Relevant bibliographies by topics / DMSL method

Academic literature on the topic 'DMSL method'

Author: Grafiati
Published: 8 June 2024

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "DMSL method":

1

Walczak, Mariusz, Aleksander Świetlicki, Mirosław Szala, Marcin Turek, and Dariusz Chocyk. "Shot Peening Effect on Sliding Wear in 0.9% NaCl of Additively Manufactured 17-4PH Steel." Materials 17, no. 6 (March 18, 2024): 1383. http://dx.doi.org/10.3390/ma17061383.

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The growing demand for modern steels showing corrosion and tribological resistance has led to their increased use in the production of medical devices. This study analyzed the effect of shot peening on wear resistance in 0.9% NaCl solution of 17-4PH steel produced by direct laser metal sintering (DMLS) technology. The study’s novelty relies on revealing the effect of shot peening (SP) surface treatment on the wet sliding wear resistance of 17-4PH steel produced with DMLS. Moreover, in the context of 17-4PH steel application for medical devices, the 0.9% NaCl tribological environment were selected, and SP processes were conducted using steel CrNi shot and ceramic (ZrO2) beads. The up-to-date scientific literature has not identified these gaps in the research. DMLS technology makes it possible to obtain products with complex architectures, but it also faces various challenges, including imperfections in the surface layer of products due to the use of 3D printing technology itself. The chemical and phase composition of the materials obtained, Vickers hardness, surface roughness, and microscopic and SEM imaging were investigated. Tribological tests were carried out using the ball-on-disc method, and the surfaces that showed traces of abrasion to identify wear mechanisms were subjected to SEM analysis. The XRD phase analysis indicates that austenite and martensite were found in the post-production state, while a higher martensitic phase content was found in peened samples due to phase transformations. The surface hardness of the peened samples increased by more than double, and the post-treatment roughness increased by 12.8% after peening CrNi steels and decreased by 7.8% after peening ZrO2 relative to the reference surfaces. Roughness has an identifiable effect on sliding wear resistance. Higher roughness promotes material loss. After the SP process, the coefficient of friction increased by 15.5% and 20.7%, while the wear factor (K) decreased by 25.9% and 32.7% for the samples peened with CrNi steels and ZrO2, respectively. Abrasive and adhesive mechanisms were dominant, featured with slight fatigue. The investigation showed a positive effect of SP on the tribological properties of DMSL 17-4PH.
2

Kinsey, Joanna D., and David J. Kieber. "Microwave preservation method for DMSP, DMSO, and acrylate in unfiltered seawater and phytoplankton culture samples." Limnology and Oceanography: Methods 14, no. 3 (January 12, 2016): 196–209. http://dx.doi.org/10.1002/lom3.10081.

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3

Zhang, Xizhen, Aiwu Zhang, Yuan Sun, Juan Wang, Haiyang Pang, Jinbang Peng, Yunsheng Chen, et al. "Deep Multi-Order Spatial–Spectral Residual Feature Extractor for Weak Information Mining in Remote Sensing Imagery." Remote Sensing 16, no. 11 (May 29, 2024): 1957. http://dx.doi.org/10.3390/rs16111957.

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Remote sensing images (RSIs) are widely used in various fields due to their versatility, accuracy, and capacity for earth observation. Direct application of RSIs to harvest optimal results is generally difficult, especially for weak information features in the images. Thus, extracting the weak information in RSIs is reasonable to promote further applications. However, the current techniques for weak information extraction mainly focus on spectral features in hyperspectral images (HSIs), and a universal weak information extraction technology for RSI is lacking. Therefore, this study focused on mining the weak information from RSIs and proposed the deep multi-order spatial–spectral residual feature extractor (DMSRE). The DMSRE considers the global information and three-dimensional cube structures by combining low-rank representation, high-order residual quantization, and multi-granularity spectral segmentation theories. This extractor obtains spatial–spectral features from two derived sequences (deep spatial–spectral residual feature (DMSR) and deep spatial–spectral coding feature (DMSC)), and three RSI datasets (i.e., Chikusei, ZY1-02D, and Pasture datasets) were employed to validate the DMSRE method. Comparative results of the weak information extraction-based classifications (including DMSR and DMSC) and the raw image-based classifications showed the following: (i) the DMSRs can improve the classification accuracy of individual classes in fine classification applications (e.g., Asphalt class in the Chikusei dataset, from 89.12% to 95.99%); (ii) the DMSC improved the overall accuracy in rough classification applications (from 92.07% to 92.78%); and (iii) the DMSC improved the overall accuracy in RGB classification applications (from 63.25% to 63.6%), whereas DMSR improved the classification accuracy of individual classes on the RGB image (e.g., Plantain classes in the Pasture dataset, from 32.49% to 39.86%). This study demonstrates the practicality and capability of the DMSRE method to promote target recognition on RSIs and presents an alternative technique for weak information mining on RSIs, indicating the potential to extend weak information-based applications of RSIs.
4

Kong, Yingying, and Si Liu. "DMSC-GAN: A c-GAN-Based Framework for Super-Resolution Reconstruction of SAR Images." Remote Sensing 16, no. 1 (December 21, 2023): 50. http://dx.doi.org/10.3390/rs16010050.

