PASNet: a self-adaptive point cloud sorting approach to an improved feature extraction. - In: 2022 IEEE International Conference on Image Processing, (2022), S. 956-960
A well-known difficulty in processing 3D point cloud is due to its unordered nature. The state-of-the-art 3D computer vision detection methods mainly use voxels to extract point cloud features. However, a drawback of point cloud voxelization is that some features of point cloud surface cannot be fully described. To address this problem, we propose an adaptive sorting approach for voxel-based point cloud. It adaptively ranks point cloud within voxels at first and then goes on to ex-tract voxel features using a multilayer perceptron, called PAS-Net (Points-Adaptive -Sorting-Net). The resulting method is plug-and-play and can be easily deployed in any voxel-based detection model. The proposed model was tested on the KITTI benchmark suit where a 2% - 7% improvement of the detection accuracy is achieved compared with other models using different point feature extraction methods.
https://doi.org/10.1109/ICIP46576.2022.9897376
Induction of embryogenic development in haploid microspore stem cells in droplet-based microfluidics. - In: Lab on a chip, ISSN 1473-0189, Bd. 22 (2022), 22, S. 4292-4305
This work presents the application of droplet-based microfluidics for the cultivation of microspores from Brassica napus using the doubled haploid technology. Under stress conditions (e.g. heat shock) or by chemical induction a certain fraction of the microspores can be reprogrammed and androgenesis can be induced. This process is an important approach for plant breeding because desired plant properties can be anchored in the germline on a genetic level. However, the reprogramming rate of the microspores is generally very low, increasing it by specific stimulation is, therefore, both a necessary and challenging task. In order to accelerate the optimisation and development process, the application of droplet-based microfluidics can be a promising tool. Here, we used a tube-based microfluidic system for the generation and cultivation of microspores inside nL-droplets. Different factors like cell density, tube material and heat shock conditions were investigated to improve the yield of vital plant organoids. Evaluation and analysis of the stimuli response were done on an image base aided by an artificial intelligence cell detection algorithm. Droplet-based microfluidics allowed us to apply large concentration programs in small test volumes and to screen the best conditions for reprogramming cells by the histone deacetylase inhibitor trichostatin A and for enhancing the yield of vital microspores in droplets. An enhanced reprogramming rate was found under the heat shock conditions at 32 ˚C for about 3 to 6 days. In addition, the comparative experiment with MTP showed that droplet cultivation with lower cell density (<10 cells per droplet) or adding media after 3 or 6 days significantly positively affects the microspore growth and embryo rate inside 120 nL droplets. Finally, the developed embryos could be removed from the droplets and further grown into mature plants. Overall, we demonstrated that the droplet-based tube system is suitable for implementation in an automated, miniaturized system to achieve the induction of embryogenic development in haploid microspore stem cells of Brassica napus.
https://doi.org/10.1039/D2LC00788F
Utilizing traceable software artifacts to improve bug localization. - Ilmenau : Universitätsbibliothek, 2022. - 1 Online-Ressource (viii, 142, XXX Seiten)
Technische Universität Ilmenau, Dissertation 2022
Die Entwicklung von Softwaresystemen ist eine komplexe Aufgabe. Qualitätssicherung versucht auftretenden Softwarefehler (bugs) in Systemen zu vermeiden, jedoch können Fehler nie ausgeschlossen werden. Sobald ein Softwarefehler entdeckt wird, wird typischerweise ein Fehlerbericht (bug report) erstellt. Dieser dient als Ausgangspunkt für den Entwickler den Fehler im Quellcode der Software zu finden und zu beheben (bug fixing). Fehlerberichte sowie weitere Softwareartefakte, z.B. Anforderungen und der Quellcode selbst, werden in Software Repositories abgelegt. Diese erlauben die Artefakte mit trace links zur Nachvollziehbarkeit (traceability) zu verknüpfen. Oftmals ist die Erstellung der trace links im Entwicklungsprozess vorgeschrieben. Dazu zählen u.a. die Luftfahrt- und Automobilindustrie, sowie die Entwicklung von medizinischen Geräten. Das Auffinden von Softwarefehlern in großen Systemen mit tausenden Artefakten ist eine anspruchsvolle, zeitintensive und fehleranfällige Aufgabe, welche eine umfangreiche Projektkenntnis erfordert. Deswegen wird seit Jahren aktiv an der Automatisierung dieses