Position Of Label Research Articles

Independent Labels in the 1980s: Between the Underground and the Mainstream

Although small labels had always existed on the margins of the music industry, the DIY spirit of punk radically changed their numbers and outlook, and in the late 1970s labels such as Stiff, Rough Trade, Cherry Red and Mute were created. In the early 1980s, the creation of independent singles and albums charts (in opposition to the mainstream charts) and the coverage given to them in weekly music papers such as the New Musical Express and Sounds, raised the profile of independent labels, as did the commercial success of ‘indie’ bands such as the Smiths. This article examines three fundamental issues concerning independent labels during this period. Firstly, it will study the ideological underpinning of the raison d’être and activities of independent labels and the values they espoused. Secondly, it looks at how they engaged with the mainstream music industry and also how they attempted to differentiate themselves from it, as well as from more underground activities, such as those of the collective based on the punk group Crass. Finally, it moves on to the relationship between the ideological positions of independent labels and the music played by the bands they promoted.

A Novel Parallel Algorithm with Map Segmentation for Multiple Geographical Feature Label Placement Problem

Multiple geographical feature label placement (MGFLP) is an NP-hard problem that can negatively influence label position accuracy and the computational time of the algorithm. The complexity of such a problem is compounded as the number of features for labeling increases, causing the execution time of the algorithms to grow exponentially. Additionally, in large-scale solutions, the algorithm possibly gets trapped in local minima, which imposes significant challenges in automatic label placement. To address the mentioned challenges, this paper proposes a novel parallel algorithm with the concept of map segmentation which decomposes the problem of multiple geographical feature label placement (MGFLP) to achieve a more intuitive solution. Parallel computing is then utilized to handle each decomposed problem simultaneously on a separate central processing unit (CPU) to speed up the process of label placement. The optimization component of the proposed algorithm is designed based on the hybrid of discrete differential evolution and genetic algorithms. Our results based on real-world datasets confirm the usability and scalability of the algorithm and illustrate its excellent performance. Moreover, the algorithm gained superlinear speedup compared to the previous studies that applied this hybrid algorithm.

DEchorate: a calibrated room impulse response dataset for echo-aware signal processing

This paper presents a new dataset of measured multichannel room impulse responses (RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of microphones, real sources, and image sources under different wall configurations in a cuboid room. These data provide a tool for benchmarking recent methods in echo-aware speech enhancement, room geometry estimation, RIR estimation, acoustic echo retrieval, microphone calibration, echo labeling, and reflector position estimation. The dataset is provided with software utilities to easily access, manipulate, and visualize the data as well as baseline methods for echo-related tasks.