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Synthetic Aperture Radar (SAR) imagery is significant in remote sensing, but the limited spatial resolution results in restricted detail and clarity. Current super-resolution methods confront challenges such as complex network structure, insufficient sensing capability, and difficulty extracting features with local and global dependencies. To address these challenges, DMSC-GAN, a SAR image super-resolution technique based on the c-GAN framework, is introduced in this study. The design objective of DMSC-GAN is to enhance the flexibility and controllability of the model by utilizing conditional inputs to modulate the generated image features. The method uses an encoder–decoder structure to construct a generator and introduces a feature extraction module that combines convolutional operations with Deformable Multi-Head Self-Attention (DMSA). This module can efficiently capture the features of objects of various shapes and extract important background information needed to recover complex image textures. In addition, a multi-scale feature extraction pyramid layer helps to capture image details at different scales. DMSC-GAN combines perceptual loss and feature matching loss and, with the enhanced dual-scale discriminator, successfully extracts features from SAR images for high-quality super-resolution reconstruction. Extensive experiments confirm the excellent performance of DMSC-GAN, which significantly improves the spatial resolution and visual quality of SAR images. This framework demonstrates strong capabilities and potential in advancing super-resolution techniques for SAR images.
5

Dong, Lihu, Yue Zhang, Zhuo Zhang, Longfei Xie, and Fengri Li. "Comparison of Tree Biomass Modeling Approaches for Larch (Larix olgensis Henry) Trees in Northeast China." Forests 11, no. 2 (February 11, 2020): 202. http://dx.doi.org/10.3390/f11020202.

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Accurate quantification of tree biomass is critical and essential for calculating carbon storage, as well as for studying climate change, forest health, forest productivity, nutrient cycling, etc. Tree biomass is typically estimated using statistical models. Although various biomass models have been developed thus far, most of them lack a detailed investigation of the additivity properties of biomass components and inherent correlations among the components and aboveground biomass. This study compared the nonadditive and additive biomass models for larch (Larix olgensis Henry) trees in Northeast China. For the nonadditive models, the base model (BM) and mixed effects model (MEM) separately fit the aboveground and component biomass, and they ignore the inherent correlation between the aboveground and component biomass of the same tree sample. For the additive models, two aggregated model systems with one (AMS1) and no constraints (AMS2) and two disaggregated model systems without (DMS1) and with an aboveground biomass model (DMS2) were fitted simultaneously by weighted nonlinear seemingly unrelated regression (NSUR) and applied to ensure additivity properties. Following this, the six biomass modeling approaches were compared to improve the prediction accuracy of these models. The results showed that the MEM with random effects had better model fitting and performance than the BM, AMS1, AMS2, DMS1, and DMS2; however, when no subsample was available to calculate random effects, AMS1, AMS2, DMS1, and DMS2 could be recommended. There was no single biomass modeling approach to predict biomass that was best for all aboveground and component biomass except for MEM. The overall ranking of models based on the fit and validation statistics obeyed the following order: MEM > DMS1 > AMS2 > AMS1> DMS2 > BM. This article emphasized more on the methodologies and it was expected that the methods could be applied by other researchers to develop similar systems of the biomass models for other species, and to verify the differences between the aggregated and disaggregated model systems. Overall, all biomass models in this study have the benefit of being able to predict aboveground and component biomass for larch trees and to be used to predict biomass of larch plantations in Northeast China.
6

Mishra, Pawan Kumar, and Adam Ekielski. "A Simple Method to Synthesize Lignin Nanoparticles." Colloids and Interfaces 3, no. 2 (June 10, 2019): 52. http://dx.doi.org/10.3390/colloids3020052.

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The self-assembly of lignin (molecular and supramolecular) is driven mainly by non-covalent interactions, and the nature of the solvents and antisolvents directly affect the driving forces. The lignin particle is usually formed by noncovalently bonded cylindrical subunits. In this paper, we report a simple method which can be used to synthesize lignin nanoparticles by using spray freezing. The method is based on two properties of dimethyl sulfoxide (DMSO) that are excellent lignin solubility and a high melting point. Based on these two properties, kraft lignin solution in DMSO was sprayed onto liquid nitrogen-cooled copper plates using a handheld spray. The high melting point of DMSO caused immediate freezing and particle formation. The obtained particles were characterized for their size and morphology using dynamic light scattering (DLS), as well as scanning electron microscopy (SEM). Nano-range polydispersed particles were obtained by spraying 0.05% of lignin onto DMSO. This method can avoid lignin–solvent–antisolvent interactions, and can also be used to study lignin–lignin (subunits) and lignin–DMSO interactions.
7

Griebler, Christian, and Doris Slezak. "Microbial Activity in Aquatic Environments Measured by Dimethyl Sulfoxide Reduction and Intercomparison with Commonly Used Methods." Applied and Environmental Microbiology 67, no. 1 (January 1, 2001): 100–109. http://dx.doi.org/10.1128/aem.67.1.100-109.2001.