Prozesses geforscht. Weiterhin wird die manuelle Erstellung und Pflege von trace links als Belastung empfunden und sollte weitgehend automatisiert werden. In dieser Arbeit wird ein neuartiger Algorithmus zum Auffinden von Softwarefehlern vorgestellt, der aktiv die erstellten trace links ausnutzt. Die Artefakte und deren Beziehungen dienen zur Erstellung eines Nachvollziehbarkeitsgraphen, welcher analysiert wird um fehlerhafte Quellcodedateien anhand eines Fehlerberichtes zu finden. Jedoch muss angenommen werden, dass nicht alle notwendigen trace links zwischen den Softwareartefakten eines Projektes erstellt wurden. Deswegen wird ein vollautomatisierter, projektunabhängiger Ansatz vorgestellt, der diese fehlenden trace links erstellt (augmentation). Die Grundlage zur Entwicklung dieses Algorithmus ist der typische Entwicklungsprozess eines Softwareprojektes. Die entwickelten Ansätze wurden mit mehr als 32.000 Fehlerberichten von 27 Open-Source Projekten evaluiert und die Ergebnisse zeigen, dass die Einbeziehung von traceability signifikant das Auffinden von Fehlern im Quellcode verbessert. Weiterhin kann der entwickelte Augmentation Algorithmus zuverlässig fehlende trace links erstellen.
https://doi.org/10.22032/dbt.53717
Answering (unions of) conjunctive queries using random access and random-order enumeration. - In: ACM transactions on database systems, ISSN 0362-5915, Bd. 47 (2022), 3, S. 9:1-9:49
As data analytics becomes more crucial to digital systems, so grows the importance of characterizing the database queries that admit a more efficient evaluation. We consider the tractability yardstick of answer enumeration with a polylogarithmic delay after a linear-time preprocessing phase. Such an evaluation is obtained by constructing, in the preprocessing phase, a data structure that supports polylogarithmic-delay enumeration. In this article, we seek a structure that supports the more demanding task of a “random permutation”: polylogarithmic-delay enumeration in truly random order. Enumeration of this kind is required if downstream applications assume that the intermediate results are representative of the whole result set in a statistically meaningful manner. An even more demanding task is that of “random access”: polylogarithmic-time retrieval of an answer whose position is given. We establish that the free-connex acyclic CQs are tractable in all three senses: enumeration, random-order enumeration, and random access; and in the absence of self-joins, it follows from past results that every other CQ is intractable by each of the three (under some fine-grained complexity assumptions). However, the three yardsticks are separated in the case of a union of CQs (UCQ): while a union of free-connex acyclic CQs has a tractable enumeration, it may (provably) admit no random access. We identify a fragment of such UCQs where we can guarantee random access with polylogarithmic access time (and linear-time preprocessing) and a more general fragment where we can guarantee tractable random permutation. For general unions of free-connex acyclic CQs, we devise two algorithms with relaxed guarantees: one has logarithmic delay in expectation, and the other provides a permutation that is almost uniformly distributed. Finally, we present an implementation and an empirical study that show a considerable practical superiority of our random-order enumeration approach over state-of-the-art alternatives.
https://doi.org/10.1145/3531055
Multi-center evaluation of gel-based and dry multipin EEG caps. - In: Sensors, ISSN 1424-8220, Bd. 22 (2022), 20, 8079, S. 1-16
Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain–computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators. We conducted a multi-center and multi-operator study validating multipin dry electrodes to study the reproducibility and generalizability of their performance in different environments and for different operators. Moreover, we aimed to study the interrelation of operator experience, preparation time, and wearing comfort on the EEG signal quality. EEG acquisitions using dry and gel-based EEG caps were carried out in 6 different countries with 115 volunteers, recording electrode-skin impedances, resting state EEG and evoked activity. The dry cap showed average channel reliability of 81% but higher average impedances than the gel-based cap. However, the dry EEG caps required 62% less preparation time. No statistical differences were observed between the gel-based and dry EEG signal characteristics in all signal metrics. We conclude that the performance of the dry multipin electrodes is highly reproducible, whereas the primary influences on channel reliability and signal quality are operator skill and experience.
