Automatically detecting events for people with diabetes mellitus using continuousglucose monitors is an important step in allowing insulin pumps to automaticallycorrect the blood glucose levels and for a more hands-off approach to thedisease. The automatic detection of events could also aid physicians whenassisting their patients when referring to their continuous glucose monitordata. A range of different deep learning algorithms has been applied forpredictions of different events for continuous glucose monitor data, such asthe onset for hyperglycemia, hypoglycemia or mealtime events. This thesisfocused on constructing sequences labelled from an unbalanced and assumedmisslabelled dataset to classify them as such using four different deep learningnetworks using convoluted neural networks and recurrent neural networks.Manual correction of the dataset allowed for only clear events starting witha high positive gradient to be labelled as positive. The classification wasperformed on exact timepoints and in time windows to allow the classificationto to be done around the beginning of an event instead of the exact timepoint.The results from using the unbalanced and assumed misslabelled datasetshowed the networks performing similarly, with high Recall and Precisionbelow 0.5, thus not found to be of use in a for automatic event detection.Further testing by using another dataset or further configurations is neededto clarify the capabilities of automatically detecting events. DDAnalytics willnot use any of the developed networks in any of their products. / Automatisk detection av event för personer med diabetes från deras kontinuerligaglukosmätare är ett viktigt steg för att låta insulinpumpar automatiskt korrigeraglukosnivåer och möjliggöra en mindre självreglering av personens diabetes.Denna automatiska detektion skulle även kunna hjälpa läkare vid samtalmed patienter och deras data från kontinuerliga glukosmätarna. En mängd avolika djupinlärningsalgoritmer har använts för förutsägelser av olika event förkontinuerlig glukosmätardata, som början av hyperglykemier, hypoglykemiereller måltider. Detta examensarbete fokuserar på skapandet av sekvenserfrån ett obalanserat och antaget inte helt korrekt markerade event i dataset,för att kunna klassificera dessa event med fyra olika djupinlärningsnätverk.Dessa nätverk bygger på konvolution och rekursiva neurala nätverk. Manuellkorrektion av datasetet möjliggjorde så att endast tydliga event som börjar meden kraftig positiv ökning av gradienten var markerade som positiva event.Klassificeringen genomfördes på både exakta tidssteg och i tidsfönster såatt början av event kunde detekteras snarare än bara det exakta tidssteget.Resultaten genom användandet av detta tidigare nämnda dataset visade liknanderesultat för samtliga nätverk, med hög Återkallelse och Precision under 0.5.Dessa resultat ledde till att nätverken inte kan antas kunna utföra automatiskevent detektion, och skulle behöva ytterligare testning på ett annat dataset medmer korrekta markerade event eller ytterligare konfigureringar på nätverken föratt verifiera dessas möjligheter att automatiskt klassificera event i kontinuerligglukosdata. DDanalytics kommer inte använda något av dessa framtagnanätverk i några av deras produkter.

As unmanned air vehicle (UAV) utilization increases in Wilderness Search and Rescue (WiSAR) efforts, onboard sensors yielding more information will be desired. UAVs can assist WiSAR efforts by accelerating the ground search process through returning quality aerial footage of the terrain. Additionally, tracking the progress of a search by populating a digital map with video resolution data increases confidence that a comprehensive search of the region has been made. This thesis presents methods for acquiring video from multiple video sensors and fusing them into a single rendered video stream as a Virtual Gimbal. The panoramic video stream is the first of its kind to be constructed from video transmissions from a small UAV, and the first known video panorama to be used to quickly survey a region within a WiSAR context. The Virtual Gimbal comprises two video transmissions from a three camera array mounted in a downward-looking configuration on a UAV. This video stream has been shown to decrease the amount of time required to thoroughly survey a region by more than 40 percent.