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ABSTRACT A new method to determine microbial (bacterial and fungal) activity in various freshwater habitats is described. Based on microbial reduction of dimethyl sulfoxide (DMSO) to dimethyl sulfide (DMS), our DMSO reduction method allows measurement of the respiratory activity in interstitial water, as well as in the water column. DMSO is added to water samples at a concentration (0.75% [vol/vol] or 106 mM) high enough to compete with other naturally occurring electron acceptors, as determined with oxygen and nitrate, without stimulating or inhibiting microbial activity. Addition of NaN3, KCN, and formaldehyde, as well as autoclaving, inhibited the production of DMS, which proves that the reduction of DMSO is a biotic process. DMSO reduction is readily detectable via the formation of DMS even at low microbial activities. All water samples showed significant DMSO reduction over several hours. Microbially reduced DMSO is recovered in the form of DMS from water samples by a purge and trap system and is quantified by gas chromatography and detection with a flame photometric detector. The DMSO reduction method was compared with other methods commonly used for assessment of microbial activity. DMSO reduction activity correlated well with bacterial production in predator-free batch cultures. Cell-production-specific DMSO reduction rates did not differ significantly in batch cultures with different nutrient regimes but were different in different growth phases. Overall, a cell-production-specific DMSO reduction rate of 1.26 × 10−17 ± 0.12 × 10−17 mol of DMS per produced cell (mean ± standard error;R 2 = 0.78) was calculated. We suggest that the relationship of DMSO reduction rates to thymidine and leucine incorporation is linear (the R 2 values ranged from 0.783 to 0.944), whereas there is an exponential relationship between DMSO reduction rates and glucose uptake, as well as incorporation (the R 2 values ranged from 0.821 to 0.931). Based on our results, we conclude that the DMSO reduction method is a nonradioactive alternative to other methods commonly used to assess microbial activity.
8

Ren, Shengbing, Wangbo Shen, Chaudry Siddique, and You Li. "Self-Adaptive Deep Multiple Kernel Learning Based on Rademacher Complexity." Symmetry 11, no. 3 (March 5, 2019): 325. http://dx.doi.org/10.3390/sym11030325.

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The deep multiple kernel learning (DMKL) method has caused widespread concern due to its better results compared with shallow multiple kernel learning. However, existing DMKL methods, which have a fixed number of layers and fixed type of kernels, have poor ability to adapt to different data sets and are difficult to find suitable model parameters to improve the test accuracy. In this paper, we propose a self-adaptive deep multiple kernel learning (SA-DMKL) method. Our SA-DMKL method can adapt the model through optimizing the model parameters of each kernel function with a grid search method and change the numbers and types of kernel function in each layer according to the generalization bound that is evaluated with Rademacher chaos complexity. Experiments on the three datasets of University of California—Irvine (UCI) and image dataset Caltech 256 validate the effectiveness of the proposed method on three aspects.
9

Tang, Jingjing, and Xilong Qiu. "Preparation of Dendritic Mesoporous Silica Nanomaterials Loaded with Toosendanin-Fumaracetin and its Anti-Peripheral Pain Study." Highlights in Science, Engineering and Technology 21 (December 4, 2022): 281–85. http://dx.doi.org/10.54097/hset.v21i.3172.

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Objective: A novel dendritic mesoporous silica nanomaterials (DMSN) was prepared and the traditional Chinese Medicine Component "Toosendanin-Tetrahydropalmatine" was loaded into DMSN in order to improve the solubility of Tetrahydropalmatine B, reduce the toxicity of Toosendanin, and enhance the anti-peripheral pain effect of the traditional. Chinese Medicine "Toosendanin-Tetrahydropalmatine" through preliminary pharmacodynamics study. Methods: DMSN were prepared using the sol-gel method and characterized by scanning electron microscope (SEM) and Fourier Transform Infrared Spectrometer (FT-IR). The preliminary study of the anti-peripheral pain pharmacodynamics of the drug-loaded system in mice was evaluated by the hot plate method. Results: The prepared DMSN has an excellent spherical shape in SEM, the size distribution of the DMSN is about 200nm, the size distribution is uniform, and the dispersion is good. The infrared results showed that the synthesized DMSN had organic functional groups and chemical structures. Compared with the control group, the pain threshold of DMSN loaded with the Toosendanin-tetrahydropalmatine group was prolonged by 45 seconds. Conclusion: The synthesized DMSN loaded with Toosendanin and Tetrahydropalmatine could release stably and continuously and had the effect of extending the pain threshold of mice. Therefore, DMSN drug delivery system has potential value in improving the bioabsorption of dangerous drugs and enhancing the bioavailability of poorly soluble drugs.
10

Page, Cheryl, and Jessica Rebeiro. "Évaluation de l’efficacité d’un programme de formation sur l’administration par bolus intraveineux de cellules souches hématopoïétiques cryoconservées." Canadian Oncology Nursing Journal 33, no. 2 (April 28, 2023): 207–14. http://dx.doi.org/10.5737/23688076332207.