https://doi.org/10.3390/s22208079
Editorial. - In: Datenbank-Spektrum, ISSN 1610-1995, Bd. 22 (2022), 1, S. 1-4
https://doi.org/10.1007/s13222-022-00405-2
Combining fluorescence lifetime with spectral information in fluorescence lifetime imaging ophthalmoscopy (FLIO). - In: Biomedical optics express, ISSN 2156-7085, Bd. 13 (2022), 10, S. 5483-5494
Fluorescence lifetime imaging ophthalmoscopy (FLIO) provides information on fluorescence lifetimes in two spectral channels as well as the peak emission wavelength (PEW) of the fluorescence. Here, we combine these measures in an integral three-dimensional lifetime-PEW metric vector and determine a normal range for this vector from measurements in young healthy subjects. While for these control subjects 97 (±8) % (median (interquartile range)) of all para-macular pixels were covered by this normal vector range, it was 67 (±55) % for the elderly healthy, 38 (±43) % for age-related macular degeneration (AMD)-suspect subjects, and only 6 (±4) % for AMD patients. The vectors were significantly different for retinal pigment epithelium (RPE) lesions in AMD patients from that of non-affected tissue (p < 0.001). Lifetime- PEW plots allowed to identify possibly pathologic fundus areas by fluorescence parameters outside a 95% quantile per subject. In a patient follow-up, changes in fluorescence parameters could be traced in the lifetime-PEW metric, showing their change over disease progression.
https://doi.org/10.1364/BOE.457946
Blink: lightweight sample runs for cost optimization of big data applications. - In: New Trends in Database and Information Systems, (2022), S. 144-154
Distributed in-memory data processing engines accelerate iterative applications by caching datasets in memory rather than recomputing them in each iteration. Selecting a suitable cluster size for caching these datasets plays an essential role in achieving optimal performance. We present Blink, an autonomous sampling-based framework, which predicts sizes of cached datasets and selects optimal cluster size without relying on historical runs. We evaluate Blink on iterative, real-world, machine learning applications. With an average sample runs cost of 4.6% compared to the cost of optimal runs, Blink selects the optimal cluster size, saving up to 47.4% of execution cost compared to average cost.
https://doi.org/10.1007/978-3-031-15743-1_14
Cost modelling for optimal data placement in heterogeneous main memory. - In: Proceedings of the VLDB Endowment, ISSN 2150-8097, Bd. 15 (2022), 11, S. 2867-2880
The cost of DRAM contributes significantly to the operating costs of in-memory database management systems (IMDBMS). Persistent memory (PMEM) is an alternative type of byte-addressable memory that offers - in addition to persistence - higher capacities than DRAM at a lower price with the disadvantage of increased latencies and reduced bandwidth. This paper evaluates PMEM as a cheaper alternative to DRAM for storing table base data, which can make up a significant fraction of an IMDBMS' total memory footprint. Using a prototype implementation in the SAP HANA IMDBMS, we find that placing all table data in PMEM can reduce query performance in analytical benchmarks by more than a factor of two, while transactional workloads are less affected. To quantify the performance impact of placing individual data structures in PMEM, we propose a cost model based on a lightweight workload characterization. Using this model, we show how to place data pareto-optimally in the heterogeneous memory. Our evaluation demonstrates the accuracy of the model and shows that it is possible to place more than 75% of table data in PMEM while keeping performance within 10% of the DRAM baseline for two analytical benchmarks.
https://doi.org/10.14778/3551793.3551837
Error-driven chained multiple-subnetwork echo state network for time-series prediction. - In: IEEE sensors journal, ISSN 1558-1748, Bd. 22 (2022), 20, S. 19533-19542
Hybrid echo state networks (ESNs), a type of modified ESN, have been developed to improve the prediction accuracy of ESNs. However, they have been criticized for their computational complexity, which makes it difficult to use them directly in industrial applications. In this article, an error-driven chained multiple-subnetwork ESN (CESN) is proposed to build a simple structured hybrid network and improve its prediction accuracy. For this reason, a chain topology is generated to gradually reduce the residual error, while each subnetwork is trained separately. The weight matrix for each subnetwork does not need to be optimized, which reduces the computational cost. Meanwhile, the optimal number of subnetworks is determined on the basis of a given application. The efficiency of the proposed CESN is tested on a Santa Fe Laser and a public building dataset. Compared with ESN, 70% of the test data have been optimized by CESN for the public building dataset.
https://doi.org/10.1109/JSEN.2022.3200069