The thesis deals with design of configuration software, ConfPix, for radiationdetecting sensor - SpacePix2. It describesdesign and implementation, as well as thetesting procedure. The software is implemented in Python, with Graphical UserInterface created using the Tkinter module for Python. The application is designed as versatile and can be used in future missions requiring the configurationof pixel radiation detectors from SpacePixfamily. The SpacePix2 sensor is a new technology developed at the Faculty of Nuclear Sciences and Physical Engineeringat Czech Technical University in Pragueand will be tested in orbit as a part of theSpace Dosimetry System Demonstrator instrument developed by the esc Aerospaces.r.o. company. Cosmic radiation sources and radiation detectors are described in the theoretical part of the thesis. The SpaceDosimetry System Demonstrator instrument, SpacePix Radiation Monitor detector and the SpacePix2 sensor are described as well.

Cyber-physical systems (CPSs) are used in several industries, such as healthcare, automotive, manufacturing, and more. The fact that CPSs often contain components integrated via communication networks means that malicious actors can exploit vulnerabilities in these components through cyber attacks. CRYSTAL Framework has been shown in previous research to be able to detect cyber attacks on CPSs. However, this has only been proven in simulation. Our research builds upon these previous research as we aim to prove that CRYSTAL Framework is a viable method for monitoring real systems to detect abnormal behaviours.  The Tiny Twin is an abstract behavioral model that defines normal running behaviour of a system, which can then be used by to compare the current state of a monitored system to detect possible attacks and abnormal behaviours. We built a monitor that integrates such a Tiny Twin, working by passively listening on input and output of components in a monitored system. We designed and implemented two different scenarios, a security alarm system and a temperature control system (TCS), to test the CRYSTAL Framework. In testing both implemented scenarios our monitor successfully detected all but one attacks during runtime by comparing the system's current state with the expected state as defined in the Tiny Twin.

No description available.

No description available.

Sleep is very important for health and academic performance. The amount of sleep is variable and depends among other things, on the age of the individual. Today there are many varieties of motion sensors that can be used in healthcare and clinical research for sleep registration, such as Actigraph GT9X Link and Actiwatch 2. The purpose of this study was to compare these two sensors, Actigraph and Actiwatch, for sleep registration by analyzing different sleep variables. The more precise sensor of the two will be used in the Energymetabolic laboratory in the case of survey or research. The method involved participants wearing both sensors for two nights and one day and trying to live as normal as possible. A sleep diary was used to complete the registrations, with related questions about sleep. There were 17 healthy participants between the ages 21 and 31. The results showed that the registrations from both sensors have varying spread and deviations. Overall the results were similar between the sensors and the sleep diary, and it was shown that there is no significant difference between the sensors. However, Actigraph deviated on most occasions from the diary. The Energymetabolic laboratory have access to many Actigraph GT9X Link sensors. This means that an evaluation has to be made to decide whether the cost of replacing the Actigraph GT9X Link sensors with Actiwatch 2 is worth it for the small improvement in precision.

Hintergrund Die Gabe von Opioiden zur Schmerzunterdrückung spielt eine zentrale Rolle in der modernen Anästhesiologie. Messungen von Hypnosetiefe und Muskelrelaxierung sind im Gegensatz zur Schmerzmessung seit Jahren etabliert. Seit Kurzem ist das PMD200 („Pain Monitoring System“; Fa. Medasense Biometrics™ Ltd., Ramat-Gan, Israel) verfügbar. Dieser Schmerzmonitor misst nichtinvasiv und errechnet einen dimensionslosen Schmerzindex („nociceptor level“, NoL). Die Validität und Zuverlässigkeit des Verfahrens sind Gegenstand von klinischen Studien. Fragestellung Reduziert die Verwendung des PMD200 die Gabe von Analgetika während einer Da-Vinci-Prostatektomie? Material