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Les infirmières autorisées (inf. aut.) d’un centre de traitement cellulaire ont bénéficié d’un programme de formation sur l’administration par bolus intraveineux de cellules cryoconservées. Les deux principales méthodes servant à administrer les produits de cellules souches hématopoïétiques (CSH) cryoconservées à l’aide de diméthylsulfoxyde (DMSO) sont la perfusion par gravité et le bolus intraveineux. Quelle que soit la voie choisie, le DMSO peut provoquer des réactions d’hypersensibilité. La perfusion par gravité étant plus lente, le DMSO y entraîne moins de réactions. Toutefois, l’exposition prolongée au DMSO une fois les cellules décongelées accroît le risque de dommages cellulaires. La méthode du bolus intraveineux, plus rapide, réduit le risque de dommages cellulaires, de même que le temps de travail du personnel. Un examen des facteurs ambiants réalisé dans des centres de greffe du Canada a montré que, dans la plupart des établissements traitant des adultes, les infirmières s’occupent des perfusions par gravité, mais que lorsque les cellules souches hématopoïétiques cryoconservées doivent être injectées par bolus intraveineux, la procédure est accomplie par un médecin. Dans le centre dont il est question ici, le bolus intraveineux était administré soit par un médecin, soit par une infirmière praticienne (IP). Comme le nombre de greffes augmente, il fallait plus de personnes capables de réaliser cette procédure. Pour conserver les bénéfices actuels de la méthode du bolus intraveineux et augmenter la capacité du programme de greffes hématopoïétiques, on a transféré la tâche d’administrer les cellules souches par bolus intraveineux, qui revenait auparavant aux IP et aux médecins, aux infirmières autorisées. Un bon programme de formation a donc été élaboré, puis évalué; il utilise l’apprentissage par simulation pour aider les infirmières en oncologie à maîtriser cette nouvelle technique.
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Journal articles Dissertations / Theses

Dissertations / Theses on the topic "DMSL method":

1

Stańczak, Magda. "Behaviour of additively manufactured metallic structures under blast loading." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0073.

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La technique de fabrication additive permet d'étudier à l'échelle du laboratoire des structures métalliques à géométrie complexe. L'application de nouvelles structures peut être particulièrement bénéfique pour améliorer la capacité d'absorption d'énergie et d'atténuation des explosions. Dans cette thèse, le rôle de la topologie des structures en aluminium AlSi10Mg fabriquées de manière additive est étudiée. Plusieurs exemplaires de structures cellulaires sont présentées. On analysera la relation entre la densité relative et les réponses de déformation des structures, ainsi que les capacités d'absorption. Le comportement de l'alliage d'aluminium AlSi10Mg imprimé est étudié afin d'étudier l'influence des conditions du processus de fabrication sur les propriétés mécaniques. Pour compléter l'étude, une analyse de la microstructure déformée est également effectuée. Les résultats obtenus prouvent la complexité du comportement du matériau. Par conséquent, un modèle phénoménologique basé sur l'approche modifiée de Johnson-Cook est proposé. Le modèle développé décrit le comportement du matériau avec une bien meilleure précision que la fonction constitutive classique. Les simulations par éléments finis réalisées avec le logiciel LS-DYNA sont utilisées pour étudier en détail les mécanismes de déformation des structures. Les résultats montrent un bon accord avec les calculs analytiques et les observations expérimentales. Les réponses indiquent qu'en sélectionnant les paramètres topologiques appropriés, il est possible d'affecter significativement les performances des structures et ainsi d'améliorer leurs propriétés d'absorption d'énergie
The additive manufacturing technique allows for studies of metallic structures with complex geometry at a laboratory scale. The application of novel structures can be especially beneficial for improving the capacity of energy absorption and blast mitigation. In the presented thesis, the role of the topology of additively manufactured AlSi10Mg aluminum structures of several exemplary cellular structures (i.e., honeycomb, auxetic, lattice, and foam) is studied at static and blast compression. Furthermore, the relationship between the relative density and the deformationresponses of the structures, as well as the energy absorption capacities is analyzed. To investigate the influence of the manufacturing process conditions on the mechanical properties, the material behavior of the printed AlSi10Mg aluminum alloy is studied. For completeness, an analysis of the deformed microstructure is also conducted. The obtained results prove the complexity of the material behavior. Therefore, a phenomenological model based on the modified Johnson-Cook approach is proposed. The developed model describes the obtained characteristics of the printed alloy with much better accuracy than the classical constitutive function. The finite element simulations conducted in LS-DYNA software are used to investigate the deformation mechanisms of the structures in detail. The results are consistent with the analytical calculations and the experimental observations. The final responses indicate that by selecting the appropriate topological parameters, it is possible to affect the performance of structures significantly and thus to improve their energy absorption properties. The resulting experiments and their modeling show that the discussed material and the manufacturing technology have a promising potential
2

Kreschel, Martin. "Experimentelle und numerische Untersuchungen an Dehnungsmessstreifen (DMS) mit übereinanderliegenden Messgittern." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10447108.

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3

Kreschel, Martin. "Experimentelle und numerische Untersuchungen an Dehnungsmessstreifen (DMS) mit übereinanderliegenden Messgittern." Thesis, Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200201252.