Radionuclide-labeled boron delivery agents

<p indent="0mm">Boron neutron capture therapy (BNCT), as a duality radiotherapy method that combines neutron irradiation and boron-containing targeted drugs, has attracted much attention. The successful BNCT mainly depends on three aspects: (1) Ideal boron delivery agents, (2) reasonable neutron source, and (3) accurate dose measurement system. Therefore, it is very important to realize the rapid and accurate measurement of the boron concentration in the patient. There are a variety of methods that have been used to measure the boron concentration. The indirect measurement method often requires the blood/tissue sample, so it can only give an estimate of the boron concentration at a single time point and sampling point, but cannot accurately describe the biodistribution of ¹⁰B concentration and the boron concentration ratio between target and non-target tissues. The sensitivity of magnetic resonance imaging (MRI) is poor, while radionuclide imaging is a non-invasive method and can provide the distribution of boron delivery agents <italic>in vivo</italic>. This article briefly describes the existing methods of measuring the boron concentration in BNCT, and the progress of radionuclide (¹⁸F, ¹²⁵I/¹³¹I, and ^99mTc) labeling methods of boron delivery agents (such as 4-borono-<italic>L</italic>-phenylalanine (BPA) and disodium mercaptoundecahydrododecaborate (BSH)) for radionuclide imaging. The common methods for labeling boron delivery agents with ¹⁸F are [¹⁸F]F₂ electrophilic substitution with a carrier, [¹⁸F]F⁻ nucleophilic substitution without a carrier, and isotope exchange. ¹⁸F-labeled BPA ([¹⁸F]-FBPA) was first prepared by the electrophilic substitution method. Research has shown that BPA and [¹⁸F]-FBPA had similar pharmacokinetics and biodistribution results. Although electrophilic fluorination can yield [¹⁸F]-FBPA with high radiochemical purity, the overall yield of the reaction is low, and the [¹⁸F]F₂ used in this process is relatively active and highly corrosive. The effect of stable F₂ gas carrier on the reaction cannot be ignored, which makes the specific activity of the product lower and the imaging quality worse. [¹⁸F]-FBPA can also be obtained from the high-value iodine-ylide precursors by nucleophilic fluoridation reaction. This method has a short labeling time and high specific activity. Fluoroboronotyrosine (FBY), a metabolically stable boron-tyrosine derivative, can also be used as a boron delivery agent, and [¹⁸F]-FBY has been prepared easily and quickly with a high radiochemical yield and radiochemical purity by isotope exchange as a tumor-targeting PET imaging agent. [¹⁸F]-FBY was stable <italic>in vitro</italic>, and it had the highest uptake in tumor and low uptake in normal tissue in mice with cutaneous melanoma grafts. The boron delivery agents of nested and closed carboranes can be radioiodine-labeled using N-chlorosuccinimide (NCS) as oxidant by electrophile iodization reaction at room temperature for <sc>10−30 min,</sc> the radiochemical yield was basically above 70%. Radioiodine-labeled carborane derivatives can also be achieved using isotope exchange reactions under catalytic conditions, but they had a lower specific activity. Unfortunately, as for the radioiodine-labeled carborane compounds, most studies only described the labeling method without further <italic>in vivo</italic> experimental data. [^99mTc(CO)₃]⁺-labeled carboranes have been prepared in aqueous solution in the presence of potassium fluoride under mild conditions, but no further biological experiments were conducted. ^99mTc-labeled BPA (^99mTc-DMG-BPA) was also obtained. Biodistribution result showed that the complex was selectively enriched in the tumor and cleared faster in non-target tissues, but unfortunately, its uptake in liver and kidney was relatively high, which may affect tumor imaging. In conclusion, radionuclide-labeled boron delivery agents are still in their infancy, and there are many aspects that need to be considered, such as radionuclide (half-life and decay type), radionuclide labeling position (influence on the biological activity of the boron delivery agent), labeling method (nucleophilic substitution, electrophilic substitution, isotope exchange, and coordination chemistry), the stability of the labeled compound and its influencing factors, and the administration method and time, etc.

Optimization of 4D-MR angiography based on superselective pseudo-continuous arterial spin labeling combined with CENTRA-keyhole and view-sharing (4D-S-PACK) for vessel-selective visualization of the internal carotid artery and vertebrobasilar artery systems

PurposeThis study investigated the optimal labeling position and gradient moment for 4D-MR angiography based on superselective pseudo-continuous arterial spin labeling combined with CENTRA-keyhole and view-sharing (4D-S-PACK) for vessel-selective flow visualization of the internal carotid artery (ICA) and vertebrobasilar artery (VBA) systems. MethodsSeven healthy volunteers were scanned with a 3.0 T MR scanner. To visualize the ICA system, the labeling focus was placed in the right ICA at 55, 75 and 95 mm below the imaging slab. To visualize the VBA system, the labeling focus was placed in the basilar artery (BA), upper vertebral artery (VA upper), and lower vertebral artery (VA lower). Two sizes of labeling focus were created using gradient moments of 0.5 and 0.75 mT/m ms. The contrast-to-noise ratio (CNR) was measured in the middle cerebral artery (MCA) and posterior cerebral artery (PCA) branches. ResultsCNRs increased as the distance between the center of the imaging slab and the labeling position decreased in all MCA segments. CNRs obtained with VA lower tended to be higher than those obtained with BA and VA upper in all PCA segments. Selective vessel visualization was achieved with the gradient moment of 0.75 mT/m ms for the ICA and VBA system. ConclusionThe optimal 4D-S-PACK gradient moment was found to be 0.75 mT/m ms for the ICA and VBA systems. When visualizing the ICA system, the labeling position should be placed as close as possible to the imaging slab. When visualizing the VBA system, the labeling position should be placed at VA lower .

