Increase In Processing Time Research Articles

Advances in Seismo-LAI anomalies detection within Google Earth Engine (GEE) cloud platform

Nowadays, satellite data is an appropriate and undeniable source for studying earthquake precursors due to their diversity, wide coverage, being up to date and low cost. Time series analysis of satellite data plays an important role in the process of detecting seismic anomalies in earthquake warning systems. But in order to reduce uncertainty during the seismic anomalies detection, it is necessary the use a variety of satellite data, although it leads to increase of data size and processing time. This paper aims to explain the role of Google Earth Engine (GEE) cloud platform in considerable progress of seismo-Lithospheric Atmospheric Ionospheric (LAI) anomalies detection in earthquake early warning systems. Among the different studied earthquakes, for example two recent powerful earthquakes in Japan (13 February and 20 March 2021) have been discussed. Deduced time series of three precursors (i.e. Aerosol Optical Thickness (AOT), Chlorophyll and Ozone) from GEE platform were investigated using Median method and a Long Short-Term Memory(LSTM) neural network to detect potentially seismo-LAI anomalies. Our satisfactory results show that with the addition of other various satellite data and also known predictors intelligent algorithms such as deep learning to GEE platform, we will see a significant leap forward in studies of earthquake precursors.

Analysis of turbulence and scattering effects on detecting elevated sources with a microphone array

Sound waves propagating in urban environments are affected by turbulence, scattering from numerous structures, and atmospheric refraction. These effects can be incorporated into beamforming algorithms but at the cost of increased processing time and algorithm complexity. An analysis of incorporating refraction effects into the beamformers for a simplified scenario is performed on detection algorithms based on four generalized beamforming algorithms. Simulated results for beamforming algorithms implemented with no model mismatch error are compared to results for classical beamforming algorithms implemented with model mismatch errors generated by atmospheric refraction. Their relative performance is evaluated using the area under the receiver operating characteristic curve statistic calculated with Monte Carlo simulations. The results processed with data that include effects from turbulence and rough surface scattering show that there is no significant improvement in detection performance obtained by including refraction effects into the beamforming algorithms over a wide range of frequencies. The results indicate that complex beamforming algorithms are not required for many urban acoustic applications.

IoT based cyber forensics in big data optimization and privacy using deep neural anomaly detection with Hadoop clustering and convolution based Adam optimizer

AbstractThe reliability of the digital forensic system mainly lies in its ability to detect the attack on time and minimize the security risk associated with the Internet of Things (IoT) device. The existing machine learning architectures mainly suffered from different complexities while processing the attack features such as increased processing time, high manual intervention, complexity to handle large datasets, and low prediction accuracy. To overcome these issues, this article proposes a novel deep learning architecture for data forensics. The low generalization capability of the neural network is handled via the Hadoop clustering and convolution‐based ADAM (CADAM) optimizer approach for improving the optimization capability of the model. In this way, the privacy of the model is improved. The efficiency of the proposed CADAM optimized deep neural network architecture is evaluated by using the UNSW‐NB15 and Bot‐IoT datasets. The proposed model offers improved performance in terms of runtime, precision, sensitivity, specificity, latency, cost, ROCAUC curve, and anomalous traffic when compared with the existing techniques. From the experiments carried out, we can conclude that the proposed framework revealed higher performance to discover and prevent cyber‐attacks against other conventional approaches.

Anthocyanin Extraction from Jaboticaba Skin (Myrciaria cauliflora Berg.) Using Conventional and Non-Conventional Methods.