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In der experimentellen Beanspruchungsanalyse ist der Einsatz von Dehnungsmessstreifen alltäglich. Besonders DMS-Rosetten mit übereinanderliegenden Messgittern bieten eine "punktgenaue" Auswertung des Dehnungszustandes an der Oberfläche eines Bauteiles. In numerischen und experimentellen Analysen wurde die Dehnungsübertragung in die übereinanderliegenden Messgitterschichten untersucht. Desweiteren wurde die Wärmeentwicklung der DMS-Rosetten auf verschiedenen Bauteilen untersucht.
4

Ambrosio, Sophie d'. "Les intéractions d'échange dans le semi-conducteur magnétique dilué ZnO.Co." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4304/document.

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Le travail sur le ZnO:Co rapporté dans ce manuscrit, donne une meilleure compréhension des interactions d'échange dans ce composé. La question des interactions spin-spin dans les DMS est abordée à la fois sur le plan théorique et expérimental. Du point de vue théorique, le modèle du superéchange d'Anderson a été utilisé et étendu, afin d'obtenir les valeurs des constantes d'échange sur l'ensemble de la série des DMS II-VI dopés Mn ou Co. Du point de vue expérimental, la combinaison inédite de trois méthodes expérimentales, la diffusion inélastique de neutrons (ou INS), la résonance paramagnétique électronique (ou EPR), et la méthode de mesure des marches d'aimantation sous champ magnétique intense (ou méthode MST), a permis d'établir, pour la première fois, la valeur des dix plus grandes constantes d'échange du ZnO:Co.Les observations faites par INS permettent de mettre en évidence de façon directe une très forte anisotropie spatiale concernant l'intégrale d'échange des premiers voisins. On établit ainsi J(1)=-25,6K et J(2)=-8,5K, correspondant respectivement à la paire des premiers voisins dans le plan (ab), et à la paire des premeirs voisins hors de ce plan. Ce résultat s'explique, en partie, par la présence dans la structure wurtzite d'une contribution ferromagnétique dans le calcul du superéchange, issue d'un chemin formant une boucle et faisant intervenir deux anions distincts.Les mesures effectuées par EPR et par MST permettent d'établir les constantes d'échange entre voisins à plus grande distance. Ainsi, on obtient: J(3)=-1,07K , J(4)=-0,38K , J(5)=0,35K , J(6)=0,17K , J(7)=-0,16K , J(8)=-0,04K , J(9)=-0,03K , |J(10)|=0,013K
The work performed on ZnO:Co enables a better understanding of exchange constants. The question of the spin-spin interactions in the Diluted Magnetic Semiconducteur (DMS) is studied from both theoretical and experimental approaches. On the théoretical side, a exchange constants for all the II-VI series doped Mn et CO. On the experimental side, the use of three techniques, Inelastic Neutron Scattering (INS), Electron Paramagnetic Resonance (EPR), and the Magnetization Steps (MST) method, has made it possible to establish, for the first time, the ten largest exchange constants in ZnO:Co.The INS experiments show, in direct way, astrong spatial anisotropy of the nearest enighbor exchange integral J(1)=-25.6 K and J(2)=-8.5 K. This result can be explained, in part, by the presence, in the wurtzite structure, of a looped exchange path which involves two distinct anions and is ferromagnetic. To justify this explanation, our model was expanded to cover the entire II-VI series doped Mn and Co. The concurrent results, for the complete series, between the known experimental data and the theoretical exchange values permit the justification and the validation of our hypotheses.The measures performed by EPR and MST enable, for their part, the establisment of the distant neighbor exchange constants. the two techniques give complementary information, and make it possible to directly observe the exchange constants of ZnO:Co going from the third to the tenth largest value, J(3)=-1.07 K ,J(4)=-0.38 K , J(5)=+0.35 K , J(6)=+0.17 K , J(7)=-0.13 K , J(8)=-0.04 K , J(9)=-0.03 K , |J(10)|=0.01 K
5

Madsen, Sabine. "Emerging methods : an interpretive study of ISD methods in practice /." København, 2004. http://www.gbv.de/dms/zbw/476259614.pdf.

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Becker, Ralf. "Consumption equivalent public capital method and a three generations model /." Marburg : Metropolis-Verl, 2002. http://www.gbv.de/dms/zbw/35493113X.pdf.

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Wøhlk, Olsen Lina. "Essays on Georg Rasch and his contributions to statistics /." Copenhagen, 2003. http://www.gbv.de/dms/zbw/367192314.pdf.

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8

Johannemann, Ulf. "Entwicklung und Stand der unitary taxation method /." Münster : Lit, 1998. http://www.gbv.de/dms/spk/sbb/recht/toc/278101658.pdf.

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9

Seel, Christian. "Visuelle Simulation von Dienstleistungsprozessen : [Methode und Werkzeugunterstützung] /." Lohmar ; Köln : Eul, 2002. http://www.gbv.de/dms/zbw/353405949.pdf.

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10

Barthel, Tom. "Eine Methode zur Spezifikationserfassung heterogener Systeme /." Düsseldorf : VDI-Verl, 1999. http://www.gbv.de/dms/bs/toc/304348678.pdf.