Machine Vision for Real-Time Intraoperative Anatomic Guidance: A Proof-of-Concept Study in Endoscopic Pituitary Surgery.

Current intraoperative orientation methods either rely on preoperative imaging, are resource-intensive to implement, or difficult to interpret. Real-time, reliable anatomic recognition would constitute another strong pillar on which neurosurgeons could rest for intraoperative orientation. To assess the feasibility of machine vision algorithms to identify anatomic structures using only the endoscopic camera without prior explicit anatomo-topographic knowledge in a proof-of-concept study. We developed and validated a deep learning algorithm to detect the nasal septum, the middle turbinate, and the inferior turbinate during endoscopic endonasal approaches based on endoscopy videos from 23 different patients. The model was trained in a weakly supervised manner on 18 and validated on 5 patients. Performance was compared against a baseline consisting of the average positions of the training ground truth labels using a semiquantitative 3-tiered system. We used 367 images extracted from the videos of 18 patients for training, as well as 182 test images extracted from the videos of another 5 patients for testing the fully developed model. The prototype machine vision algorithm was able to identify the 3 endonasal structures qualitatively well. Compared to the baseline model based on location priors, the algorithm demonstrated slightly but statistically significantly (P < .001) improved annotation performance. Automated recognition of anatomic structures in endoscopic videos by means of a machine vision model using only the endoscopic camera without prior explicit anatomo-topographic knowledge is feasible. This proof of concept encourages further development of fully automated software for real-time intraoperative anatomic guidance during surgery.

Intrinsic anisotropy parameters of a series of lanthanoid complexes deliver new insights into the structure-magnetism relationship

Intrinsic anisotropy parameters of a series of lanthanoid complexes deliver new insights into the structure-magnetism relationship

Influence of the Position and Composition of Radiometals and Radioiodine Labels on Imaging of Epcam Expression in Prostate Cancer Model Using the DARPin Ec1.

Simple SummaryMetastasis-targeting therapy might improve outcomes in oligometastatic prostate cancer. Epithelial cell adhesion molecule (EpCAM) is overexpressed in 40–60% of prostate cancer cases and might be used as a target for specific delivery of toxins and drugs. Radionuclide molecular imaging could enable non-invasive detection of EpCAM and stratification of patients for targeted therapy. Designed ankyrin repeat proteins (DARPins) are scaffold proteins, which can be selected for specific binding to different targets. The DARPin Ec1 binds strongly to EpCAM. To determine an optimal design of Ec1-based probes, we labeled Ec1 at two different positions with four different nuclides (68Ga, 111In, 57Co and 125I) and investigated the impact on Ec1 biodistribution. We found that the C-terminus is the best position for labeling and that 111In and 125I provide the best imaging contrast. This study might be helpful for scientists developing imaging probes based on scaffold proteins.The epithelial cell adhesion molecule (EpCAM) is intensively overexpressed in 40–60% of prostate cancer (PCa) cases and can be used as a target for the delivery of drugs and toxins. The designed ankyrin repeat protein (DARPin) Ec1 has a high affinity to EpCAM (68 pM) and a small size (18 kDa). Radiolabeled Ec1 might be used as a companion diagnostic for the selection of PCa patients for therapy. The study aimed to investigate the influence of radiolabel position (N- or C-terminal) and composition on the targeting and imaging properties of Ec1. Two variants, having an N- or C-terminal cysteine, were produced, site-specifically conjugated to a DOTA chelator and labeled with cobalt-57, gallium-68 or indium-111. Site-specific radioiodination was performed using ((4-hydroxyphenyl)-ethyl)maleimide (HPEM). Biodistribution of eight radiolabeled Ec1-probes was measured in nude mice bearing PCa DU145 xenografts. In all cases, positioning of a label at the C-terminus provided the best tumor-to-organ ratios. The non-residualizing [125I]I-HPEM label provided the highest tumor-to-muscle and tumor-to-bone ratios and is more suitable for EpCAM imaging in early-stage PCa. Among the radiometals, indium-111 provided the highest tumor-to-blood, tumor-to-lung and tumor-to-liver ratios and could be used at late-stage PCa. In conclusion, label position and composition are important for the DARPin Ec1.

