abstract: In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings. The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented. Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring. A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results. State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

Rapid determination of drugs effective against bacterial strains is critically important to stopping further spread of an infection and reducing antibiotic resistance. Antimicrobial susceptibility testing (AST) is done to determine what type of antibiotic and what concentration will be effective in treating an infection. Current, growth-dependent, AST methods are reliant on the growth rate of the bacteria and can take several days to several weeks to get results. A piezoelectric plate sensor can be used to measure an instant change in the minute physiological stresses of the bacteria cells when they are exposed to an effective concentration of antibiotic. This work aims to investigate the feasibility of piezoelectric plate sensors used for instantaneous AST (iAST) results and develop a technological framework for scaling this technology to a clinical lab setting. Four Clinical and Laboratory Standards Institute (CLSI) quality control strains of bacteria were tested with a wide range of antibiotics from various drug classes using the piezoelectric sensor. Results were obtained within 30 minutes and compared to standard of care AST methods used in clinical labs, and CLSI prescribed ranges for each strain of bacteria. This thesis will also discuss a framework for developing more scalable sensors, and challenges associated with the different sensor designs.

Reflection is one of the most important factors that affects learning. A good learning strategy is supposed to improve a learner's reflection level. In addition, the past studies has proved u-learning can enhance learning performance, motivation and efficiency of learners. This study integrates these into learning activity of distinguishing vegetation, let learner reflect in u-learning environment. Almost of past researches promoted learners¡¦ reflection was by text-based. However, the limit of learning activity's character and mobile device¡¦s screen, the design of text-based promotes is confined. Therefore, this study proposes a video-based reflection prompts strategies in high media richness, and the Context-Aware Reflection Prompt System (CRPS) can detect learner¡¦s location by QR Code to provide appropriate guidance, facilitating learner to observe and reflect. Further to explore effects of reflection level and satisfaction between video-based and text-based reflection prompt strategies. This study recruited 70 college students to participate in this experiment, and divide into two groups of video-based and text- based reflection prompts. The results showed that the reflection level of the video-based reflection prompt group is significantly improved than of the text-based reflection prompt group; however, there was no differences found on the satisfaction. In addition, this study further investigated the learners¡¦ opinions and perspectives toward a video-based and a text-based reflection prompt strategy, and interviewed some learners to obtain the potential factors which may affect satisfaction.

The area of the research comprises the field of virtualization as specified to the field of three-dimensional user interfaces (3D UIs). It is an approach of applying the field of motion-sensing technology to potential areas of apparel value chains focusing on design. The background of this thesis is the industry’s established 3D design and development process and new digital tools that enable embodied interaction. So far companies are still working with a limited 3D design approach, which requires several non-value-adding activities, e.g. technical sketching and pattern creation, before a product can be virtually simulated and evaluated. As the current fashion industry’s human-computer interaction (HCI) applications have non-embodied interaction technologies, which deny natural hand movements, it was evaluated, if motion-sensing technology can enable the feeling of natural handcrafting. The purpose of the project was to investigate the designer’s attitude towards motion-sensing technology as a design tool and the potential of embodied HCI in design and development processes of apparel value chains. Enabling the designer the feeling of handcrafting in a 3D world opens a new area of research within the use of 3D fashion design tools. Moreover the thesis expected to prove the desire towards embodied interaction during the apparel design and development processes and the designer’s openness to try out new things. To fulfill the purpose, the motion-sensing technology tool Leap Motion was used as a practical device, which enables embodied interaction in design applications. A team of various designers was used to conduct a practical experiment, combined with interviews and observations. The experiment has been analysed on the designer’s attitude towards the use of a motion-sensing technology tool within the design field and possible implications on the design and development phases of apparel value chains. The results show, that the designers supported embodied interaction and experienced the use of motion-sensing technology as an enhancing and powerful tool. However, it has become clear that the designers experienced the usage of free-handed motion-sensing technology as not natural or intuitive and rather prefer tangible tools. Presupposing a crucial improvement of the technology, different ways of substituting current design activities like enabling the draping process on a virtual basis could enhance the value chain regarding speed, flexibility and waste. This would enable earlier entry into the evaluation stage of virtual simulated prototypes while directly starting the design and development process in 3D and reducing several iterations of non-value adding activities.

Thesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2017. / Real-time remote monitoring of Africa’s resources, such as water quality, by using terrestrial sensors is impeded by the limited connectivity over the vast rural areas of the continent. Without such monitoring, the effective management of natural resources, and the response to associated disasters such as flooding, is almost impossible. A constellation of nanosatellites could provide near real-time connectivity with ground-based sensors that are distributed across the continent. This study evaluates the high level development of a mission design for a near real-time remote monitoring CubeSat constellation and ground segment for in-situ monitoring in regions of interest on the African continent. This would facilitate management of scarce resources using a low-cost constellation. To achieve this, the design concept and operation of a Walker constellation are examined as a means of providing connectivity to a low bit rate sensor network distributed across geographic areas of interest in South Africa, Algeria, Kenya and Nigeria. The mission requirements include the optimisation of the constellation to maintain short revisit times over South Africa and an investigation of the required communications link to perform the operations effectively. STK software is used in the design and evaluation of the constellations and the communications system. The temporal performance parameters investigated are access and revisit times of the constellations to the geographic areas mentioned. The types of constellation configurations examined, involved starting with a system level analysis of one satellite. This seed satellite has known orbital parameters. Then a gradual expansion of two to twelve satellites in one, two and three orbital planes follows. VHF, UHF and S-band communication links are considered for low data rate in-situ monitoring applications. RF link budgets and data budgets for typical applications are determined. For South Africa, in particular, a total of 12 satellites evenly distributed in a two-plane constellation at an inclination of 39° provide the optimal solution and offer an average daily revisit time of about 5 minutes. This constellation provides average daily access time of more than 16 hours per day. A case study is undertaken that decribes a constellation for the provision of maritime vessel tracking in the Southern African oceans using the Automated Information System (AIS). This service supports the Maritime Domain Awareness (MDA) initiative implemented by the South African Government, under its Operation Phakisa. / National Research Foundation (NRF) French South African Institute of Technology (F’SATI)

Through the Global Gas Flaring Reduction (GGFR) initiative a substantial amount of effort and international attention has been focused on the reduction of gas flaring since 2002 (Elvidge et al., 2009). Nigeria is rated as the second country in the world for gas flaring, after Russia. In an attempt to reduce and eliminate gas flaring the federal government of Nigeria has implemented a number of gas flaring reduction projects, but poor governmental regulatory policies have been mostly unsuccessful in phasing it out. This study examines the effects of pollution from gas flaring using multiple satellite based sensors (Landsat 5 TM and Landsat 7 ETM+) with a focus on vegetation health in the Niger Delta. Over 131 flaring sites in all 9 states (Abia, Akwa Ibom, Bayelsa, Cross Rivers, Delta, Edo, Imo, Ondo and Rivers) of the Niger Delta region have been identified, out of which 11 sites in Rivers State were examined using a case study approach. Land Surface Temperature data were derived using a novel procedure drawing in visible band information to mask out clouds and identify appropriate emissivity values for different land cover types. In 2503 out of 3001 Landsat subscenes analysed, Land Surface Temperature was elevated by at least 1 ℃ within 450 m of the flare. The results from fieldwork, carried out at the Eleme Refinery II Petroleum Company and Onne Flow Station, are compared to the Landsat 5 TM and Landsat 7 ETM+ data. Results indicate that Landsat data can detect gas flares and their associated pollution on vegetation health with acceptable accuracy for both Land Surface Temperature (range: 0.120 to 1.907 K) and Normalized Differential Vegetation Index (sd ± 0.004). Available environmental factors such as size of facility, height of stack, and time were considered. Finally, the assessment of the impact of pollution on a time series analysis (1984 to 2013) of vegetation health shows a decrease in NDVI annually within 120 m from the flare and that the spatio-temporal variability of NDVI for each site is influenced by local factors. This research demonstrated that only 5 % of the variability in δLST and only 12 % of the variability in δNDVI, with distance from the flare stack, could be accounted for by the available variables considered in this study. This suggests that other missing factors (the gas flaring volume and vegetation speciation) play a significant role in the variability in δLST and δNDVI respectively.

<p>This dissertation explores the world of non-intrusive wireless sensing for diet and fitness activity monitoring, in addition to assessing security risks in human activity recognition (HAR). It delves into the use of WiFi and millimeter wave (mmWave) signals for monitoring eating behaviors, discerning intricate eating activities, and observing fitness movements. The proposed systems harness variations in wireless signal propagation to record human behavior while providing exhaustive details on dietary and exercise habits. Significant contributions encompass unsupervised learning methodologies for detecting dietary and fitness activities, implementing soft-decision and deep neural networks for assorted activity recognition, constructing tiny motion mechanisms for subtle mouth muscle movement recovery, employing space-time-velocity features for multi-person tracking, as well as utilizing generative adversarial networks and domain adaptation structures to enable less cumbersome training efforts and cross-domain deployments. A series of comprehensive tests validate the efficacy and precision of the proposed non-intrusive wireless sensing systems. Additionally, the dissertation probes the security vulnerabilities in mmWave-based HAR systems and puts forth various sophisticated adversarial attacks - targeted, untargeted, universal, and black-box. It designs adversarial perturbations aiming to deceive the HAR models whilst striving to minimize detectability. The research offers powerful insights into issues and efficient solutions relative to non-intrusive sensing tasks and security challenges linked with wireless sensing technologies.</p>