und Methoden In die Studie wurden 50 Patienten aufgenommen. Nach gewichtsadaptierter Sufentanilgabe zur Narkoseinduktion und einem 10 µg Bolus vor Hautschnitt erfolgte die intraoperative Analgesie durch subjektive Entscheidung (CONT) oder aufgrund eines erhöhten NoL-Index (INT). Die statistische Auswertung erfolgte durch Mann-Whitney-U-, Kolmogorow-Smirnow-Test und Levene-Statistik. Ergebnisse In der INT-Gruppe war die Anzahl der Sufentanilboli/h nicht signifikant geringer als in der CONT-Gruppe (p = 0,065). Die Varianz der Sufentanilgaben unterschied sich signifikant (p = 0,033). In der CONT-Gruppe war die Applikation normal verteilt (p = 0,2), in der INT-Gruppe hingegen nicht (p = 0,003). Diskussion Eine mögliche Interpretation der Daten ist, dass die Schmerzmittelgabe in der INT-Gruppe individualisierter erfolgte, d. h., es wurden nichterforderliche Schmerzmittelgaben vermieden, und gleichzeitig detektierte das NoL-Monitoring einzelne Patienten mit deutlich erhöhtem Schmerzmittelbedarf. Diese Schlussfolgerung ist nur unter der Voraussetzung zulässig, dass das PMD200 auch tatsächlich die Entität Schmerz misst. / Background Administration of opioids to suppress pain plays a major role in modern anesthesia. Measuring depth of hypnosis and neuromuscular recovery are already well established, and devices for pain monitoring are available. Nonetheless pain monitoring is rare in clinical practice. Recently, the pain monitoring device PMD200 (Medasense Biometrics™ , Israel) was introduced. It non-invasively measures heart rate, heart rate variability, skin resistance, resistance variability, temperature and movement to calculate a nociception level (NoL) index. The NoL index range starts at zero, which is equivalent to being painless, and goes up to a value of 100. The validity and reliability of NoL monitoring is the content of current studies. Objective We tested the hypothesis if the use of the PMD200 significantly reduces opioid consumption during da Vinci prostatectomy. Material and methods A total of 50 male patients were included in this randomized, single blinded study. Exclusion criteria were arrhythmia because the pain monitoring device requires a sinus rhythm for reliable results. Patients received a weight-adjusted sufentanil bolus (0.3 µg/kg ideal body weight) during induction of anesthesia. Additionally, they received 10 µg of sufentanil before skin incision. Both groups received total intravenous anesthesia with propofol and continuous muscle relaxation through cis-atracurium. In the control group (CONT; n = 26), a standardized sufentanil bolus of 10 µg were administered by common criteria (heart rate/blood pressure increase, lacrimation, gut feeling) at the anesthesiologistʼs discretion. In the intervention group (INT; n = 24), patients received the standardized sufentanil bolus when the NoL index was above 25 for 2 min, which corresponds to the manufacturerʼs recommendation. The NoL index and bolus administrations were recorded for every patient. In the control group, the display of the pain monitor showing the NoL index was not visible for the anesthesiologist. Postoperatively, pain/nausea scores and piritramide consumption were taken every 10 min for 1h in the recovery room. None of the patients had prior chronic pain with long-term use of painkillers. Statistics were done using Mann-Whitney U‑test, Kolmogorov-Smirnov test and Levene test. Results Sufentanil bolus administrations, normalized for duration of surgery, were not significantly lower in the intervention group (p = 0.065). We noticed a significant difference in variation of opioid administrations (p = 0.033). Sufentanil boluses per hour in the INT were normally distributed (p = 0.2), whereas in CONT they were not (p = 0.003). Postoperative data like nausea, opioid consumption and pain scale showed no differences between groups. Conclusion The use of PMD200 did not significantly reduce cumulative opioid consumption. Following on we must reject the initial hypothesis. The difference in sufentanil bolus variances may point to an individualized antinociceptive therapy when NoL monitoring is used. We suppose patients with high opioid demands are detected and patients with low opioid demands did not receive unnecessary opioids. This assumption is only true if the PMD200 measures the entity pain. Further studies with more participants during surgery with higher tissue damage could lead to more convincing data and conclusions.