Bi-directional Long Short-Term Memory Model with Semantic Positional Attention for the Question Answering System

The intelligent question answering system aims to provide quick and concise feedback on the questions of users. Although the performance of phrase-level and numerous attention models have been improved, the sentence components and position information are not emphasized enough. This article combines Ci-Lin and word2vec to divide all of the words in the question-answer pairs into groups according to the semantics and select one kernel word in each group. The remaining words are common words and realize the semantic mapping mechanism between kernel words and common words. With this Chinese semantic mapping mechanism, the common words in all questions and answers are replaced by the semantic kernel words to realize the normalization of the semantic representation. Meanwhile, based on the bi-directional LSTM model, this article introduces a method of the combination of semantic role labeling and positional context, dividing the sentence into multiple semantic segments according to semantic logic. The weight is given to the neighboring words in the same semantic segment and propose semantic role labeling position attention based on the bi-directional LSTM model (BLSTM-SRLP). The good performance of the BLSTM-SRLP model has been demonstrated in comparative experiments on the food safety field dataset (FS-QA).

In Vivo Behavior of the Antibacterial Peptide Cyclo[RRRWFW], Explored Using a 3-Hydroxychromone-Derived Fluorescent Amino Acid.

Labeling biomolecules with fluorescent labels is an established tool for structural, biochemical, and biophysical studies; however, it remains underused for small peptides. In this work, an amino acid bearing a 3-hydroxychromone fluorophore, 2-amino-3-(2-(furan-2-yl)-3-hydroxy-4-oxo-4H-chromen-6-yl)propanoic acid (FHC), was incorporated in a known hexameric antimicrobial peptide, cyclo[RRRWFW] (cWFW), in place of aromatic residues. Circular dichroism spectropolarimetry and antibacterial activity measurements demonstrated that the FHC residue perturbs the peptide structure depending on labeling position but does not modify the activity of cWFW significantly. FHC thus can be considered an adequate label for studies of the parent peptide. Several analytical and imaging techniques were used to establish the activity of the obtained labeled cWFW analogues toward animal cells and to study the behavior of the peptides in a multicellular organism. The 3-hydroxychromone fluorophore can undergo excited-state intramolecular proton transfer (ESIPT), resulting in double-band emission from its two tautomeric forms. This feature allowed us to get insights into conformational equilibria of the labeled peptides, localize the cWFW analogues in human cells (HeLa and HEK293) and zebrafish embryos, and assess the polarity of the local environment around the label by confocal fluorescence microscopy. We found that the labeled peptides efficiently penetrated cancerous cells and localized mainly in lipid-containing and/or other nonpolar subcellular compartments. In the zebrafish embryo, the peptides remained in the bloodstream upon injection into the cardinal vein, presumably adhering to lipoproteins and/or microvesicles. They did not diffuse into any tissue to a significant extent during the first 3 h after administration. This study demonstrated the utility of fluorescent labeling by double-emission labels to evaluate biologically active peptides as potential drug candidates in vivo.

Geometry and water accessibility of the inhibitor binding site of Na+-pump: Pulse- and CW-EPR study

Spin labels based on cinobufagin, a specific inhibitor of the Na,K-ATPase, have proved valuable tools to characterize the binding site of cardiotonic steroids (CTSs), which also constitutes the extracellular cation pathway. Because existing literature suggests variations in the physiological responses caused by binding of different CTSs, we extended the original set of spin-labeled inhibitors to the more potent bufalin derivatives. Positioning of the spin labels within the Na,K-ATPase site was defined and visualized by molecular docking. Although the original cinobufagin labels exhibited lower affinity, continuous-wave electron paramagnetic resonance spectra of spin-labeled bufalins and cinobufagins revealed a high degree of pairwise similarity, implying that these two types of CTS bind in the same way. Further analysis of the spectral lineshapes of bound spin labels was performed with emphasis on their structure (PROXYL vs. TEMPO), as well as length and rigidity of the linkers. For comparable structures, the dynamic flexibility increased in parallel with linker length, with the longest linker placing the spin label at the entrance to the binding site. Temperature-related changes in spectral lineshapes indicate that six-membered nitroxide rings undergo boat-chair transitions, showing that the binding-site cross section can accommodate the accompanying changes in methyl-group orientation. D2O-electron spin echo envelope modulation in pulse-electron paramagnetic resonance measurements revealed high water accessibilities and similar polarity profiles for all bound spin labels, implying that the vestibule leading to steroid-binding site and cation-binding sites is relatively wide and water-filled.