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Books on the topic "DMSL method":

1

Corradini, Fabio. Development of a HPLC method for analysis of DMSP, glycinebetaine and proline in plants. Dublin: University College Dublin, 1996.

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2

Wolfe, Gordon V. Accumulation of dissolved DMSP by marine bacteria and its degradation via bacterivory. [Washington, DC: National Aeronautics and Space Administration, 1996.

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3

Siksimova, Marina, Ol'ga Begicheva, and Svetlana Mozgot. Solfeggio and music theory: a practical course. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1971854.

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The textbook combines all the main types and forms of practical work in the disciplines of the musical and theoretical cycle, as well as the main topics on musical literacy and music theory, forms of control papers (exam papers), which, as a rule, are presented in such publications separately, without following an integrated approach. The forms of planning and methods of implementation of independent work of students are elaborated and presented in detail. The proposed principle of systematic learning helps in the practical development of disciplines, contributes to the acquisition of the necessary professional knowledge, skills and abilities. It is intended for use in the classroom work of students of performing and theoretical departments of music colleges, as well as advanced students of the senior classes of SSMSH, DMSh and DSHI. It can be used for independent work of students of various specialties of secondary vocational education institutions and areas of higher education: 53.02.03 "Instrumental performance (by types of instruments)", 53.03.03 "Vocal art", 53.03.04 "The Art of folk singing", as well as for preparing applicants for entrance exams.
4

Dittel, K. K. The Double Dynamic Martin Screw (DMS): Adjustable Implant System for Proximal and Distal Femur Fractures. Heidelberg: Steinkopff, 2008.

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Lindenberger, Alexandra. DMSO, MSM, CDL Handbuch: Die 3 Effektivsten Alternativen Heilmittel Um Ihre Gesundheit Langfristig Zu Verbessern und Entzündungen Zu Heilen Inkl. Detaillierte Eigen-Therapie Methode. Independently Published, 2019.

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Book chapters on the topic "DMSL method":

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Mayr, Martin. "Dehnungsmessstreifen-Methode (DMS-Methode)." In Technische Mechanik, 391–97. 9th ed. München: Carl Hanser Verlag GmbH & Co. KG, 2021. http://dx.doi.org/10.3139/9783446469525.054.

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Mayr, Martin. "Dehnungsmessstreifen-Methode (DMS-Methode)." In Technische Mechanik, 391–97. München: Carl Hanser Verlag GmbH & Co. KG, 2015. http://dx.doi.org/10.3139/9783446446182.046.

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Delley, B. "DMol Methodology and Applications." In Density Functional Methods in Chemistry, 101–7. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3136-3_7.

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Agner, T., and J. Serup. "DMSO Irritancy Assessed Using Noninvasive Methods." In Current Topics in Contact Dermatitis, 425–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74299-6_86.

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Sahoo, Ashok Kumar, Seshadev Sahoo, and Virendra Patel. "Simulation of AlSi10Mg Powder for Temperature Profile by DMLS Method." In Lecture Notes in Mechanical Engineering, 681–88. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9057-0_73.

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Gupta, Paromita, and Silvia Rouskin. "In Vivo RNA Structure Probing with DMS-MaPseq." In Methods in Molecular Biology, 299–310. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1851-6_16.

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Swarnakumari, V., and A. L. Theerthan. "Protein Stability Using Thermal Shift Assay (TSA): DMSO Tolerance." In Methods for Fragments Screening Using Surface Plasmon Resonance, 43–50. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1536-8_6.

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Andrade, José M., Ricardo F. dos Santos, and Cecília M. Arraiano. "RNA Structure Analysis by Chemical Probing with DMS and CMCT." In Methods in Molecular Biology, 209–23. New York, NY: Springer US, 2019. http://dx.doi.org/10.1007/978-1-0716-0231-7_13.

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Vera, Nicholas B., Michelle Clasquin, Stephen L. Coy, and Paul Vouros. "The Use of DMS-MS for the Quantitative Analysis of Acylcarnitines." In Methods in Molecular Biology, 95–101. New York, NY: Springer US, 2019. http://dx.doi.org/10.1007/978-1-0716-0030-6_5.

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Liu, Yitong. "Study Liver Cytochrome P450 3A4 Inhibition and Hepatotoxicity Using DMSO-Differentiated HuH-7 Cells." In Methods in Molecular Biology, 63–70. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6346-1_7.

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Conference papers on the topic "DMSL method":

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Nomaguchi, Yutaka, Anders Askhøj, Kristian F. Madsen, Ryota Akai, and Kikuo Fujita. "Design Method Selection Matrix for Facilitating Product Platform and Family Design." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70861.

