Wall segmentation is a special case of semantic segmentation, and the task is to classify each pixel into one of two classes: wall and no-wall. The segmentation model returns a mask showing where objects like windows and furniture are located, as well as walls. This article proposes the module's structure for semantic segmentation of walls in 2D images, which can effectively address the problem of wall segmentation. The proposed model achieved higher accuracy and faster execution than other solutions. An encoder-decoder architecture of the segmentation module was used. Dilated ResNet50/101 network was used as an encoder, representing ResNet50/101 network in which dilated convolutional layers replaced the last convolutional layers. The ADE20K dataset subset containing only interior images, was used for model training, while only its subset was used for model evaluation. Three different approaches to model training were analyzed in the research. On the validation dataset, the best approach based on the proposed structure with the ResNet101 network resulted in an average accuracy at the pixel level of 92.13% and an intersection over union (IoU) of 72.58%. Moreover, all proposed approaches can be applied to recognize other objects in the image to solve specific tasks.

• Klíčová slova
• ADE20K, Encoder-decoder, PSPNet, Semantic segmentation, Wall segmentation,
• Publikační typ
• časopisecké články MeSH

The estimation of the speed of human motion from wearable IMU sensors is required in applications such as pedestrian dead reckoning. In this paper, we test deep learning methods for the prediction of the motion speed from raw readings of a low-cost IMU sensor. Each subject was observed using three sensors at the shoe, shin, and thigh. We show that existing general-purpose architectures outperform classical feature-based approaches and propose a novel architecture tailored for this task. The proposed architecture is based on a semi-supervised variational auto-encoder structure with innovated decoder in the form of a dense layer with a sinusoidal activation function. The proposed architecture achieved the lowest average error on the test data. Analysis of sensor placement reveals that the best location for the sensor is the shoe. Significant accuracy gain was observed when all three sensors were available. All data acquired in this experiment and the code of the estimation methods are available for download.

• Klíčová slova
• autoencoder architecture, deep learning, inertial measurement unit, motion speed estimation, walking speed,
• MeSH
• bérec MeSH
• chodci * MeSH
• deep learning * MeSH
• lidé MeSH
• nositelná elektronika * MeSH
• pohyb těles MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

A new approach is proposed for lossless raster image compression employing interpolative coding. A new multifunction prediction scheme is presented first. Then, interpolative coding, which has not been applied frequently for image compression, is explained briefly. Its simplification is introduced in regard to the original approach. It is determined that the JPEG LS predictor reduces the information entropy slightly better than the multi-functional approach. Furthermore, the interpolative coding was moderately more efficient than the most frequently used arithmetic coding. Finally, our compression pipeline is compared against JPEG LS, JPEG 2000 in the lossless mode, and PNG using 24 standard grayscale benchmark images. JPEG LS turned out to be the most efficient, followed by JPEG 2000, while our approach using simplified interpolative coding was moderately better than PNG. The implementation of the proposed encoder is extremely simple and can be performed in less than 60 lines of programming code for the coder and 60 lines for the decoder, which is demonstrated in the given pseudocodes.

• Klíčová slova
• JPEG 2000 lossless, JPEG LS, PNG, algorithm, computer science, interpolative coding, predictions,
• Publikační typ
• časopisecké články MeSH

Land Cover and Land Use (LCLU) segmentation plays a fundamental role in various remote sensing applications, including environmental monitoring, urban planning, and disaster management. Traditional models often face limitations in real-time processing and deployment on resource-constrained devices due to their high computational requirements. This paper presents a lightweight neural network designed to address these challenges by integrating dense dilated convolutions with pyramid depthwise convolutions for multiscale feature extraction. The proposed encoder-decoder architecture utilizes dense connections to aggregate spatial and contextual information across different resolutions, enhancing segmentation accuracy while minimizing computational overhead. The model's performance was rigorously evaluated using the NITRDrone and UDD6 datasets, demonstrating a segmentation accuracy of 94.8%, with a significantly reduced parameter count compared to state-of-the-art methods. The compact design of the network facilitates its implementation on low-power devices, enabling real-time LCLU analysis across diverse environmental conditions. This work underscores the potential of lightweight neural networks to advance remote sensing image processing, offering scalable and efficient solutions for practical applications in geospatial analysis.

• Klíčová slova
• Context information aggregation module, Deep learning, Dense dilated convolution, Land cover land use LCLU, Lightweight implementation, Remote sensing,
• Publikační typ
• časopisecké články MeSH

OBJECTIVE: One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. APPROACH: In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. MAIN RESULTS: We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. SIGNIFICANCE: We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

• MeSH
• akční potenciály fyziologie   MeSH
• algoritmy * MeSH
• evokované potenciály fyziologie   MeSH
• lidé MeSH
• modely neurologické * MeSH
• neurony fyziologie   MeSH
• percepce fyziologie   MeSH
• počítačová simulace MeSH
• reprodukovatelnost výsledků MeSH
• senzitivita a specificita MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH
• práce podpořená grantem MeSH

The time to the first spike after stimulus onset typically varies with the stimulation intensity. Experimental evidence suggests that neural systems use such response latency to encode information about the stimulus. We investigate the decoding accuracy of the latency code in relation to the level of noise in the form of presynaptic spontaneous activity. Paradoxically, the optimal performance is achieved at a nonzero level of noise and suprathreshold stimulus intensities. We argue that this phenomenon results from the influence of the spontaneous activity on the stabilization of the membrane potential in the absence of stimulation. The reported decoding accuracy improvement represents a novel manifestation of the noise-aided signal enhancement.

• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

In kinetoplastid protists, all mitochondrial tRNAs are encoded in the nucleus and imported from the cytoplasm to maintain organellar translation. This also applies to the tryptophanyl tRNA (tRNATrp) encoded by a single-copy nuclear gene, with a CCA anticodon to read UGG codon used in the cytosolic translation. Yet, in the mitochondrion it is unable to decode the UGA codon specifying tryptophan. Following mitochondrial import of tRNATrp, this problem is solved at the RNA level by a single C34 to U34 editing event that creates the UCA anticodon, recognizing UGA. To identify the enzyme responsible for this critical editing activity, we scrutinized the genome of Trypanosoma brucei for putative cytidine deaminases as the most likely candidates. Using RNAi silencing and poisoned primer extension, we have identified a novel deaminase enzyme, named here TbmCDAT for mitochondrial Cytidine Deaminase Acting on tRNA, which is responsible for this organelle-specific activity in T. brucei. The ablation of TbmCDAT led to the downregulation of mitochondrial protein synthesis, supporting its role in decoding the UGA tryptophan codon.

• Klíčová slova
• Mitochondrion, cytidine deaminase, editing, trypanosoma, tryptophanyl tRNA,
• MeSH
• cytidin chemie   genetika   MeSH
• cytidindeaminasa genetika   metabolismus   MeSH
• konformace nukleové kyseliny MeSH
• mitochondrie enzymologie   genetika   MeSH
• RNA mitochondriální analýza   genetika   MeSH
• RNA protozoální analýza   genetika   MeSH
• RNA transferová Trp MeSH
• sekvence aminokyselin MeSH
• sekvence nukleotidů MeSH
• sekvenční homologie MeSH
• terminační kodon * MeSH
• Trypanosoma brucei brucei genetika   růst a vývoj   metabolismus   MeSH
• uridin chemie   genetika   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• cytidin MeSH
• cytidindeaminasa MeSH
• RNA mitochondriální MeSH
• RNA protozoální MeSH
• RNA transferová Trp MeSH
• terminační kodon * MeSH
• uridin MeSH

We report luminescent photon-upconversion barcodes for indexing the chemical content of droplets. The barcode is compatible with the simultaneous detection of fluorescence. The encoding and decoding of the initial concentration of enzyme β-galactosidase and substrate 4-methylumbelliferyl β-d-galactopyranoside are described. The fluorescent product 4-methylumbelliferone is detected simultaneously with the barcode.

• MeSH
• beta-galaktosidasa genetika   MeSH
• fluorescenční barviva * MeSH
• galaktosa MeSH
• mikrofluidika * MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• beta-galaktosidasa MeSH
• fluorescenční barviva * MeSH
• galaktosa MeSH

It is automatically assumed that the accuracy with which a stimulus can be decoded is entirely determined by the properties of the neuronal system. We challenge this perspective by showing that the identification of pure tone intensities in an auditory nerve fiber depends on both the stochastic response model and the arbitrarily chosen stimulus units. We expose an apparently paradoxical situation in which it is impossible to decide whether loud or quiet tones are encoded more precisely. Our conclusion reaches beyond the topic of auditory neuroscience, however, as we show that the choice of stimulus scale is an integral part of the neural coding problem and not just a matter of convenience.

• MeSH
• akustická stimulace metody   MeSH
• algoritmy * MeSH
• lidé MeSH
• modely neurologické * MeSH
• nervová vlákna fyziologie   MeSH
• nervové vedení fyziologie   MeSH
• nervus cochlearis fyziologie   MeSH
• počítačová simulace statistika a číselné údaje   MeSH
• stochastické procesy MeSH
• vnímání hlasitosti fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

In this paper, we propose a rateless codes-based communication protocol to provide security for wireless systems. In the proposed protocol, a source uses the transmit antenna selection (TAS) technique to transmit Fountain-encoded packets to a destination in presence of an eavesdropper. Moreover, a cooperative jammer node harvests energy from radio frequency (RF) signals of the source and the interference sources to generate jamming noises on the eavesdropper. The data transmission terminates as soon as the destination can receive a sufficient number of the encoded packets for decoding the original data of the source. To obtain secure communication, the destination must receive sufficient encoded packets before the eavesdropper. The combination of the TAS and harvest-to-jam techniques obtains the security and efficient energy via reducing the number of the data transmission, increasing the quality of the data channel, decreasing the quality of the eavesdropping channel, and supporting the energy for the jammer. The main contribution of this paper is to derive exact closed-form expressions of outage probability (OP), probability of successful and secure communication (SS), intercept probability (IP) and average number of time slots used by the source over Rayleigh fading channel under the joint impact of co-channel interference and hardware impairments. Then, Monte Carlo simulations are presented to verify the theoretical results.

• Klíčová slova
• co-channel interference, energy harvesting, hardware impairments, rateless codes, transmit antenna selection,
• Publikační typ
• časopisecké články MeSH