Learning Precise Temporal Point Event Detection with Misaligned Labels

This work addresses the problem of robustly learning precise temporal point event detection despite only having access to poorly aligned labels for training. While standard (cross entropy-based) methods work well in noise-free setting, they often fail when labels are unreliable since they attempt to strictly fit the annotations. A common solution to this drawback is to transform the point prediction problem into a distribution prediction problem. However, we show that this approach raises several issues that negatively affect the robust learning of temporal localization. Thus, in an attempt to overcome these shortcomings, we introduce a simple and versatile training paradigm combining soft localization learning with counting-based sparsity regularization. In fact, unlike its counterparts, our approach allows to directly infer clear-cut point predictions in an end-to-end fashion while relaxing the reliance of the training on the exact position of labels. We achieve state-of-the-art performance against standard benchmarks in a number of challenging experiments (e.g., detection of instantaneous events in videos and music transcription) by simply replacing the original loss function with our novel alternative---without any additional fine-tuning.

Shade recognition of the color label based on the fuzzy clustering

In this article the task of determining the current position of pneumatic actuators is considered. The solution to the given task is achieved by using a technical vision system that allows to apply the fuzzy clustering method to determine in real time the center coordinates and the displacement position of a color label located on the mechatronic complex actuators. The objective of this work is to improve the accuracy of the moving actuator’s of mechatronic complex by improving the accuracy of the color label recognition. The intellectualization of process of the color shade recognition is based on fuzzy clustering. First, a fuzzy model is built, that allows depending on the input parameters of the color intensity for each of the RGB channels and the color tone component, to select a certain color in the image. After that, the color image is binarized and noise is suppressed. The authors used two defuzzification models during simulation a fuzzy system: one is based on the center of gravity method (CoG) and the other is based on the method of area ratio (MAR). The model is implemented based on the method of area ratio and allows to remove the dead zones that are present in the center of gravity model. The method of area ratio determines the location of the color label in the image frame. Subsequently, when the actuator is moved longitudinally, the vision system determines the location of the color label in the new frame. The color label position offset between the source and target images allows to determine the moved distance of the color label. In order to study how noise affects recognition accuracy, the following digital filters were used: median, Gaussian, matrix and binomial. Analysis of the accuracy of these filters showed that the best result was obtained when using a Gaussian filter. The estimation was based on the signal-to-noise coefficient. The mathematical models of fuzzy clustering of color label recognition were simulated in the Matlab/Simulink environment. Experimental studies of technical vision system performance with the proposed fuzzy clustering model were carried out on a pneumatic mechatronic complex that performs processing, moving and storing of details. During the experiments, a color label was placed on the cylinder, after which the cylinder moved along the guides in the longitudinal direction. During the movement, video recording and image recognition were performed. To determine the accuracy of color label recognition, the PSNR and RMSE coefficients were calculated which were equal 38.21 and 3.14, respectively. The accuracy of determining the displacement based on the developed model for recognizing color labels was equal 99.7%. The defuzzifier speed has increased to 590 ns.

Redesign packaging on Aloe Vera bottle product based on Kansei Engineering

Packaged designers must be able to select packaging elements that characterize products, communicate brand products, and create packaging into attractive media to attract consumers to purchase products among the various available products. The aim of this study is to understand visual design concepts and structural design concepts in the design of aloe vera bottled bottles. The method used for the development of a design product that focuses on consumer perceptions and links it with the attributes of the product is Kansei engineering. Kansei engineering is a technology capable of translating consumer feelings into design concepts. Research came up with a visual design concept of the chosen Kansei word, which is elegant, commercial, fresh, modern, varnish, aesthetic, interesting, simple, subjective, summarized. The visual design concept is barcode, nutrition fact-general, 1ogo-word mark, brand top sign, product name-top sign, produce-bearing name, product present composition, family-size approach, back ground cool colors, font color-white, font type-san serif, Figure-original, material label-film plastic, and position label-wrap around label positions. The structural design concept is tropical as the top structure of the bottle, jugo as the center structure of the bottle, plastic colored as bottled material, and the size of the bottle 500 ml.