This study evaluated the effect of different extraction technologies and conditions in order to obtain jaboticaba skin extracts. Firstly, the skins were extracted by conventional extraction, according to a rotatable central composite design, varying ethanol concentration, solid:liquid ratio, and temperature. Next, ultrasound-assisted extraction was performed using different power densities and times. Finally, high-pressure extractions were performed with varying pressures and times. For agitated bed extraction, the highest anthocyanin content was observed for ethanol concentrations varying between 60% and 80%. Thus, the independent variables which more influenced anthocyanin content were ethanol concentration and solid:liquid ratio. Folin–Ciocalteu reducing capacity was linearly affected by the increase in temperature. Ethanol concentration was the variable that most influenced ABTS+. On the other hand, the increase in ethanol concentration decreased the antioxidant capacity by ABTS+. Considering the ultrasound extraction, increasing its power did not affect total monomeric anthocyanins content, while the increase in process time had better yields. The highest antioxidant capacity and total monomeric anthocyanins were found for the highest extraction time. Similarly, with ultrasound, the increase in high hydrostatic-assisted extraction time positively influenced anthocyanin content and antioxidant capacity. As a result, the ultrasound-assisted method was found to be the best extraction technology for anthocyanins recovery.

Effects of the combination of compression and impregnation with phenolic resin on the dimensional stability in the multiscale wood structure of Chinese fir

Chinese fir wood was pretreated by phenol–formaldehyde (PF) resin and followed by the compression along the radial direction at the compression ratio of 10%, 20% and 30%, respectively. The microscopic images of the control and modified wood at different humidity were then collected to evaluate the dimensional stability of wood cellular structures. The interactions between the cell wall and resin were also observed by SEM and Raman spectroscopy to reveal the fixation effects of resin on the compressed wood at cell-level. Results indicated that the number of wood cells filled with PF resin increased significantly with the increase of impregnation pressure and processing time, which contributed to an obvious decrease in the linear and volumetric expansion ratio of wood at high humidity, in particular at the RH of 90%. The filling of PF resin in the wood cell lumen and the open pits on the tracheid walls not only inhibited the entry of water molecules but also had a chemical interaction with cell-wall, which could significantly reduce the set-recovery of the compressed wood. The radial expansion ratio of wood at a compression ratio of 30% has been reduced by about 65% at the RH of 90% after PF resin impregnation.

Analysis of Plastic Improvement and Interference Behavior in Current-Assisted Riveting of CFRP Laminates.

In order to improve the joint performance of a titanium alloy rivet connecting aircraft CFRP structure and promote the wide application of ordinary titanium alloy rivets in the aviation field, the ductility of a Ti45Nb rivet was improved using a current-assisted method in this paper. Through experiments, the mechanical behavior and temperature during the riveting process were monitored, and the variation rules of interference and damage were studied in detail. The results show that a current within 16.5 A/mm2 can effectively reduce the riveting pressure requirement, and the maximum engineering stress is reduced by nearly 22%. As the current density increases, the softening effect is obvious, but as the processing time increases, the softening effect has an upper threshold. The current-assisted method can significantly increase the interference fit level, and the uniformity of riveting can be improved by nearly 30%. The outlet burr height of a joint obtained by new technology meets the relevant standards. When the current density is too large or the action time is long, the damage pattern and mechanism at different depths of hole have obvious regional differences.

Effect of Ammonia Addition on the Growth of an AlO(OH) Film during Steam Coating Process

Al alloys possess excellent physical and mechanical properties, such as low density, high specific strength, and good ductility. However, their low corrosion resistance limits their use in corrosive environments. The steam coating process has attracted considerable attention as a new coating technology that can improve the corrosion resistance of Al alloys. This surface treatment technology uses steam to form a corrosion-resistant film on Al alloys. However, a decrease in the processing time, which can result in a lower cost, is needed for the practical application of the steam coating process. In this study, an Al-Mg-Si alloy is used as the base material, and ammonia is added to the steam source to increase the film formation rate. By adding ammonia (0.5 mol/L) to the steam source, the rate constant, K, for film formation increases 1.82 times compared to that of the pure-water-only treatment. Field emission scanning electron micrographs of the film surface confirms that the crystal morphologies of the crystals change from rectangular to parallelepiped shape with increasing process time by ammonia addition. Furthermore, X-ray diffraction patterns show that AlO(OH) crystals are successfully synthesized without byproducts, even when ammonia is added.

