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Temporally Consistent Mitral Annulus Measurements from Sparse Annotations in Echocardiographic Videos
Get PDFFostering the Development of Young Students’ Analytical Thinking by use of a Problem-solving Method
Get PDFThe analytical thinking level of secondary school students in the Netherlands has been on the decline for the past few years, with grave consequences for the mathematical level of these students, who often struggle later on in their academic careers. In particular, these students showcase underdeveloped basic skills such as critical reading and critical thinking, vital to many subjects in secondary school. Problem-solving methods have been utilised widely across the literature to foster both academic skills and the performance of students. In this research, a problem-solving method, inspired by Polya’s four step method, is introduced and extended to include a reflection part (inside phase) to help students foster and develop their analytical thinking. Qualitative findings from a study conducted with K–8 students are reported and discussed to determine the degree to which the methodology helped these students develop their analytical thinking compared to a parallel class of K–8 students
Toward the optimal spatial resolution ratio for fusion of UAV and Sentinel-2 satellite imageries using metaheuristic optimization
Get PDFSentinel-2A/2B twin satellites provide multispectral imagery every 5 days at a medium spatial resolution (10 m for visible and near-infrared bands). In contrast, UAV photogrammetry with low-cost visible-light (RGB) sensors produces ultra-high-resolution orthomosaics but lacks rich spectral information. Fusing these datasets is a solution to enhance the resolution of Sentinel imagery using UAV data. However, fusion is challenging due to large spatial resolution disparities, particularly in Ground Sampling Distance (GSD). By challenging the common practice of sharpening the Sentinel image to match the UAV resolution, we propose a method that fuses the two images at an intermediate resolution level where their information content is comparable. Our approach uses natural target edge analysis and a Genetic-based metaheuristic optimization technique. By minimizing an objective function comprising true GSD or Ground Resolved Distance (GRD) and Mutual Information (MI), we determine the optimal resolution level for fusion. Experimental validation on two UAV and Sentinel datasets, yielded optimal GRD estimates of 2.35 m and 2.03 m, respectively, with Sentinel GRD values of 12.12 m and 12.39 m. The optimal UAV-Sentinel GRD ratios were 0.193 and 0.164. The sharpened Sentinel images showed efficient fusion through subjective and objective quality assessments. Testing the method on 24 UAV-Sentinel datasets from various regions, including America (United States), Europe (Germany, Spain, and Switzerland), and Asia (Iran and Qatar), demonstrated its robustness across different land covers and sensor types. This approach can be applied to any multi-sensor remote sensing image fusion task with significant resolution differences, establishing the meaningful level for fusion.</p
Industrial Perspective of Electrified Ethylene Production via Membrane-Assisted Nonoxidative Dehydrogenation of Ethane
Get PDFThe potential of applying ceramic proton-conducting electrolysis cell (PCEC) membranes in ethylene production processes was explored in this work. To this end, the techno-economics of a PCEC-assisted ethane dehydrogenation process were compared against the conventional ethane steam cracking (SC) process. The PCEC process required four to five times more electricity than the SC process. Consequently, fully renewable electricity needed to be utilized in the PCEC process to outcompete conventional SC in terms of carbon dioxide emissions. Notably, the PCEC process was financially and environmentally competitive with conventional SC only when achieving similar ethylene yields (ca. 50%). For an ethylene yield of ca. 25%, which is currently achievable using PCEC technologies, the capital investment and carbon emissions of the PCEC process were too excessive to outcompete electrified SC. The total energy usage, utility demand, and capital investment were substantially higher for the 25% ethylene yield PCEC case as compared to the 50% PCEC one, due to larger process streams and process units as a result of the lower single-pass yield. The results further highlighted that carbon emissions could be reduced from ca. 1.5 tCO2/tethylene to ca. 0.2 tCO2/tethylene when employing green electrified SC or PCEC processes instead of conventional fossil fuel-based SC, but only if fully renewable electricity was utilized. Moreover, a carbon tax of more than 100 USD/tCO2 would need to be imposed to make the green electrified SC and PCEC process more viable than their fossil-based counterparts. Lastly, technological challenges related to attainable ethylene yield, PCEC stability, large-scale sustainable production of PCECs, and the continuous availability of green electricity were identified as the main hurdles for the industrial implementation of PCECs for green ethylene production.</p
Exploring strategies for managing maturity variations among project partners:from underperformance and controlling weak links to stretching capabilities
Get PDFThe construction industry has experienced digital transformation with the widespread adoption of Building Information Modelling (BIM). However, the implementation of BIM has not been uniform across construction organizations, leading to variations in their maturity levels in using BIM. Collaborative projects involving multiple organizations face challenges due to these variations. This study aims to investigate how these variations influence the overall project maturity. Contrary to the belief that project maturity is merely the average of partner maturities, this research reveals that project managers employ strategies to influence project maturity. These strategies involve adjusting ambitions, strategically limiting certain parties’ involvement, and fostering maturity development through structure and education. Consequently, project partners can achieve a project maturity level that surpasses their individual capabilities.</p
Extreme values for the waiting time in large fork-join queues