Relationships between spinal cord blood flow measured with flow-sensitive alternating inversion recovery (FAIR) and neurobehavioral outcomes in rat spinal cord injury

In the traumatically injured spinal cord, decreased perfusion is believed to contribute to secondary tissue damage beyond the primary mechanical impact, and restoration of perfusion is believed to be a promising therapeutic target. However, methods to monitor spinal cord perfusion non-invasively are limited. Perfusion magnetic resonance imaging (MRI) techniques established for the brain have not been routinely adopted to the spinal cord. The purpose of this study was to examine the relationship between spinal cord blood flow (SCBF) and injury severity in a rat thoracic spinal cord contusion injury (SCI) model using flow-sensitive alternating inversion recovery (FAIR) with two variants of the label position. SCBF as a marker of severity was compared to T1 mapping and to spinal cord-optimized diffusion weighted imaging (DWI) with filtered parallel apparent diffusion coefficient. Thirty-eight rats underwent a T10 contusion injury with varying severities (8 sham; 10 mild; 10 moderate; 10 severe) with MRI performed at 1 day post injury at the lesion site and follow-up neurological assessments using the Basso, Beattie, Bresnahan (BBB) locomotor scoring up to 28 days post injury. Using whole-cord regions of interest at the lesion epicenter, SCBF was decreased with injury severity and had a significant correlation with BBB scores at 28 days post injury. Importantly, estimates of arterial transit times (ATT) in the injured spinal cord were not altered after injury, which suggests that FAIR protocols optimized to measure SCBF provide more value in the context of acute traumatic injury to the cord. T1-relaxation time constants were strongly related to injury severity and had a larger extent of changes than either SCBF or DWI measures. These findings suggest that perfusion decreases in the spinal cord can be monitored non-invasively after injury, and multi-parametric MRI assessments of perfusion, diffusion, and relaxation capture unique features of the pathophysiology of preclinical injury.

Analysis of pyrene-labelled apolipoprotein A-I oligomerization in solution: Spectra deconvolution and changes in P-value and excimer formation

ApoA-I is the main protein of HDL which has anti-atherogenic properties attributed to reverse cholesterol transport. It shares with other exchangeable apolipoproteins a high level of structural plasticity. In the lipid-free state, the apolipoprotein amphipathic α-helices interact intra- and inter-molecularly, providing structural stabilization by a complex self-association mechanism. In this study, we employed a multi-parametric fluorescent probe to study the self-association of apoA-I. We constructed six single cysteine mutants spanning positions along three helices: F104C, K107C (H4), K133C, L137C (H5), F225C and K226C (H10); and labelled them with N-Maleimide Pyrene. Taking advantage of its spectral properties, namely formation of an excited dimer (excimer) and polarity-dependent changes in its fluorescence fine structure (P-value), we monitored the apoA-I self-association in its lipid-free form as a function of its concentration. Interactions in helices H5 (K133C) and H10 (F225C and K226C) were highlighted by excimer emission; while polarity changes were reported in helix H4 (K107C), as well as in helices H5 and H10. Mathematical models were developed to enrich data analysis and estimate association constants (KA) and oligomeric species distribution. Furthermore, we briefly discuss the usefulness of the multi-parametric fluorescent probe to monitor different equilibria, even at a single labelling position. Results suggest that apoA-I self-association must be considered to fully understand its physiological roles. Particularly, some contacts that stabilize discoidal HDL particles seem to be already present in the lipid-free apoA-I oligomers.