Physicochemical characteristics of sweet corn kernels during microwave blanching

Sweet corn kernels are easily perishable because of their high amount of moisture content. Microwave blanching was applied at the power level of 180–900 W for 30–70 s to inactivate the enzymes of sweet corn kernels. The increase in microwave power level and processing time reduced the length from 11.13 to 10.78 mm, width from 9.54 to 9.24 mm, thickness from 4.01 to 3.71 mm, true density from 1052.07 to 1012.03 kg/m3, porosity from 37.43 to 24.54%, moisture content from 70.00% to 68.93% on a wet basis, total soluble solid from 22.3 to 18.7 °Brix, total sugar from 8.80% to 6.67%, ascorbic acid from 8.04 to 5.92 mg/100 g, and peroxidase activity up to 1.37% in sweet corn kernels, but it increased the bulk density from 658.23 to 763.6 kg/m3 and total color difference up to 14.55. Novelty impact statement The microwave blanching was found adequate for processing sweet corn kernels at the power level of 720 W for a short duration of 40 s to achieve a 90% reduction in peroxidase activity. The ascorbic acid, total sugar, overall acceptability after the microwave blanching were 6.86 mg/100 g, 7.87%, and 8.21, respectively, indicating 85, 89, and 94% retention of fresh samples properties. The total plate count was 9.1 log cfu/g in fresh kernels, which was also reduced to 1.8 log cfu/g in kernels blanched at the power level of 720 W for 40 s duration.

PEO processing of AZ91Nd/Al2O3 MMC-the role of alumina fibers

• Al 2 O 3 fibers interrupted the continuity of PEO coating at the interface of coating/substrate. • Al 2 O 3 fibers reactively incorporated in PEO coating through thermal drive reactions. • A MgAl 2 O 4 containing layer was formed in plasma electrolytic oxidation coating near the surface. This work reports the influence of alumina fiber reinforcement of an AZ91Nd MMC (metal matrix composite) on the PEO coating formation process in a sodium phosphate-based electrolyte. By comparison with the pure AZ91Nd, the evolution of alumina fiber during the processing and the characteristics of the resultant PEO coating were investigated. The voltage response as a function of processing time was changed. Lower voltage in the presence of alumina fiber is responsible for the lower coating thickness. The morphology and phase composition of the coatings are also influenced by the incorporation of the fiber. Firstly, the fiber is embedded in the coating and interrupts the continuity of the coating. With increasing processing time, the fiber is found to be reactively incorporated in the coating. The intention to produce a MgAl 2 O 4 containing coating is achieved and it is mainly accumulated near the coating surface. However, due to the low number of fibers, the Al content is overall still low and only near to the fibers the MgAl 2 O 4 spinel phase can form.

BASF to invest EUR 4.5 bn in EV battery recycling

In this work, we studied the structural, morphological and chemical transformations in α- chitin, caused by its mechanical activation in the form of an aqueous suspension in the rotor-stator device for 5–30 s. Mechanically activated chitin (MA-chitin) was characterized using optical and electron scanning microscopy, N2 adsorption/desorption isotherms, X-ray diffraction and FTIR-spectroscopy. It was established that the specific surface area, porosity and the deacetylation degree of chitin increase with increasing processing time, and the decrease in crystallinity and reducing the packing density of macromolecular chains does not correlate with this indicator due to the development of recrystallization. The efficiency of chitin activation was evaluated by studying its ability to adsorb anionic and cationic dyes. It was found that the limiting adsorption capacity of MA-chitin was on average 2–4 times higher, and the time to reach equilibrium was, on average, 3–4 times less compared to raw chitin.

