Data fusion of RGB and depth data with image enhancement. - In: Journal of imaging, ISSN 2313-433X, Bd. 10 (2024), 3, 73, S. 1-17
Since 3D sensors became popular, imaged depth data are easier to obtain in the consumer sector. In applications such as defect localization on industrial objects or mass/volume estimation, precise depth data is important and, thus, benefits from the usage of multiple information sources. However, a combination of RGB images and depth images can not only improve our understanding of objects, capacitating one to gain more information about objects but also enhance data quality. Combining different camera systems using data fusion can enable higher quality data since disadvantages can be compensated. Data fusion itself consists of data preparation and data registration. A challenge in data fusion is the different resolutions of sensors. Therefore, up- and downsampling algorithms are needed. This paper compares multiple up- and downsampling methods, such as different direct interpolation methods, joint bilateral upsampling (JBU), and Markov random fields (MRFs), in terms of their potential to create RGB-D images and improve the quality of depth information. In contrast to the literature in which imaging systems are adjusted to acquire the data of the same section simultaneously, the laboratory setup in this study was based on conveyor-based optical sorting processes, and therefore, the data were acquired at different time periods and different spatial locations. Data assignment and data cropping were necessary. In order to evaluate the results, root mean square error (RMSE), signal-to-noise ratio (SNR), correlation (CORR), universal quality index (UQI), and the contour offset are monitored. With JBU outperforming the other upsampling methods, achieving a meanRMSE = 25.22, mean SNR = 32.80, mean CORR = 0.99, and mean UQI = 0.97.
https://doi.org/10.3390/jimaging10030073
Modelling reaction transfer velocities in disconnected compact heterogeneous multilayer reactive material systems. - In: MRS advances, ISSN 2059-8521, Bd. 0 (2024), 0, S. 1-6
The tuning of the self-propagating reaction is studied theoretically by introducing a non-reactive material between two reactive material elements. For the study, the Ni/Al bilayer system was chosen. The Ni/Al elements were placed on a silicon wafer covered with a 1-µm-thick silicon dioxide. The spaces between the multilayer reactive material elements were filled with different non-reactive materials covering a wide range of thermal properties. On top of this heterogeneous layer, a 1-µm-thick sealing layer was placed consisting of the filler material. The carried out two-dimensional simulations demonstrated that embedding material allows to scale the ignition transfer time and the heat propagation velocity. For example, for a transfer length of 1 µm, the ignition time can be tuned from nano- to microseconds. Consequently, in contrast to previous results embedding materials allow scaling the properties of the self-propagating reaction in heterogeneous reactive material systems.
https://doi.org/10.1557/s43580-024-00822-3
Experimental validation for the combination of funnel control with a feedforward control strategy. - In: Multibody system dynamics, ISSN 1573-272X, Bd. 0 (2024), 0, S. 1-19
Current engineering design trends, such as lightweight machines and human-machine interaction, often lead to underactuated systems. Output trajectory tracking of such systems is a challenging control problem. Here, we use a two-design-degree of freedom control approach by combining funnel feedback control with feedforward control based on servo-constraints. We present experimental results to verify the approach and demonstrate that the addition of a feedforward controller mitigates drawbacks of the funnel controller. We also present new experimental results for the real-time implementation of a feedforward controller based on servo-constraints on a minimum phase system.
https://doi.org/10.1007/s11044-024-09976-2
7 dimensions of software change patterns. - In: Scientific reports, ISSN 2045-2322, Bd. 14 (2024), 6141, S. 1-17
Evolving software is a highly complex and creative problem in which a number of different strategies are used to solve the tasks at hand. These strategies and reoccurring coding patterns can offer insights into the process. However, they can be highly project or even task-specific. We aim to identify code change patterns in order to draw conclusions about the software development process. For this, we propose a novel way to calculate high-level file overarching diffs, and a novel way to parallelize pattern mining. In a study of 1000 Java projects, we mined and analyzed a total of 45,000 patterns. We present 13 patterns, showing extreme points of the 7 pattern categories we identified. We found that a large number of high-level change patterns exist and occur frequently. The majority of mined patterns were associated with a specific project and contributor, where and by whom it was more likely to be used. While a large number of different code change patterns are used, only a few, mostly unsurprising ones, are common under all circumstances. The majority of code change patterns are highly specific to different context factors that we further explore.