Sequential semi-supervised segmentation for serial electron microscopy image with small number of labels

BackgroundSegmentation of electron microscopic continuous section images by deep learning has attracted attention as a technique to reduce the cost of annotation for researchers attempting to make observations using 3D reconstruction methods. However, when the observed samples are rare, or scanning circumstances are unstable, pursuing generalization performance for newly obtained samples is not appropriate. New methodsWe assume a transductive setting that predicts all labels in a dataset from only partially obtained labels while avoiding the pursuit of generalization performance for unknown data. Then, we propose sequential semi-supervised segmentation (4S), which semi-automatically extracts neural regions from electron microscopy image stacks. This method focuses on the fact that adjacent images have a strong correlation in serial images. Our 4S repeats training, inference, and pseudo-labeling using a minimal number of teacher labels and performs segmentation on all slices. ResultOur experiments using two types of serial section images showed effectiveness in terms of both quality and quantity. In addition, we experimentally clarified the effect of the number and position of teacher labels on performance. Comparison with existing methodsCompared with supervised learning when a small number of labeled data was obtained, the performance of the proposed method was shown to be superior. ConclusionOur 4S leverages a limited number of labeled data and a large amount of unlabeled data to extract neural regions from serial image stacks in a transductive setting. We plan to develop this method as a core module of a general-purpose annotation tool in our future work.

Vision-Based Robotic Solution for Wire Insertion With an Assigned Label Orientation

This paper tackles the problem of wire insertion in switchgear assembly according to the current regulations. In particular, the wire connections require that the wire label has to be oriented facing up in order to simplify and speed up testing and maintenance of the switchgear. The proposed approach exploits the a priori knowledge of the scenario with a calibrated RGB camera and a robotic arm to estimate both wire end pose and label position. The procedure combines several techniques (gradient base, trained classifier and stereo vision) to elaborate standard images in order to extract some wire features related to its shape and label. Specific frames are fixed according to estimated features and then used to correctly complete the task by using a robotic system. Experiments are reported to verify the effectiveness of the proposed approach.

RFID aided SINS integrated navigation system for lane applications

To improve the lane vehicle position accuracy, RFID technology is applied to correct the position of the SINS irregularly with label positioning. The acceleration data of the vehicle in three directions is measured by the accelerometers of the inertial measurement unit, the attitude matrix is updated in real time using the angular velocity of the gyroscope output space, the acceleration component is transformed into the geographic coordinate system, and the acceleration of the inertial measurement unit. The data is subjected to an integral operation process to obtain a spatial displacement value of the vehicle. The real-time updating algorithm of the attitude matrix and the processing of the inertial measurement unit signal are presented. The quaternion-based algorithm is used to solve the attitude matrix as well as updating the coordinate system of the inertial navigation attitude matrix in real time. The Hilbert-Huang transform is used to filter the acceleration signal to solve the integrator saturation problem caused by the low-frequency component of the acceleration signal. The EMD algorithm based on the continuous root mean square error is applied in rejecting the low-frequency components in the signal. The simulation experiments show that the system can be reliable and high precision.

Multiple Geographical Feature Label Placement Based on Multiple Candidate Positions in Two Degrees of Freedom Space

Automatic multiple geographical feature label placement (MGFLP) is a combinatorial optimization problem shown to be an NP-hard problem, and it is a challenge in automatic cartography. Many automatic label placement algorithms for point, line, and area features were put forward. It is a common way to use multiple candidate positions (MCP) for label placement, but the research in this way mostly focuses on point features and does not take all three types of features and all the possible candidate positions into account on the map. Therefore, in this paper, the concept of degrees of spatial freedom for feature label placement is proposed based on the idea of degrees of freedom of mechanical motion. We define the degrees of freedom (DOF) and its space for feature labels on a planar map so as the potential space, including all the optional candidate positions of each feature label, can be standardized. Based on two degrees of freedom (2-DOF) space, feature reference position (FRP), and certain buffer distance (CBD) from FRP, we studied the methods including generating, calculating, evaluating, and selecting MCP for feature label. By using and improving the discrete differential evolution genetic algorithm (DDEGA), we carried out MGFLP experiments on the same dataset used by DDEGA algorithm. The results show that: 1) although the MCP based on the 2-DOF space increase the complexity of the NP-hard problem, however, the obtained results by optimizing the performance of the algorithm and increasing the number of candidate positions are still better than the traditional 8-candidate positions model. 2) In the same 2-DOF space, increasing the candidate positions from less to more along each direction of the 2-DOF space improves the quality of label placement.