Background: Brucellosis is a common zoonotic disease and remains a major burden in both human and domesticated animal populations worldwide. Few geographic studies of human Brucellosis have been conducted, especially in China. Inner Mongolia of China is considered an appropriate area for the study of human Brucellosis due to its provision of a suitable environment for animals most responsible for human Brucellosis outbreaks. Methods: The aggregated numbers of human Brucellosis cases from 1951 to 2005 at the municipality level, and the yearly numbers and incidence rates of human Brucellosis cases from 2006 to 2010 at the county level were collected. Geographic Information Systems (GIS), remote sensing (RS) and ecological niche modeling (ENM) were integrated to study the distribution of human Brucellosis cases over 1951-2010. Results: Results indicate that areas of central and eastern Inner Mongolia provide a long-term suitable environment where human Brucellosis outbreaks have occurred and can be expected to persist. Other areas of northeast China and central Mongolia also contain similar environments. Conclusions: This study is the first to combine advanced spatial statistical analysis with environmental modeling techniques when examining human Brucellosis outbreaks and will help to inform decision-making in the field of public health.

自工業革命後，隨著科技的進步，人口、經濟、醫療技術皆快速發展，也因人類需求的增加而大量燃燒化石燃料，大規模的砍伐熱帶雨林，導致大氣中二氧化碳大量增加，進而衍生溫室效應的發生，甚至造成全球氣候變遷。 在全球暖化的狀態下，聯合國氣候變化綱要公約與京都議定書中都明確肯定森林可固定主要溫室氣體二氧化碳，由於森林具備吸收和儲存二氧化碳的能力，其對於生態系統中的碳循環功能扮演重要的角色。若能有效監控森林資源，便能管理溫室氣體，且能提出有效的控管方式。 而本研究將應用遙測技術於碳吸存與環境變化的監測，透過美國大地衛星影像（Landsat）進行不同時期與區域之碳吸存的評估，與以往研究之最大差異為可進行大尺度與多時期的碳吸存評估，並且達到經濟、準確、有效提升效率之目標。 本研究根據光能利用率（Light use efficiency）為基礎模型，計算2005-2010之植生淨初級生產量（Net Primary Productivity, NPP），且配合不同的研究區域：台北、高雄，進一步探討不同的氣候條件與土地利用的條件下，其差異性對於NPP之影響。 成果顯示，在不同環境條件下碳吸存能力受到氣候條件影響最大，且在資料具有缺漏狀態下，依然能反映不同區域之趨勢，雖無法有效評估年總量，但仍可供評估區域性碳吸存能力之趨勢。 / Since the industrial revolution, with the rapid progress of science and technology, population, economy, and medical technology also grow rapidly. Because of increased human demand, coupled with burning lots of fossil fuels, and large-scale felling of tropical rain forests, which result in a significant increase in atmospheric carbon dioxide, and then trigger the greenhouse effect to occur, hence causing global climate change. Under the global warming condition, the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol (KC) both clearly affirmed that forests can fix the main greenhouse gas—carbon dioxide. Because forests have the ability to absorb and store carbon dioxide, they plan an important role in carbon cycle function for ecosystem. If we can effectively monitor forest resources, we will be able to manage greenhouse gases, and can come up with effective control methods. In the present study, we will use remote sensing technology to monitor carbon sequestration and environmental changes. Using Landsat images, we assessed carbon sequestration of different time periods and areas. The biggest difference between this study and previous researches is that large-scale and multi-temporal carbon sequestration assessment can be done, and the goals of economic, accurate, and increasing efficiency can be achieved. In this study, the Net Primary Productivity (NPP) of 2005-2010 was calculated based on the light use efficiency model. By comparing the results of different research areas—Taipei and Kaohsiung, the effects of different climatic conditions and land use conditions on NPP was investigated. The results show that, under different environmental conditions, the carbon sequestration capacity is affected the most by climatic conditions. Furthermore, in the absence of data, it still can reflect the trend of different regions. Although not being able to effectively assess the total amount of a year, it still can be used to assess the trend of regional carbon sequestration capacity.

Rheumatoid Arthritis (RA) is a disease in which the body has "turned on itself", with its immune system attacking mobility. In RA, an immune mechanism attacks and destroys the joints and limits mobility, in some circumstances to the point of needing replacement of joints. The aim of this research is the development of a less costly, widely accessible, passive sensing technology that provides a quantitative assessment of RA and that monitors the therapeutic effectiveness on joint-debilitating diseases. The proposed solution relies on a quantitative evaluation of human gestures. Such a quantitative assessment supports the comparison between the motion capabilities of a patient and that of a healthy person, using a kinematic model of the human skeleton. Criteria for the classification of severity were established, and tables were generated to classify the levels of severity as a function of the measurements extracted from processed videos of a subject performing predefined movements. This research project, while contributing a new tool to the process of classification of RA level of severity, opens the way for using widely accessible digital imaging for diagnosing and monitoring the evolution of the illness. Replacing MRI or HRUS with a cheaper and more accessible technology would have a major impact on health care services. From the clinical point of view, the proposed techniques based on digital images processing combined with a monitoring approach based on infrared images that was previously developed may provide a utility of care for patients with RA, as well as an alternative and automated approach for early detection of RA and active inflammation at a critical time.