Global ETD Search

11	Worker's Behavioral Adaptation to Safety Interventions and Technologies: Empirical Evidence and Theoretical Considerations Through The Case of Simulated Residential Roofing Task Mohammadhasanzadeh, Sogand 14 April 2020 (has links) On-the-job injuries that occur even after implementing safety interventions highlight the need for identifying the limitations in them and for making future safety interventions and technological advances more effective. One possible reason for this lower-than-expected-safety returns is the latent side-effect of safety interventions, known as risk compensation. This dissertation aimed to provide empirical evidence and theoretical considerations of risk compensation effect in the construction industry. Accordingly, a multi-sensor immersive mixed-reality environment consists of a virtual projection of the environment and passive haptics of a roof was developed to study risk compensation among residential roofers. Simulating height, environmental factors (wind and sound), passive haptic, and virtual falls stimulated sufficient Sense of Presence to trigger subjects' behavioral changes while installing shingles on a 27-degree sloped roof under three levels of safety interventions (i.e., with no fall-safety intervention, with an injury-reducing fall-safety intervention—i.e., fall-arrest system—and with an injury-preventing fall-safety intervention— i.e., a fall-arrest system and a guardrail). The baseline demographic, psychographic, and cognitive measures combined with real-time tracking and wearable sensors provided an opportunity to track the worker's motions, localize his/her position, obtain real-time musculoskeletal data, and monitor the his/her behavioral and physiological responses. The collected data is then translated into information about the risk perception and risk-taking behavior of the worker. The results yielded unequivocal evidence of risk compensation—the lower perceived risk associated with the situation (lower levels of stress) and the false sense of security among roofers when they were provided with safety interventions apparently encouraged them to be less cautious by leaning over the edge, stepping closer to the roof edge, spending more time exposing themselves to fall risk, over-relying on the safety equipment through different facing directions and choices of posture stability. As a result, they also experienced more near-misses (close calls). This behavioral adaptation was more pronounced when they were provided with an injury-preventing safety intervention (e.g., guardrail). The findings also suggested that the productivity and safety benefits of safety interventions can be negated due to risk compensation, which identifies vital information for the construction-safety community to consider during the design and implementation of more effective safety interventions and technological advances. Roofers with high risk tolerance and sensation seekers were identified as high-risk groups who are more likely to be involved in risk-compensatory behaviors; various behavioral interventions are suggested in this dissertation to counteract excessive risk-taking and to reduce risk compensation. The findings of this study shed light on the question of why injury rates have remained at worrisome levels despite advances in protective measures and interventions. In the long-term, a better understanding of risk compensation will translate into fundamental knowledge about how the construction industry should approach and maintain controls after safety interventions. / Doctor of Philosophy / While researchers have dispensed considerable efforts to reduce the risk of occupational injuries by implementing safety interventions, the large number of safety incidents occurring each year in the construction industry. It is hypothesized that the latent effect of safety interventions, known as risk compensation, might be a possible reason why many of the safety interventions and technological advances have not fully achieved their safety objectives. This dissertation aimed to empirically examine the changes in workers' productivity, risk perception, risk-taking behaviors as a function of different safety interventions in place. To study this within a risk-free setting, an immersive mixed-reality environment simulating roofing task was developed. Then, the reactionary behavioral responses of participants were monitored using real-time tracking sensors and qualitative sources of data while they were completing a roofing task under three counterbalanced levels of safety interventions (i.e., with no fall-safety intervention, with an injury-reducing fall-safety intervention—i.e., fall-arrest system—and with an injury-preventing fall-safety intervention— i.e., a fall-arrest system and a guardrail). The findings indicated that the reduced perceived risk and the desire for increased productivity may skew risk analysis and strongly bias workers toward presuming invulnerability when safety interventions are in place. According to risk compensation theory, workers' risk tolerance and perceptions of risk influence their risk-taking behavior—as the perceived risk associated with the situation decreases, individuals take more risks to achieve a level of risk they can comfortably tolerate. Therefore, the workers might become less cautious by leaning over the edge, stepping closer to the roof edge, spending more time exposing themselves to fall risk, over-relying on the safety equipment through different facing directions and choices of posture stability. This result does not necessarily imply the safety innovations are completely ineffective, but rather demonstrates dangers users face when they misperceive the effectiveness of a safety intervention. Furthermore, roofers with high risk tolerance and a high sensation-seeking disposition were identified as high-risk groups who are more likely to be involved in risk-compensatory behaviors. This research represented a substantive departure from the status quo by proposing novel pathways for proactive incident prevention due to risk compensation in the construction industry. The contribution of this study is especially significant because a better understanding of risk compensation will translate into fundamental knowledge about how the construction industry should approach and maintain controls after safety interventions. Risk compensation Risk-taking behavior Risk perception Risk propensity Fall hazard Construction safety Mixed-reality Passive haptics Real-time tracking sensors.