An Approach for Optimization of Features using Gorilla Troop Optimizer for Classification of Melanoma

The diagnosis and categorization of skin cancer, as well as the difference in skin textures and injuries, is a tough undertaking. Manually detecting skin lesions from dermoscopy images seems to be a difficult and cumbersome challenge. Recent advancements in the internet of things (IoT) and artificial intelligence for clinical applications have shown significant increase in precision and processing time. A lot of attention is given to deep learning models because they are effective at identifying cancer cells. The diagnosis and accuracy levels can be greatly increased by categorizing benign and malignant dermoscopy images. This work suggests an automated classification system based on a deep convolutional neural network (DCNN) in order to precisely perform multi-classification. The DCNN's structure was thoughtfully created by arranging a number of layers that are in charge of uniquely extracting different features from skin lesions. In this paper, we proposed a deep learning approach to tackle the three main tasks-deep extraction of features (task1) using transfer learning, selection of features (task2)-using metaheuristic algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Gorilla Troop Optimization (GTO) as a feature selector, the extensive feature set is optimized, and the amount of features is reduced to within the range, and a two-level classification (task3) was proposed that are emerging in the field of skin lesion image processing. On the HAM10000 dataset, the proposed deep learning frameworks were assessed. The accuracy achieved on the dataset is 93.58 percent. The proposed method outperforms state-of-the-art (SOTA) techniques in terms of accuracy. The suggested technique is however highly scalable.

Hierarchical Semantic Broadcasting Network for Real-Time Semantic Segmentation

Semantic segmentation has been one of the essential tasks in computer vision. More complicated and computationally intensive mechanisms are integrated into segmentation models to get more accurate results, leading to increased processing time and resource usage. Based on the idea that pixels with similar high-level features are more likely to have similar semantic labels, we propose a computationally efficient mechanism named Hierarchical Semantic Broadcasting (HSB), which can infer earlier-stage semantic label maps from lower-level feature maps by referring to semantic label maps of higher-level feature maps. Since lower-level feature maps have higher resolution and richer context, HSB can provide additional details for better semantic segmentation. By integrating HSB into a general-purpose light network, we propose Hierarchical Semantic Broadcasting Network (HSB-Net) for real-time semantic segmentation, which achieves a good trade-off between accuracy and speed. Evaluated by the Cityscapes dataset, HSB-Net can run at 123.7 FPS for a 512 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ \boldsymbol{\times }$</tex-math></inline-formula> 1024 input on a single GeForce RTX 2080 Ti card while achieving 73.1% mean IoU.

Fuzzy Isolation Forest for Anomaly Detection

Anomaly detection is nowadays a key data mining task. Anomaly detection methods generally look for patterns of ”normal” profile and then identify data points that do not match that profile. One outstanding method, Isolation Forest, showed high detection performance and computational efficiency. This method does not profile normal instances. Instead, it seeks to separate ”abnormal” data points that are ”few and different”, from the others. This method builds a forest of trees to define a model for classifying data points as normal or abnormal. Building trees involve recursive random partitioning of data. Instances resulting in shorter path lengths are considered anomalies because they are located in sparse regions whereas instances ending deeper in tree path are normal points. Most outlier detection approaches, including Isolation Forest, have been used on precise, crisp data. However, in real life, data may be imprecise, incomplete, ambiguous, or uncertain. In this paper, we propose a new approach, called Fuzzy Isolation Forest, which adapts the Isolation Forest method to fuzzy data to handle the ”vagueness” of data. We use a fuzzy partitioning strategy based on the alpha-cut approach in which data instances will be assigned to tree nodes by comparing their membership value to an alpha-cut threshold. Fuzzy Isolation Forest is as efficient as Isolation Forest in detecting anomalies on fuzzy data without significantly increasing processing time.

Design and Simulation Study of the Induction Heated Injection Mold with Sliders.

