, a key factor in ensuring both food security and the livelihoods of farmers. Objectives. The primary focus of this research is to tackle the often-overlooked challenge of precise disease localization within rice plants by harnessing the power of deep learning techniques. The primary goal is not only to classify diseases accurately but also to pinpoint their exact locations, a vital aspect of effective disease management. The research encompasses early disease detection, classification, andthe precise identification of disease locations, all of which are crucial components of a comprehensive disease management strategy. Methods. To establish the reliability of the proposed model, a rigorous validation process is conducted using standardized datasets of rice plant diseases. Two fundamental research questions guide this study: (1) Can deep learning effectively achieve early disease detection, accurate disease classification, and precise localizationof rice plant diseases, especially in scenarios involving multiple diseases? (2) Which deep learning architecture demonstrates the highest level of accuracy in both disease  diagnosis and localization? The performance of the model is evaluated through the application of three deep learning architectures: Masked RCNN, YOLO V8, and SegFormer. Results. These models are assessed based on their training and validation accuracy and loss, with specific metrics as follows: For Masked RCNN, the model achieves a training accuracy of 91.25% and a validation accuracy of 87.80%, with corresponding training and validation losses of 0.3215 and 0.4426. YOLO V8 demonstrates a training accuracy of 85.50% and a validation accuracy of 80.20%, with training andvalidation losses of 0.4212 and 0.5623, respectively. SegFormer shows a training accuracy of 78.75% and a validation accuracy of 75.30%, with training and validation losses of 0.5678 and 0.6741, respectively. Conclusions. This research significantly contributes to the field of agricultural disease management, offering valuable insights that have the potential to enhance crop yield, food security, and the overall well-being of farmers