https://doi.org/10.1038/s41598-024-54894-0
Feedback rectifiable pairs and stabilization of switched linear systems. - In: Systems & control letters, ISSN 1872-7956, Bd. 186 (2024), 105755, S. 1-10
We address the feedback design problem for switched linear systems. In particular we aim to design a switched state-feedback such that the resulting closed-loop subsystems share the same eigenstructure. To this effect we formulate and analyse the feedback rectification problem for pairs of matrices. We present necessary and sufficient conditions for the feedback rectifiability of pairs for two subsystems and give a constructive procedure to design stabilizing state-feedback for a class of switched systems. In particular the proposed algorithm provides sets of eigenvalues and corresponding eigenvectors for the closed-loop subsystems that guarantee stability for arbitrary switching. Several examples illustrate the characteristics of the problem considered and the application of the proposed design procedure.
https://doi.org/10.1016/j.sysconle.2024.105755
Comparison of LQR with MPC in the adaptive stabilization of a glass conditioning process using soft-sensors for parameter identification and state observation. - In: Control engineering practice, ISSN 1873-6939, Bd. 146 (2024), 105884, S. 1-11
The paper presents the comparison of two different continuous-time adaptive control strategies applied to the temperature stabilization of molten glass during conditioning. Both control methods include on-line linear continuous-time model parameter identification using a nonstandard procedure based on the modulating functions method. The related control task is of great practical importance because it directly affects the quality of manufactured glass containers. The molten glass temperature must be stabilized with accuracy of about 1C˚ which can be very difficult. At the core of this work, the synthesis of a nonstandard adaptive control procedure is described that consists of a linear quadratic regulator (LQR) being fed with process parameters and state estimates. These new state estimates are generated with a special transform and reconstructed by a special type of modulating function state observer consisting of two modulating function based soft-sensors which rely on a continuous-time model. However, an equally important issue of this investigation is the efficiency and accuracy of the algorithm. To this end, the described stabilization method will be compared with a standard continuous-time model predictive control (MPC) approach that was used in the authors’ previous research on the continuous molten glass temperature stabilization in a single glass forehearth zone. Simulation results based on experimental calibration data are presented and compared for these two approaches. It turns out that the first method with LQR is simpler than the MPC approach while maintaining the same level of accuracy and quality of control.
https://doi.org/10.1016/j.conengprac.2024.105884
A novel 2-in-1 heat management and recovery system for sustainable electronics. - In: Energy conversion and management, ISSN 0196-8904, Bd. 303 (2024), 118171, S. 1-12
Overheating poses major challenges in miniaturized electronics, especially as their power consumption increases. For this reason, thermal management is a necessity for efficient electronics, and its optimization is a central task in the design especially for miniaturized compact electronics. On the other hand, recovering this waste energy could be beneficial for battery-free electronics such as wireless sensors and devices located in remote environments, where the charging or changing of batteries are challenging and delicate tasks. Furthermore, batteries are known for their storage capacity degradation over time and environmental pollution. This paper presents the design, development, demonstration, and validation of an innovative 2-in-1 heat management and recovery system for autonomous electronic devices. The design incorporates the use of thermal vias as in-package heat management and vertical thermocouples, enabling simultaneously management and recovery of the heat emitted from a Si-chip. The proposed design is fabricated in Low Temperature Co-fired Ceramic (LTCC) technology, allowing the creation of a monolithic package containing miniaturized multilayer microvias in the range of 90 µm using different materials to act as embedded thermal management and vertical thermocouples, simultaneously. The design consists of 20 lateral (Ag/Co) and 21 vertical (Ag/AgPd) micro-TEGs connected electrically in series in the system. The hybrid TEG is made by combining thick- and thin-film technologies, favoring the use of different materials and technologies with high power factors for further improvements in the field of thermal energy harvesting. The proposed design allows the management of 67 % of the IC temperature by reducing it from 246 ˚C to 80 ˚C using Ag and AgPd thermal vias. At the same time, the system recovers the lost thermal energy to generate 37.5 µW of electrical power at a temperature difference of 58 ˚C. The proposed approach allows simultaneously transitioning into green and sustainable battery-free electronics and enhances the devicés reliability by maintaining thermal stabilization in a miniaturized devices using a monolithic package.