In order to increase the quality of the products manufactured by injection molding, RTC technology can be used to achieve higher mold temperatures. As a result, the path of the injected melt can be extended, allowing the production of parts with more complex shapes and greater length. Induction heating allows heating only selected forming surfaces of the mold which increases the speed and efficiency of the process. This paper presents the concept of a detachable inductor integrated with sliders to enable the application of this technology in an injection mold with sliders, along with the theoretical model used to perform the tests. First, the effect of the magnetic concentrator shape on the process was analyzed. This was followed by a simulation study of the influence of process parameters: heating time, frequency, and electric current. An extensive analysis of the test results of the temperature distribution on the insert allowed for the selection of parameter sets that would enable obtaining the desired surface temperature without a major increase in process time. The results of simulation studies confirm the possible applications and present the range of parameters for obtaining the optimal process.

Nanostructured PEO-coatings on silumin as environmental catalysts

The process of the formation of mixed oxide coatings on a high-silicon aluminum alloy in the cobalt-containing pyrophosphate electrolyte by the plasma-electrolytic oxidizing (PEO) method has been studied. It has been shown that AK12M2MgN chemical composition heterogeneity causes the consumption of part of the anode current to homogenize the treated surface, which is reflected in minimizing the content of doping components at the initial processing stage. It has been established that the growth of mixed oxides Al2O3·CoOx relative mass is a function of time with the maximum at 55 min. The chemical, phase composition and surface morphology of the formed oxide layer depend on the oxidizing time. The catalytic component content in the surface oxides varies from 0.2 to 23.3 at.% with an increase in processing time from 10 to 60 min. Maximum cobalt incorporation into the oxide layer occurs at PEO of 35–50 min, while the silicon content in the surface layers does not exceed 2 at.%, which is favorable for the catalytic properties. The cobalt oxide, preliminary Co3O4, incorporation in alumina α-Al2O3 matrix is visualized by the blue-violet color spheroid surface structures at the sites of micro-arc discharges. The mixed alumina and cobalt oxides layer are characterized by a developed micro globular surface consisting of conglomerate spheroids with an average size of 1–2 µm. There are some amorphous phases in the structure of mixed oxides due to non-equilibrium PEO conditions. The set of detected factors is a prerequisite for the high catalytic properties of oxide coatings. A promising field of Al2O3·CoOx systems application is an intra-cylinder catalysis in the internal combustion engines.

Natural Disasters and the Effect of Celerity on Criminal Case Outcomes: A Natural Experiment in Kings County

Using case-level data, this study tests whether an increase in average crime-to-disposition time for felony arrests affects case outcomes. These outcomes are the likelihood of no-conviction, the likelihood of downgrading during the case disposition process (regardless of whether the case resulted in a conviction or no conviction), and the likelihood of an incarceration sentence. On October 29, 2012, Hurricane Sandy produced extreme weather conditions in the greater New York City area, including Kings County. For felonies committed during the two-week period (October 28, 2012–November 10, 2012), Kings County experienced, on average, a 20.2% increase (34.3 days) in crime-to-disposition time. This increase provides an instrumental variable (IV) to test the effect of crime-to-disposition time on criminal case outcomes. Neither the hurricane aftermath nor a crime-to-disposition delay had any significant effect on the likelihood of incarceration, the likelihood of no-conviction, or the likelihood of downgrading. As a theoretical matter, the IV estimates suggest that reduced celerity (operationalized by a 20% increase in case processing time) does not affect the severity of punishment (operationalized by incarceration), the certainty of punishment (operationalized by the likelihood of no-conviction), or case processing complexity (operationalized by the likelihood of downgrading).

Processing sheep milk by cold plasma technology: Impacts on the microbial inactivation, physicochemical characteristics, and protein structure