Nordic Development Finance Institutions (DFIs) play an important role in providing sustainable development for Africa which accordance with their mandates.  By investing in private equity Funds in Africa, investee companies have covered various sectors inAfricawhich may not only improve economic development but also increase employment. Additionally, investing in a Fund can spread risk through diversifications and help DFIs to share knowledge with Fund manager in local presence.   This study analyzes the management control systems (MCS) of DFIs’ investing in private equity Funds, wherein we mainly focus on output control and behavior control which are two types of control widely discussed in previous research and literature. Hereby we set three hypotheses based on our research and get findings to support the research questions, which are: 1.      DFIs use output control mechanism with contractual framework to secure their investment. Output control sets standards as to targets. It plays a fundamental role in the control process, as the contractual framework is short of standardized in private equity industry and Fund managers are selected strictly during screening process.   2.      DFIs use behavior control to interact with Fund managers. Behavior control means appropriate instruction and guidelines imposed as results become foreseeable during the monitoring process. It becomes a central element where DFIs have to interact with Fund managers to track the investment progress & development effect, including investment decision making.   3.      DFIs’ syndicated investment affects their control activities. Nordic DFIs’ investment strategy is making co-investment in Funds. When more parties are involved, the monitoring and control process become different compared with only one investor and it is affected by syndicated investment. While we did not deeply explore the control mechanism and process under syndication investment by either quantitative & qualitative method or case studying approach, we conclude that it does exist based on communication with interviewees.   The word “Control” looks like a bureaucratic word. However, we found that Alignment is essential in control process for each partners while behavior control helps to assure the alignment. We think that control process become less difficult when previous strict selection of trust partner is successful. We suggest that the alignment between DFIs and other investors as well as Funds should be strengthened in the control process, so that investment objectives can be well realized.   Besides Nordic DFIs, Africa also benefits from others such asChina’s “going global” strategy to encourage outward FDI. China-Africa Development Fund (CADFund) is the first Fund focused specially on large scale investment in Africa among Private Equity Funds inChina. China Development Bank (CDB) is the shareholder of CADFund, who provide resources and support to CADFund. By briefly comparing Nordic DFIs and CADFund, we found they use similar investment instruments and also similar strategies, such as investment in less developed countries inAfricato improve economic conditions, support home companies investing in Africa etc. Including an analysis on CAD as well as the comparison with Nordic DFIs not only strengthen the understanding of DFIs’ activities in Africa, but also clarify the different investment characteristics of Western and Eastern investors in Africa. We also suggest that Nordic DFIs and CADFund can share experience and knowledge to promote sustainable development for Africa. / Nordic Development Finance Institutions (DFIs) spelar en viktig roll för att skapa en hållbar utveckling för Afrika