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The aim of this research is to develop a method to manage product platform and family design methods and to select one appropriate for a specific design case. As the need for product platform has increased over the last 20 years, research within the area has led to the development of various methods that aim at evaluating a candidate of design. While sharing similar approach, different researchers have developed different methods that vary greatly in type, focus and complexity. Although their differences are considered a strong point of the theoretical field, the large variety can end up complicating the selection process, which will result in choosing less optimal methods for a specific design case. This paper proposes Design Method Selection Matrix (DMSM) that can help designers choose appropriate design methods. The underlying basis for the proposed DMSM is to determine methods appropriateness based on the availability of information, which is defined by the situation in which the evaluation takes place, as well as the importance of information, which is determined by the goal of the evaluation. The output of DMSM is a score for each of the identified methods that represent the appropriateness of the given method, based on the situation and goal(s) chosen by the designer. Suggestions are based on parameters that can easily be determined by designers without extensive experience within platform based product design. The case study demonstrates the effectiveness of DMSM.
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Xu, Cai, Ziyu Guan, Wei Zhao, Yunfei Niu, Quan Wang, and Zhiheng Wang. "Deep Multi-View Concept Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/402.

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Multi-view data is common in real-world datasets, where different views describe distinct perspectives. To better summarize the consistent and complementary information in multi-view data, researchers have proposed various multi-view representation learning algorithms, typically based on factorization models. However, most previous methods were focused on shallow factorization models which cannot capture the complex hierarchical information. Although a deep multi-view factorization model has been proposed recently, it fails to explicitly discern consistent and complementary information in multi-view data and does not consider conceptual labels. In this work we present a semi-supervised deep multi-view factorization method, named Deep Multi-view Concept Learning (DMCL). DMCL performs nonnegative factorization of the data hierarchically, and tries to capture semantic structures and explicitly model consistent and complementary information in multi-view data at the highest abstraction level. We develop a block coordinate descent algorithm for DMCL. Experiments conducted on image and document datasets show that DMCL performs well and outperforms baseline methods.
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Zhijian, Lyu, Jiang Shaohua, Liang Yigao, and Gao Min. "GDGRU-DTA: Predicting Drug-Target Binding Affinity based on GNN and Double GRU." In 3rd International Conference on Data Mining and Machine Learning (DMML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120703.

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The work for predicting drug and target affinity(DTA) is crucial for drug development and repurposing. In this work, we propose a novel method called GDGRU-DTA to predict the binding affinity between drugs and targets, which is based on GraphDTA, but we consider that protein sequences are long sequences, so simple CNN cannot capture the context dependencies in protein sequences well. Therefore, we improve it by interpreting the protein sequences as time series and extracting their features using Gate Recurrent Unit(GRU) and Bidirectional Gate Recurrent Unit(BiGRU). For the drug, our processing method is similar to that of GraphDTA, but uses two different graph convolution methods. Subsequently, the representation of drugs and proteins are concatenated for final prediction. We evaluate the proposed model on two benchmark datasets. Our model outperforms some state-of-the-art deep learning methods, and the results demonstrate the feasibility and excellent feature capture ability of our model.
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Huai, Mengdi, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, and Aidong Zhang. "Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/352.

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As an effective way to learn a distance metric between pairs of samples, deep metric learning (DML) has drawn significant attention in recent years. The key idea of DML is to learn a set of hierarchical nonlinear mappings using deep neural networks, and then project the data samples into a new feature space for comparing or matching. Although DML has achieved practical success in many applications, there is no existing work that theoretically analyzes the generalization error bound for DML, which can measure how good a learned DML model is able to perform on unseen data. In this paper, we try to fill up this research gap and derive the generalization error bound for DML. Additionally, based on the derived generalization bound, we propose a novel DML method (called ADroDML), which can adaptively learn the retention rates for the DML models with dropout in a theoretically justified way. Compared with existing DML works that require predefined retention rates, ADroDML can learn the retention rates in an optimal way and achieve better performance. We also conduct experiments on real-world datasets to verify the findings derived from the generalization error bound and demonstrate the effectiveness of the proposed adaptive DML method.
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Reddy, P. Deepak, Chirag Rudresh, and Adithya A S. "Multilingual Speech Recognition Methods using Deep Learning and Cosine Similarity." In 3rd International Conference on Data Mining and Machine Learning (DMML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120702.

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The paper includes research on discovering new methods for multilingual speech recognition and comparing the effectiveness of the existing solutions with the proposed novelty approaches. The audio and textual multilingual dataset contains multilingual sentences where each sentence contains words from two different languages - English and Kannada. Our proposed speech recognition process includes preprocessing and splitting each audio sentence based on words, which is then given as input to the DL translator (using MFCC features) along with next word predictions. The use of a Next Word Prediction model along with the DL translator to accurately identify the words and convert to text. Similarly the other approach proposed is the use of cosine similarity where the speech recognition is based on the similarity between word uttered and the generated training dataset. Our models were trained on an audio and textual dataset that were generated by the team members and the test accuracies were measured based on the same dataset. The accuracy of our speech recognition model, using the novelty method, is 71%. This is a considerably good result compared to the existing multilingual translation solutions. Communication gap has been a major issue for many natives and locals trying to learn or move ahead in this tech-savvy English-speaking world. To communicate effectively, it is not only essential to have a single language translator but also a tool that can help understand a mixture of different languages to bridge the gap of communication with the non-English speaking communities. Integrating a multilingual translator with the power of a smart phone voice assistant can help aid this process.
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Jahan, Suchana, and Hazim El-Mounayri. "Game Theoretic Modelling Approach for Optimizing Direct Metal Laser Sintering Process Parameters Using Artificial Neural Network." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23504.

