Search Results (7)

In the realm of precision space applications, improving the accuracy of orbit determination (OD) is a crucial and demanding task, primarily because of the presence of measurement noise. To address this issue, a novel machine learning method based on bidirectional long short-term memory (BiLSTM) is proposed in this research. In particular, the proposed method aims to improve the OD accuracy of Earth–Moon Libration orbits with angle-only measurements. The proposed BiLSTM network is designed to detect inaccurate measurements during an OD process, which is achieved by incorporating the least square method (LSM) as a basic estimation approach. The structure, inputs, and outputs of the modified BiLSTM network are meticulously crafted for the detection of inaccurate measurements. Following the detection of inaccurate measurements, a compensating strategy is devised to modify these detection results and thereby reduce their negative impact on OD accuracy. The modified measurements are then used to obtain a more accurate OD solution. The proposed method is applied to solve the OD problem of a 4:1 synodic resonant near-rectilinear halo orbit around the Earth–Moon L2 point. The training results reveal that the bidirectional network structure outperforms the regular unidirectional structures in terms of detection accuracy. Numerical simulations show that the proposed method can reduce the estimated error by approximately 10%. The proposed method holds significant potential for future missions in cislunar space. Full article

Recently, the widespread use of social media and easy access to the Internet have brought about a significant transformation in the type of textual data available on the Web. This change is particularly evident in Arabic language usage, as the growing number of users from diverse domains has led to a considerable influx of Arabic text in various dialects, each characterized by differences in morphology, syntax, vocabulary, and pronunciation. Consequently, researchers in language recognition and natural language processing have become increasingly interested in identifying Arabic dialects. Numerous methods have been proposed to recognize this informal data, owing to its crucial implications for several applications, such as sentiment analysis, topic modeling, text summarization, and machine translation. However, Arabic dialect identification is a significant challenge due to the vast diversity of the Arabic language in its dialects. This study introduces a novel hybrid machine and deep learning model, incorporating an attention mechanism for detecting and classifying Arabic dialects. Several experiments were conducted using a novel dataset that collected information from user-generated comments from Twitter of Arabic dialects, namely, Egyptian, Gulf, Jordanian, and Yemeni, to evaluate the effectiveness of the proposed model. The dataset comprises 34,905 rows extracted from Twitter, representing an unbalanced data distribution. The data annotation was performed by native speakers proficient in each dialect. The results demonstrate that the proposed model outperforms the performance of long short-term memory, bidirectional long short-term memory, and logistic regression models in dialect classification using different word representations as follows: term frequency-inverse document frequency, Word2Vec, and global vector for word representation. Full article

The efficiency of solid oxide fuel cell cathodes can be improved by microstructural optimization and using active layers, such as doped bismuth oxides. In this work, Bi_1.5Y_0.5O₃ (BYO) films are prepared by spray-pyrolysis deposition at reduced temperatures on a Zr_0.84Y_0.16O_1.92 (YSZ) electrolyte. The influence of the BYO film on the performance of an La_0.8Sr_0.2MnO₃ (LSM) cathode prepared by traditional screen-printing and spray-pyrolysis is investigated. A complete structural, morphological, and electrochemical characterization is carried out by X-ray diffraction, electron microscopy, and impedance spectroscopy. The incorporation of BYO films decreases the Area Specific Resistance (ASR) of screen-printed cathodes from 6.4 to 2.2 Ω cm² at 650 °C. However, further improvements are observed for the nanostructured electrodes prepared by spray-pyrolysis with ASRs of 0.55 and 1.15 Ω cm² at 650 °C for cathodes with and without an active layer, respectively. These results demonstrate that microstructural control using optimized fabrication methods is desirable to obtain high-efficiency electrodes for solid oxide fuel cell (SOFC) applications. Full article

The photocatalyst bismuth oxide, which is active under visual light, was deposited using an atmospheric pressure plasma jet (APPJ). Sixteen different samples were generated under different parameters of the APPJ to investigate their catalytic activity. The prepared samples were characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), laser scanning microscopy (LSM), and UV–vis diffuse reflectance absorption spectroscopy. The measured data, such as average sample thickness, coverage ratio, phase fraction, chemical composition, band gap, and photocatalytic performance were used for comparing the samples. The XRD analysis showed that the deposition process produced a mixed phase of monocline Bi₂O₃ and tetragonal Bi₂O_2.33. Using the Rietveld refinement method, phase fractions could be determined and compared with the XPS data. The non-stoichiometric phases were influenced by the introduction of nitrogen to the surface as a result of the deposition process. The band gap calculated from the diffuse absorption spectroscopy shows that Bi₂O_2.33 with 2.78 eV had a higher band gap compared to the phases with a high proportion of Bi₂O₃ (2.64 eV). Furthermore, it was shown that the band gap was dependent on the thickness of the sample and oxygen vacancies or loss of oxygen in the surface. All coatings had degraded methyl orange (MO) under irradiation by xenon lamps. Full article

The switching device is relatively weakest in the traction converter, and this paper aims at the fault prediction of it. Firstly, the mathematical distribution is analyzed based on the results that were obtained in electro thermal simulation and a single-directional accelerated fatigue test. Then, the accelerated fatigue test with bi-directional fatigue current is proposed, the data from which reflects the accelerating effect from FWD on the device aging process. The analytical model of fatigue process is fitted with the data that were obtained in the test. In order to shorten the test time consumption, we propose a weighted least squares method (LSM) to fit the failure data. Finally, the prediction model is presented with the consideration of fatigue signature and Arrhenius temperature factor. Full article

In this study, bismuth oxide powder (Bi₂O₃) was deposited by an atmospheric pressure plasma jet onto borosilicate glass. The layer produced through this method is to be used as a photo catalyst in later applications. The deposited coating was analyzed by X-ray diffraction (XRD) to determine the crystal structure, and X-ray photoelectron spectroscopy (XPS) to analyze the chemical state. The results showed a change in crystal and chemical structure during the deposition process. The morphological properties of the layer were examined with scanning electron microscopy (SEM) and laser scanning microscopy (LSM). The band gap structure of the coating was investigated by UV-Vis spectroscopy. The layer produced by the plasma spraying process consisted of circular multi-phase bismuth oxide droplets (monoclinic Bi₂O₃ and tetragonal Bi₂O_2.33), showing a direct band gap of E_g = 2.72 eV, which allows their use as a photocatalyst. Full article

Displacement and deformation are fundamental measures of Earth surface mass movements such as glacier flow, rockglacier creep and rockslides. Ground-based methods of monitoring such mass movements can be costly, time consuming and limited in spatial and temporal coverage. Remote sensing techniques, here matching of repeat optical images, are increasingly used to obtain displacement and deformation fields. Strain rates are usually computed in a post-processing step based on the gradients of the measured velocity field. This study explores the potential of automatically and directly computing velocity, rotation and strain rates on Earth surface mass movements simultaneously from the matching positions and the parameters of the geometric transformation models using the least squares matching (LSM) approach. The procedures are exemplified using bi-temporal high resolution satellite and aerial images of glacier flow, rockglacier creep and land sliding. The results show that LSM matches the images and computes longitudinal strain rates, transverse strain rates and shear strain rates reliably with mean absolute deviations in the order of 10⁻⁴ (one level of significance below the measured values) as evaluated on stable grounds. The LSM also improves the accuracy of displacement estimation of the pixel-precision normalized cross-correlation by over 90% under ideal (simulated) circumstances and by about 25% for real multi-temporal images of mass movements. Full article