What are the possible causes of negative uptake of volume in a surface area measurement?5 answersNegative uptake of volume in a surface area measurement can be influenced by various factors. Partial volume effects (PVE) in positron emission tomography (PET) imaging can lead to incorrect uptake measurements in tumors, affecting volume calculations. Experimental errors in gas adsorption measurements due to temperature fluctuations can also impact volume determinations, especially in solids with lower adsorptive capacity. Inaccuracies in surface reconstruction from incomplete 3-D data points can result in errors in measuring object surface area and volume, particularly for irregularly shaped objects, affecting the overall volume measurement accuracy. These factors highlight the importance of considering various sources of error when interpreting negative uptake of volume in surface area measurements.
How to calculate the distortion of point cloud map?5 answersDistortion of a point cloud map can be calculated by considering the position information and weight configuration of the points in the point cloud. Different weights can be assigned to points with different position information, allowing for a more accurate representation of the actual situation of the point cloud. One method for distortion quantification is the multiscale potential energy discrepancy (MPED), which measures both geometry and color differences in a point cloud by evaluating at various neighborhood sizes. Another approach is the use of lidar and IMU fusion to remove distortion caused by rapid motion, where the pose of the lidar is estimated and used to remove the distortion of the point cloud. Additionally, in video-based point cloud compression, considering only the rate instead of the rate distortion cost for unoccupied pixels can lead to bitrate savings without sacrificing the quality of the reconstructed point cloud.
What are the challenges and opportunities of using holographic technology for teaching?3 answersUsing holographic technology for teaching presents both challenges and opportunities. One of the challenges is the need to understand the strengths and weaknesses of holographic technology as a teaching tool in order to evaluate its effectiveness in higher education. Additionally, the practical use of skills and the comparison of real objects and tasks with those covered in the educational process is an important aspect of learning, and holographic models can provide a simulated model of anything to help students understand the material better. On the other hand, holographic teaching has the potential to enhance the learning experience by providing a higher level of learning flow experience for students. It also offers opportunities to enhance the teaching presence of remote presenters and the engagement between participants, leading to an enjoyable seminar experience. However, it is important to consider non-technological factors such as the teacher's experience and the pedagogical approach in order to positively impact student performance.
What are the main challenges in holographic MIMO?5 answersThe main challenges in holographic MIMO systems include the non-separable correlation structure for small-scale fading due to the coupling effect between transmit and receive antennas, which poses difficulties in characterizing the fundamental limits of holographic MIMO channels. Another challenge is the antenna efficiency, which is crucial for achieving capacity improvement in holographic MIMO systems. Additionally, the computational complexity of minimum mean square error (MMSE) channel estimation increases significantly with a massive number of individually controlled antennas, making it challenging to implement in holographic MIMO systems. These challenges highlight the need for research in developing techniques to address the non-separable correlation structure, improving antenna efficiency, and reducing computational complexity in holographic MIMO systems.
What are the current research challenges in digital holography?5 answersDigital holography faces several research challenges. One challenge is the efficient compression of holographic data, as standard compression techniques perform poorly due to the unique nature of holographic data. Another challenge is the quality evaluation of different compression methodologies, as the 3D nature of holograms makes it difficult to find suitable objective evaluation models. Additionally, the extension of digital holography to the polarization domain, known as digital polarization holography, presents another area of research. Furthermore, the use of film-based techniques in holography has limitations such as slow real-time applications and limited access to recorded holograms. Lastly, in the field of digital holography, finding optimal hologram patterns for desired shapes is a challenge, and current approaches rely on iterative phase-retrieval algorithms that do not account for optical aberrations and deviations.
How can we measure the distortion of a 3D point cloud?4 answersDistortion of a 3D point cloud can be measured using various methods. One approach is to use a pseudo-reference PCQM metric based on joint 2D and 3D distortion description. This method constructs a joint texture-geometry distribution with texture projection map and geometry projection map to measure the joint texture-geometry distortion of the point cloud. Another method is the multiscale potential energy discrepancy (MPED), which evaluates distortion at various neighborhood sizes, achieving global-local tradeoffs and capturing distortion in a multiscale fashion. Additionally, a new quality metric compares local shape and appearance measurements between a reference and a distorted point cloud, using a large set of geometric and textural descriptors. Statistical dispersion measurements can also be employed to predict perceptual degradations by characterizing local distributions of point cloud attributes.