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Abstract Additive Manufacturing, also known as Rapid Prototyping and 3D Printing is a three-dimensional fabrication process, executed by adding materials in layers. Among many different classes of AM processes, Direct Metal Laser Sintering is a widely used metal part manufacturing method. The design, planning and implementation of overall DMLS process and its process parameters are yet to be optimized. To be able to render minimum defects as well as higher quantity of production, it is essential to apply ever developing computer technologies, data storage capabilities and optimization techniques. Typically, the defects on any 3D printed part can alter mechanical properties and shorten its durability. To minimize the defects and produce good quality parts at a mass level, has been a challenge in additive manufacturing industry. In this paper, a framework is presented to utilize game theoretic modelling approach to optimize DMLS process parameters. Online monitoring of DMLS process can identify defects of printed layers and correlate them with temperature signatures. An Artificial Neural Network is trained to predict printing defects and process parameters. predicted model can be further used in a game theoretic playoff matrix to identify the most optimal combination or configuration of DMLS process parameters to minimize defects and maximize the production quantity. The proposed method can also be applied in different domains of additive and advanced manufacturing.
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Yuan, Tao, Xinqi Zheng, and Wei Zhou. "Calculation methods of territorial development intensity using DMSP/OLS data." In 2011 19th International Conference on Geoinformatics. IEEE, 2011. http://dx.doi.org/10.1109/geoinformatics.2011.5980751.

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Zeng, Jie, Guoxian Yu, Jun Wang, Maozu Guo, and Xiangliang Zhang. "DMIL-III: Isoform-isoform interaction prediction using deep multi-instance learning method." In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019. http://dx.doi.org/10.1109/bibm47256.2019.8982956.

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Pavel, Radu, and Anil K. Srivastava. "Investigations for Safe Grinding of Ti-6Al-4V Parts Produced by Direct Metal Laser Sintering (DMLS) Technology." In ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/msec2014-4130.

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Direct Metal Laser Sintering (DMLS) is an additive manufacturing technology that can construct medium to small size parts very efficiently in comparison to traditional machining processes. The ability of this technology to grow complex parts made of high strength titanium- and nickel-based alloys led to increasing interest from aerospace, defense, and medical industries. Although the technology allows growing parts close to their final shape, the active surfaces still need a finishing operation such as grinding to meet the tight tolerances and surface finish requirements. Due to the novelty of the DMLS technology, and the relatively recent developments of titanium alloy powders, there is a need for testing and validating the capabilities of the components manufactured through a combination of DMLS and grinding processes. This paper presents the findings of an experimental study focused on the effect of various grinding conditions on the surface integrity of titanium alloy (Ti-6Al-4V) specimens produced using DMLS technology. The goal is to identify dressing and grinding conditions that would result in ground surfaces free of defects such as micro-cracks, discoloration of surfaces and/or burn marks due to high heat generated during grinding. The residual stresses were used to quantify the effect of the grinding conditions on the ground surfaces. These investigations were conducted on an instrumented CNC surface grinding machine, using a silicon-carbide grinding wheel and a water-based fluid. The X-ray diffraction method was used to measure the residual stresses. Two batches of specimens were manufactured for these tests. The growing strategy of the specimens and the presence of apparent defects in material structure are considered some of the main causes for the differences observed in the outcomes of the grinding trials. The results of these investigations support the need for continuing research in the additive manufacturing field to develop methods and technologies that will ensure a high level of consistency of the grown parts.
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Li, Haoyu, Ryan Yan, and Ang Li. "An Intelligent Social-based Assistant Application for Study Time Management using Artificial Intelligence and Natural Language Processing." In 3rd International Conference on Data Mining and Machine Learning (DMML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120714.

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The question that we aim to solve is “How will elderly people be able to increase their productivity and remember their tasks?” There are many ways to go about answering this question, but we have devised a simple solution to this question that can directly and quickly have a positive impact on these individuals. Our method to solving this is creating a to-do list in Flutter, which will allow elderly people to have easy access to a list of tasks that they have to complete [5]. Some predicted results of this to-do list is that it can raise productivity for its users. Our to-do list features a ChatBot, which talks to the user through a message-like system in order to prompt user input for specific details such as the time, date, and main description of the task [6]. Then, the ChatBot will take in all this information to produce a clean and concise final task description that takes keywords from the user-inputted description. This provides users of our to-do list with an alternative method of adding tasks, which may be greatly appreciated by those who are less able-bodied or struggle to type. By offering the elderly a way of adding tasks that can take less typing, these individuals may rely on this to-do list as a great convenience to their lives.

Reports on the topic "DMSL method":

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Dang, Nhan, Jennifer Gottfried, and Frank De Lucia. The Electronic Excitation of 2,4,6-triamino-1,3,5-trinitrobenzene in DMSO Solution under Indirect Ultrafast Heating: A Comparison to Results Obtained by Optical Pumped Method. DEVCOM Army Research Laboratory, August 2023. http://dx.doi.org/10.21236/ad1210128.

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