12	穿戴式互動展演創新應用與即時追蹤技術研究 / Interactive Performance Using Wearable Devices: Real-time Tracking Technology and Innovative Applications 鄭仲祐, Cheng, Chung Yu Unknown Date (has links) 近年來越來越多虛實整合技術不斷地湧出，像是電影阿凡達或虛實互動型態的表演。這樣的表演會根據事先預錄好的虛擬角色進行演出，但要成功地演出需要演員們不斷的練習。另外,許多電影利用攝影機捕捉人體姿態來與虛擬角色互動，但此方法受限於燈光環境以及障礙物。此篇論文運用穿戴式裝置與新一代無線網路藍芽4.0,提出即時追蹤技術套用於這類表演,可使得演出更加豐富並且能即興創作。然而，目前受限於穿戴式平台上的藍芽訊號強度更新頻率每秒只有5至10次且傳輸容量有限，所以本篇論文結合體態感測裝置輔助無線網路藍芽4.0,提升對穿戴者的即時追蹤能力。實驗結果與真實位置只有0.3至0.5秒的延遲時間,並在校內進行兩場互動式展演作驗證成果。未來期許可以將此技術運用於多人展演場，讓更多使用者可以互動體驗。 / Recently, more and more interactive performance technologies appear such as Avatar or virtual-character integrated art perform. Such performs are based on pre-made animations and physics simulations. However, this kind of shows need a lot of practice, and it is impossible that audience or performers play with or interact with the virtual characters. In addition, many moviemakers use high quality cameras to distinguish body postures. Although cameras can record anything with high precision, it is constrained on the light and obstacles of the environments. If we, somehow, can capture the motion of the performers in real time, then we are able to interact with virtual characters and make improvisation possible. This thesis aims to use the wearable sensors and the Received Signal Strength Indication (RSSI) of BLE to track in real-time. However, the update rate of RSSI is limited to 5~10 per second. This thesis proposed a tracking technique which combines with wearable motion sensors to assist BLE localization. The tracking lag can be reduced to only 0.3~0.5 seconds, and also real performance was experimented in the campus. In the future, we hope to use this technique on interactive performance with many people in different places. 藍牙4.0 虛實互動表演即時體態捕捉即時追蹤穿戴式裝置 Bluetooth 4.0 Real-time motion capture Real-time Tracking Wearable devices
13	Trasování objektu v reálném čase / Visual Object Tracking in Realtime Kratochvíla, Lukáš January 2019 (has links) Sledování obecného objektu na zařízení s omezenými prostředky v reálném čase je obtížné. Mnoho algoritmů věnujících se této problematice již existuje. V této práci se s nimi seznámíme. Různé přístupy k této problematice jsou diskutovány včetně hlubokého učení. Představeny jsou reprezentace objektu, datasety i metriky pro vyhodnocování. Mnoho sledovacích algorimů je představeno, osm z nich je implementováno a vyhodnoceno na VOT datasetu.