Get PDFWe prove that the scaled maximum steady-state waiting time and the scaled maximum steady-state queue length among N GI/GI/1-queues in the N-server fork-join queue converge to a normally distributed random variable as N→∞. The maximum steady-state waiting time in this queueing system scales around 1γlogN, where γ is determined by the cumulant generating function Λ of the service times distribution and solves the Cramér–Lundberg equation with stochastic service times and deterministic interarrival times. This value 1γlogN is reached at a certain hitting time. The number of arrivals until that hitting time satisfies the central limit theorem, with standard deviation σAΛ′(γ)γ. By using the distributional form of Little’s law, we can extend this result to the maximum queue length. Finally, we extend these results to a fork-join queue with different classes of servers.</p
Factors Affecting the Adoption of Transboundary Groundwater Agreements and Potential Solutions:A Focus on the Nubian Sandstone Aquifer System
No full textCompared with international law applicable to surface water, international groundwater law has seen slower development. This has resulted in groundwater playing a secondary role in international water conventions and the adoption of fewer groundwater basin agreements. This chapter examines three main factors affecting cooperation over transboundary groundwater from a legal perspective. These factors are (1) the hidden nature of this resource, (2) lack of scientific understanding in the past and present, and (3) the potential impact of current scientific developments on the adoption of water agreements. These factors will be examined in the context of a case study, the Nubian Sandstone Aquifer System, shared among Libya, Egypt, Chad, and Sudan. Based on the analysis, recommendations are made on how these factors can strengthen the adoption and implementation of a new aquifer agreement.<br/
Dual-Mode Nonlinear Radar with an Auxiliary Transmitter:Coverage Analysis
Get PDFNonlinear radar uses passive harmonic tags to detect and track objects in cluttered environments. Being an effective solution against clutter, it is notorious for its low range in relation to transmit power. A novel dual-mode nonlinear radar employs auxiliary transmitters to generate and process harmonic and intermodulation tag returns. This work investigates how this dual-mode operation can be leveraged to increase system coverage
Integrating multiple cold plasma generators and Bernoulli-driven microbubble formation for large-volume water treatment
Get PDFCold plasma-bubble is a promising clean technology for wastewater treatment using air and electricity. However, scalability continues to pose a significant challenge to industrial applications. In this study, we integrate portable, low-power cold plasma generators with spontaneous microbubble formation in engineered venturi tubes for rapid water treatment. These tubes provide water flow channels with multiple plasma ports. The design expanded the flow rate range for stable microbubble formation from earlier reports, enabling 16 L/min and scaling up the volume of treated water to 40 L with same energy efficiency. Importantly, we identified a universal linear correlation between the total surface area of microbubbles and activation efficiency, represented by removal of a model dye, methyl orange. Significant disinfection against Gram-(−/+) bacteria with 6.68-log was confirmed in increasing water volume. Time required for effective disinfection of 4-log CFU/mL removal increases approximately linearly with volume of water, suggesting that disinfection can be achieved even at large-scale without losing the effectiveness. Increasing the plasma generator numbers (four-needle), the treatment capacity can be further improved to 120 L. Our work demonstrates that the cold plasma-bubble technology for flowing water is rapid and scalable, providing a sustainable solution for diverse industrial and environmental challenges. Synopsis: This study integrates portable, low-power cold plasma generators for microbubble enhanced activation using engineered venturi tubes, demonstrating scalable, efficient and sustainable wastewater treatment and disinfection.</p
Design of intelligent autocatalytic reaction networks
Get PDFThis thesis investigates the design of autocatalytic chemical reaction networks (CRNs) for out-of-equilibrium conditions in order to create intelligent chemical systems capable of decision-making, memory, and adaptation. Autocatalysis provides nonlinear feedback dynamics that mimic regulatory processes found in biological systems, allowing chemical systems to exhibit functions such as logic processing, signal response, and environmental adaptation. By carefully tuning flow conditions, catalytic composition, and the reactor properties, it becomes possible to program CRNs to store memory, perform logic operations, and propagate spatial information. Such systems lay the foundation for a new class of programmable, self-regulating materials with potential applications in neuromorphic computation, sensing, soft robotics, and synthetic biology. As this field progresses, intelligent chemical systems may increasingly perform intricate tasks like real-time stimulus processing, history-dependent decision-making, and spatial navigation. These abilities suggest broad applicability: in environmental monitoring, chemical systems could autonomously detect and respond to pollutants; in healthcare, they may underpin wearable devices that react to physiological changes; in soft robotics, they offer embedded sensing and actuation in complex terrains. The integration of chemical intelligence with digital platforms could further expand their real-world utility, enabling hybrid systems that combine chemical adaptability with computational precision. As design principles mature, it may become possible to build chemical circuits that replicate essential electronic components — like memory switches or oscillators — but operate through fluidic or molecular interactions instead of electrons. Ultimately, the promise of autocatalytic CRNs lies not only in emulating biology but in surpassing current limitations of semiconductor technology by creating biodegradable, low-energy, decentralized systems. This thesis brings us closer to realizing a new technological paradigm, where chemistry, computation, and biology merge into sustainable, intelligent systems for the future