i linje med dess mandat. Genom att investera i private Equity-fonder i Afrika har investeringsföretagen täckt olika sektorer i Afrika, något som inte bara kan förbättra den ekonomiska utvecklingen, utan även öka sysselsättningen. Dessutom kan investering i fonder sprida risker genom diversifiering och hjälpa instituten för DFI att sprida kunskaper från fondförvaltare på lokal närvaro. Denna studie analyserar ledningskontrollsystemet för DFIs’ investeringar i private Equity-fonder och vi fokuserar främst på produktions- och beteendekontroll, Dessa är de två typer av styrning som allmänt diskuteras i tidigare forskning och litteratur. Härmed ställer vi upp följande tre hypoteser som är baserade på relevant forskning och slutsats för att stödja nedslående hypoteserna: 1. DFIs använder en produktionskontrollmekanism med avtalsram för att säkerställa sina investeringar. Produktionskontroll-mekanismen är en metod som sätter standard enligt målet. Denna metod fungerar som den mest grundläggande i kontrollprocessen, eftersom avtalsramarna redan är standardiserade i privata Equity-fonder och fondförvaltaren är omsorsgsfullt valda i den initiala urvalsprocessen. 2. DFIs använder kontroll av beteende för att interagera med fondförvaltare. Beteendekontroll används beroende på utfall av investesteringen, och i denna kontrollprocess verkställs lämpliga instruktioner och riktlinjer efter resultat. DFI och fondförvaltaren samarbetar här för att följa investeringsprocessen och utvecklingseffekten, däribland också att fatta investeringsbeslut. 3. DFIs' saminvesteringar i fonder kommer att påverka dess kontrollverksamhet. DFI investeringsstrategier är att göra saminvesteringar i fonder. När flera partier är inblandade blir spårande- och kontrollprocessen annorlunda jämfört med endast en investerare och detta är påverkad av sammarbetsinvesteringar. Även om vi inte gjorde en djup undersökning av kontrollmekanism och processen under sammarbetsinvestering gällande kvantitativ och kvalitativ metoder eller fältstudier. Men vi sammanfattar detta att det existerar via kommunikation med intervjuer i föreliggande studie kan vi sammanfattningsvis slå fast att styrningen via fonder påverkas av att en DFI inte ensamt investerar i en fond. Ordet "kontroll" (på svenska snarare ”styrning”) kan låta byråkratiskt, men vi kommer fram till att kontrollprocessen huvudsakligen sker i samförstånd för varje part, medan beteendekontroll underlättar samförståndet. Vi tror att kontrollprocessen blir mindre komplicerad när val av godtrogna parter lyckas. Vi föreslår ett utökat samarbete mellan DFIs och andra investerare och fonder under kontrollprocessen, så att investeringsmålen kan uppnås. Förutom investeringar från nordiska DFIer drar Afrika också fördel av andra initiativ, såsom Kinas "going global"-strategi för att uppmuntra direkta utlandsinvesteringar. Den Kinesisk-Afrikanska Utvecklingsfonden (CADFund) är den första fonden som fokuserar speciellt på strategiska investeringar, med det största antalet private Equity-fonder i Kina, medan Kinesiska utvecklingsbanken (CDB) är aktieägare till CADFund, och förser fonden med resurser och stöd. Genom en kort jämförelse av Nordic DFIs och CADfund fann vi att liknande investeringsinstrument med samma strategi används, såsom investering i mindre utvecklade länder i Afrika för att förbättra de ekonomiska villkoren, hjälpa företag från respektive hemland att investera i Afrika etc. Detta kan också stärka förståelsen för DFIs verksamhet i Afrika. Vi har valt att även analysera CADFund samt göra en jämförelse med de nordiska DFIs, vilket inte bara stärkt vår förståelse av DFIernas aktiviteter i Afrika, men också hjälpt till att förstå och klargöra skillnader mellan investerare från väst respektive öst när det gäller investeringar i Afrika. Vi föreslår även att nordiska DFIs och CADfond kan dela erfarenhet och kunskap för främjande av den hållbara utvecklingen i Afrika. / 摘  要      北欧发展金融组织构成了为非洲提供可持续发展的重要组成部分，这也符合其运作的使命。