14	使用穿戴裝置實現即時相對方向定位 / Real-time relative directional positioning using wearable devices 蔡育銓, Tsai,Yua Chan Unknown Date (has links) 近年來穿戴相關發展越來越蓬勃，特別是在虛擬-實境的綜合藝術表演中，例如: 電影「猩球崛起」。然而大部分虛擬實境的綜合內容是基於腳本預先錄製好的，而且演員需要大量的練習，使表演能夠完美演出。此外，如果我們想要在兩人的相對方向定位上有特殊效果，那麼預先錄製的的方法是不合適的。解決這個問題的一個方法是，使用高品質的相機偵測身體的姿勢或位置。但是精准度常會受限於光線或是障礙物。本篇論文中，我們提出一個即時相對方向定位方法，這方法使用無線可穿戴式設備解決這個問題。我們結合BLE 所發送的Received Signal Strength Indicator (RSSI)與IMU 感測器資訊，來追蹤兩個表演者的相對方向定位的位置。但是RSSI 資料有波動與不穩定性、IMU 會引起累積的誤差。我們發明了「可靠程度」的RSSI 量測概念，並且把這概念運用在IMU 定期校正上。我們實驗的情況是，兩個人的舞蹈來驗證準確性，結果是令人滿意的。我們還使用Unity 來實踐人體骨架，以便與兩個舞者動作做比較。在未來，我們開發的方案可以用於藝術表演，使內容更豐富，更具互動性。 / In recent years, wearable-related applications are flourishing, especially in virtual-real integrated art performance, such as “Rise of the Planet of the Apes”. However, most of the virtual-real integrated contents are pre-recorded based on the script, and the performer needs a lot of practice to make the integration perfect. Moreover, if we want to make special effect based on the relative directional positions of two performers, the pre-recorded approach is not suitable. One way to tackle this problem is to use the high-quality camera to detect the body posture or position.But the accuracy is usually limited in light intensity or obstacles. In this thesis, we propose a real-time relative directional positioning approach using wireless wearable devices to solve this problem. We use Received Signal Strength Indicator (RSSI) of BLE, combined with IMU sensors to track two performers’ relative directional positions. The RSSI fluctuates and the IMU causes accumulated errors. We invent the concept of “reliable level” of RSSI measures to periodically correct the IMU errors. We experiment the scenario of two-person dance to validate the accuracy, and the result is satisfactory. We also use Unity to real-time render the human skeleton for comparison with the two dancers’ motion.In the future, our developed scheme can be used in the art performance to make the content richer and more interactive. 藍芽4.0 穿戴式裝置即時追蹤體感偵測技術 RSSI IMU 可靠程度相對方向定位 Bluetooth 4.0 Wearable devices Real-time Tracking Motion Capture RSSI IMU reliable level relative directional positioning
15	Vizuální sledování objektu v reálném čase / Real-Time Object Tracking in Video Šimon, Martin January 2015 (has links) This thesis focuses on real-time visual object tracking with emphasis on problems caused by a long-term tracking task. Among theses problems belong primarily an occlusion problem, both the partial and the full one, and appearance changes of the object during the tracking. The work is also concerned with tracking objects of a very limited size and unsteady camera movements. These two particular problems are relatively common when tracking distant objects. A part of this work is also a summary of related work and a proposal of a system with high qualitative stability and robustness to problems mentioned. The proposed system was implemented and the evaluation demonstrated that it is capable of solving these problems partially.
16	Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms Vestin, Albin, Strandberg, Gustav January 2019 (has links) Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms. evaluation target tracking multiple sensors non-causal smoother smoothing tracking vehicle tracking camera lidar estimate estimation prediction vehicle dynamics sensor fusion real-time tracking extended kalman filter filter validation validation position estimation velocity estimation dynamic model model complexity multi object tracking multiple object tracking single object tracking data association tracking fundamentals iterated kalman filter track management gnn global nearest neighbour mahalanobis mahalanobis distance performance evaluation differential gps dgps roi ego several sensors sensors rmse root mean square error invertible motion anti-causal motion anti-causal tracking constant velocity gnn imu tfs two filter smoother ekf rts radar inertial measurement unit nonlinear nonlinear systems mono camera monocular camera noise model tracking performance fixed interval smoothing m/n logic centralized fusion non-causal object tracker car tracking car dynamics automotive active safety object tracking automotive industry thesis master reverse dynamics reverse tracking reverse sequence sequence tracking data propagation ground truth estimating ground truth additional sensors mounted sensors true estimates environment comparison algorithm independent targets overlapping measurements occluded track switch improve lower uncertainty more certain state process noise covariance sampling image sprt adas cnn cv pdf track target ego tracker tentative track observatiom online tracking offline tracking online offline recorded sequences robust self driving self-driving car traffic trajectory true state scenario scenarios future accurate output advanced driver assistance systems non-linear complex noise pedestrian truck bus maneuvering vehicles processed measurement frame state correction probability density function tuning likelihood transition measurement motion model recursion gaussian approximation distribution linear jacobian multiplicative noise ratio ad hoc ad hoc state space approach backward auction euclidean distance statistical threshold gating association margin normalize covariance matrix fusion confirmed rejected tentative history absolute error modular ego motion parameters variables logg hardware specification fused causal factorization independent uncorrelated transform moving rotation translation oncoming overtaking Control Engineering Reglerteknik

Page generated in 0.0945 seconds