https://doi.org/10.1016/j.enconman.2024.118171
Single-trial EEG analysis reveals burst structure during photic driving. - In: Clinical neurophysiology, ISSN 1872-8952, Bd. 159 (2024), S. 66-74
Objective: Photic driving in the human visual cortex evoked by intermittent photic stimulation is usually characterized in averaged data by an ongoing oscillation showing frequency entrainment and resonance phenomena during the course of stimulation. We challenge this view of an ongoing oscillation by analyzing unaveraged data. Methods: 64-channel EEGs were recorded during visual stimulation with light flashes at eight stimulation frequencies between 7.8 and 23 Hz for fourteen healthy volunteers. Time-frequency analyses were performed in averaged and unaveraged data. Results: While we find ongoing oscillations in the averaged data during intermittent photic stimulation, we find transient events (bursts) of activity in the unaveraged data. Both resonance and entrainment occur for the ongoing oscillations in the averaged data and the bursts in the unaveraged data. Conclusions: We argue that the continuous oscillations in the averaged signal may be composed of brief, transient bursts in single trials. Our results can also explain previously observed amplitude fluctuations in averaged photic driving data. Significance: Single-trial analyses might consequently improve our understanding of resonance and entrainment phenomena in the brain.
https://doi.org/10.1016/j.clinph.2024.01.005
Efficient analytical evaluation of the singular BEM integrals for the three-dimensional Laplace and Stokes equations over polygonal elements. - In: Engineering analysis with boundary elements, ISSN 0955-7997, Bd. 161 (2024), S. 70-77
Singularities in the fundamental solutions pose a mathematical challenge for all applications of the boundary element method, if the source and field point lie on the same element. To avoid complex and error-prone numerical procedures, analytical solutions for the integrals that arise are desirable. In this work, easy and efficiently to implement analytical solutions are presented for the fundamental solutions of the three-dimensional Stokes equation as well as Laplace’s equation. Explicit expressions are derived for general triangular elements using constant shape functions. In addition, options for extending to arbitrary polygonal elements are shown. In particular, the three cases that the incenter, the centroid or the vertices of the triangles are used as source points for the calculation are addressed. The impressive numerical efficiency of the method is demonstrated by explicit examples.
https://doi.org/10.1016/j.enganabound.2024.01.013
Fast ML-based next-word prediction for hybrid languages. - In: Internet of things and cyber-physical systems, ISSN 2667-3452, Bd. 25 (2024), 101064, S. 1-15
Smartphone users are beyond two billion worldwide. Heavy users of the texting application rely on input prediction to reduce typing effort. In languages based on the Roman alphabet, many techniques are available. However, Japanese text is based on multiple character sets such as Kanji (Chinese-like word symbols), Hiragana and Katakana syllable sets. For its time/labor intensive input, next word prediction is crucial. It is still an open challenge. To tackle this, a hybrid language model is proposed. It integrates a Recurrent Neural Network (RNN) with an n-gram model. RNNs are powerful models for learning long sequences for next word prediction. N-gram models are best at current word completion. Our RNN language model (RNN-LM) predicts the next words. According the “price” of the performance gain paid by a higher time complexity, our model best deploys on a client-server architecture. Heavily-loaded RNN-LM deploys on the server while the n-gram model on the client. Our RNN-LM consists of an input layer equipped with word embedding, an output layer, and hidden layers connected with LSTMs (Long Short-Term Memories). Training is done via BPTT (Back Propagation Through Time). For robust training, BPTT is elaborated by learning rate refinement and gradient norm scaling. To avoid overfitting, the dropout technique is applied except for LSTM. Our novel model is compact (2 LSTMs, 650 units per layer), indeed. Due to synergetic elaboration, it shows 10 % lower perplexity than Zaremba's excellent conventional models in our Japanese text prediction experiment. Our model has been incorporated into IME (Input Method Editor) we call Flick. On the Japanese text input experiment, Flick outperforms Mozc (Google Japanese Input) by 16 % in time and 34 % in the number of keystrokes.
https://doi.org/10.1016/j.iot.2024.101064