This study aimed to evaluate the impacts of cold plasma processing time of 30 s, 180 s, and 300 s (CSM30, CSM180, and CSM300) on the microbial inactivation, physicochemical characteristics, and protein structure of raw sheep milk. Pasteurized sheep milk was used as the positive control. The microbial inactivation rate of CSM300 sample was similar to the pasteurized sample, and the former had a significantly smaller casein micelle size and polydispersity index (P < 0.05). The pH, and a* value decreased from 6.79 to 6.65, and −1.74 to −1.98, respectively (P < 0.05) with increasing processing time. Also, the moisture content of the freeze-dried milk decreased from 43.4 g/kg to 28.9 g/kg. The Fourier-transform infrared spectra indicated that the CSM180 and CSM300 samples had higher proportions of β-turn structures and a diminished-random coil conformation, the latter could induce an appropriate conformational transformation from α-helix to β-sheet. Scanning electron microscopy images confirmed that the CSM300 sample promoted a more uniform microstructure and a better dispersion state of proteins. These results might provide practical information regarding cold plasma–treated sheep milk, which can be considered as a potential alternative to conventional pasteurization.

Growth characteristics and properties of micro-arc oxidation coatings on AlSi10Mg selective laser-melted components

Micro-arc oxidation (MAO) ceramic coatings were prepared on porous AlSi10Mg selective laser-melted components to improve their corrosion property. The microstructure and composition of the coatings at different processing times were characterized via scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction analysis, and X-ray photoelectron spectroscopy. Results showed that the diameter of micro-pores increased with an extension of treatment time, the porosity of coatings decreased from 6.24% to 0.85%. Thickness increased from 4.45 ± 0.01 μm to 15.20 ± 0.01 μm and surface roughness increased from 0.76 ± 0.01 μm to 5.41 ± 0.01 μm with increasing processing time. Meanwhile, the coatings were mostly composed of γ-Al2O3 and trace amounts of α-Al2O3, Al2SiO5, AlPO4 and WO3, the content of α-Al2O3 was increased from 0.51% to 4.12%. Corrosion current density decreased from 2.213 e−5 A·cm−2 to 1.088 e−7 A·cm−2. The polarization resistances Rb were increased from 4.8 × 103 Ω·cm2 to 2.6 × 105 Ω·cm2. The long term EIS results show that Rb was 7.7 × 103 Ω·cm2 after 3 weeks immersion, which show that the MAO coatings could provide good protection on AlSi10Mg alloy. The gas holes and defects of the SLM components were treated via MAO to form uniform MAO coatings on the surface of a sample, expanding the application range of selective laser-melted components in corrosive environments.

Ultra low bitrate retinal image compression using integer lifting scheme and subband encoder

Recently, ophthalmic clinics have seen many complaints related to retinal diseases. The degree of clarity of the blood vessels (BV) in the eye can be an important indicator of some diseases affecting the retina such as diabetic retinopathy. To diagnose it, we need to intervene more than a medical team, especially in some difficult cases, through the exchange of medical images obtained by photography. This method has contributed significantly to the production of large data that can quickly saturate transmission, storage systems and increase processing time, so the need to compress images efficiently without modifying the content before transmission represents a major challenge. This paper provides an effective method for compressing color retinal images (CRI), which relies on the use of an integer lifting scheme (ILS) based on cohen daubechies-feaveau wavelet (CDFW9/7) and the set partitioning in hierarchical trees (SPIHT) to encode large coefficients. The obtained results demonstrate that the suggested method reduce algorithmic complexity, improve the retinal image quality and achieves high objective parameters values for ultra-low bitrate compared to the conventional methods.

Alternative RNA extraction-free techniques for the real-time RT-PCR detection of SARS-CoV-2 in nasopharyngeal swab and sputum samples

Standard diagnoses of SARS-CoV-2 infections are done by RNA extraction and real-time RT-PCR (rRT-PCR). However, the need for RNA extraction complicates testing due to increased processing time, high cost, and limited availability of commercial kits. Therefore, alternative methods for rRT-PCR detection of SARS-CoV-2 without RNA extraction were investigated. Nasopharyngeal and sputum samples were used to compare the sensitivity of three techniques: Trizol RNA extraction, thermal shock, and the direct use of samples with an RNase inhibitor. Direct, extraction-free use of primary samples plus the RNase inhibitor produced diagnostic values of 100 % sensitivity and specificity compared to standard protocols, and these findings were validated in a second, independent laboratory.