通过投资在非洲的私募股权基金，受资公司覆盖非洲的各行业，这不仅促进了当地经济的发展，而且也增加了就业机会。与此同时，投资于基金能够分散风险，并且北欧金融组织能够和当地的基金经理分享投资经验与知识。 本文分析了北欧发展金融组织投资私募股权基金采用的管理控制流程，我们重点研究产出控制和行为控制，这两种控制方法在以前的研究和文献中也被广泛提及。同时我们基于相关理论提出三种假设并得出结论来支持研究问题，它们是：   1.北欧发展金融组织采用产出控制方法及一系列合同及框架条款来保证他们的投资.    产出控制指的是一种根据目标设立标准的控制方法，它在控制控制中起着基础性的作用，因为合同条在这个行业已经基本标准化，而且它们在筛选基金经理时有严格的条件。    2.北欧发展金融组织采用行为控制方法来影响制约基金经理。     行为控制指当结果可以预知时，在控制过程中采用适当的规范和准则.当北欧发展金融组织与基金经理互动来跟踪投资进展，发展效应，以及做投资决定时，它就变得至关重要。   3.北欧发展金融组织的联合投资将会影响到他们的控制行为。      北欧发展金融组织的投资策略是与其他组织共同投资于基金。当多方参与时，跟踪和控制流程就与只有一个投资者参与时不一样，而且其受联合投资的影响。虽然我们没有用定性和定量的方法甚至案例来深入研究在联合投资下的控制机制和流程，但是根据多方面的采访我们认为这个影响确实存在。       “控制”一词虽然听起来官僚，但是我们发现在控制流程中各方的精诚合作至关重要，同时行为控制也能加强这种合作。在这种情况下，我们认为在前期选择好合作伙伴后控制流程就变得相对简单。我们的建议是北欧发展金融组织和其他投资者以及其与基金的合作应该加强，从而实现更好的投资目标。       除了北欧发展金融组织外，非洲也受益于中国的“走出去”对外投资战略。中非发展基金是第一只也是中国最大的专注于非洲投资的私募股权基金。国家开发银行（国开行）是中非发展基金的股东,它可以为该基金提供项目资源与支持。通过对北欧发展金融组织和中非发展基金的简单对比，我们发现他们采用类似的投资工具和策略, 比如投资于非洲的不发达国家来改变当地的经济状况,支持本国企业在非洲投资等.这也将加强读者对北欧发展金融组织在非洲的认识。我们同时也建议北欧发展金融组织和中非发展基金之间能交流投资经验和知识来更好地推动非洲的可持续发展。

台灣地區地層下陷問題肇始於六十年代迄今已逾三十餘載，持續下陷面積已達1,194平方公里，最大累積下陷量達到三公尺以上。而目前地層下陷地表監測所採用的傳統水準測量耗費人力、時間較多，且不易獲得連續和全面性之地層下陷資料，目前國內水利單位限於人力時間，無法針對所有監測區域每年皆施測一次。近年來由於空載光達測量技術興起，其具有短時間內獲取大區域高密度、高精度高程資料的特性，因此本研究之目的在探討如何利用空載光達測量技術快速獲取高精度之三維點雲資訊，進行大區域的地層下陷監測及其成效。 研究方法係首先將監測區內掃瞄的光達點雲資料進行網格化分群；接著，計算網格區域內所有光達點擬合平面的中心高程；然後，以人工或自動方法萃取出平坦、穩固的網格區域做為監測面；最後，進行不同時期網格監測面高程差異之統計測試分析，以求出地層下陷量。 實驗結果顯示改善點雲高程精度至5公分以內後，經由網格監測面的精度、坡度、坡向、反射強度、道路範圍等為門檻值，可萃取出80%以上正確率的穩固監測面，且其高差成果與長期監測成果的平均值差異在1.3公分至2.9公分之間，由此成果可以說明本研究成果對建立一套省時省力的監測模式，進而達到地層下陷監測自動化的目的有相當幫助。 / The issue of land subsidence in Taiwan has been concerned for over 30 years since 1970. Land subsidence area has been already over 1194 km2, the maximum amount of accumulative subsidence is more than 3 meters. The conventional leveling for the land subsidence monitoring is labor-intensive and time-consuming, so that the Water Resources Agency could not monitor all the subsidence area every year. Airborne LIDAR technology was developed in recent years, it has the characteristics of collecting 3-D point data at the high density and high elevation accuracy in short time. The purpose of this study, therefore, is to discuss how to utilize the airborne LIDAR technology to monitor the land subsidence. The proposed approach, therefore, is first to divide the collecting DSM points in the monitor area into regular grids. Secondly, all the points in the regular grids are fitted to one set planar parameters by least squares principle and the centric elevation of each grid is calculated. Third, the flatness and well-defined planar grids are selected as the monitoring surfaces with the manual or automatic method. Finally, the difference of centric elevation in each monitoring surfaces at different period is calculated and analyzed with statistical approach. This study shows that after refining the elevation accuracy of point clouds within 5 cm, our approach can extract stable monitoring surfaces by limiting planar fitting accuracy, flatness, slope, intensity, or by using road information. The extracted correct rate can be more than 80%. The discrepancy of elevation difference between this study and long-term monitoring result is between 1.3 cm and 2.9 cm. It proves the proposed approach is helpful on constructing the monitoring model in timesaving and efficient way, and our proposed approach has the potential for developing automatic land subsidence monitoring method.