Top Corner Research Articles

Front Cover: Visible‐Light Induced Oxidative Annulation of Enamides to 2,4,5‐Trisubstituted Oxazole Skeletons (Asian J. Org. Chem. 5/2023)

This cover is presented with a relatively dark background with a shining light on the top right corner, which highlights the blue light playing an important role in the transformation. Enamides are transformed into oxazoles under blue light irradiation. The ball of oxazole is on top of a carton of capsules indicating that oxazole skeletons are widely present in drugs and bioactive molecules. Four bioactive molecules bearing oxazole scaffolds are also presented in the picture. More information can be found in the Research Article by Le Liu et al.

Convolved Feature Vector Based Adaptive Fuzzy Filter for Image De-Noising

In this paper, a convolved feature vector based adaptive fuzzy filter is proposed for impulse noise removal. The proposed filter follows traditional approach, i.e., detection of noisy pixels based on certain criteria followed by filtering process. In the first step, proposed noise detection mechanism initially selects a small layer of input image pixels, convolves it with a set of weighted kernels to form a convolved feature vector layer. This layer of features is then passed to fuzzy inference system, where fuzzy membership degrees and reduced set of fuzzy rules play an important part to classify the pixel as noise-free, edge or noisy. Noise-free pixels in the filtering phase remain unaffected causing maximum detail preservation whereas noisy pixels are restored using fuzzy filter. This process is carried out traditionally starting from top left corner of the noisy image to the bottom right corner with a stride rate of one for small input layer and a stride rate of two during convolution. Convolved feature vector is very helpful in finding the edge information and hidden patterns in the input image that are affected by noise. The performance of the proposed study is tested on large data set using standard performance measures and the proposed technique outperforms many existing state of the art techniques with excellent detail preservation and effective noise removal capabilities.

Investigation of peak wind loading on a high-rise building in the atmospheric boundary layer using large-eddy simulations

Significant negative peak pressures have been observed in two recent wind tunnel experiments of a high-rise building for certain wind directions. This peak wind loading is crucial for the design of cladding systems. However, the governing flow physics is not well understood. In this study, large-eddy simulations with sufficient resolution are performed to capture and analyze these peak pressure phenomena. The atmospheric boundary layer flow is generated using a divergence free synthetic turbulence inflow generator before the high-rise building is placed in the flow at various wind directions. The mean, standard deviation, and peak pressure coefficients are shown to agree well with the experimental measurements. The strongest negative peak pressures near the top trailing corner on the leeward surface are captured by simulations with the resolved scale between the Taylor microscale and Kolmogorov scale. The probability density function of the pressure at the top trailing corner is well approximated using a log-normal distribution, which is a signature of the effect of small-scale turbulence intermittency. Flow visualization indicates that the strong negative peak values result from the interaction between small eddies shed from the separated flow region at the upwind roof edge and larger eddies downstream of the leeward roof edge.

Simultaneous control of combustion instabilities and NOx emissions in a lean premixed flame using linear genetic programming

Combustion instabilities have been a plaguing challenge in lean-conditioned propulsion systems. An open-loop control system was developed using machine learning to suppress pressure fluctuations and NOx emissions simultaneously. The open-loop control is realized by regulating the solenoid valve to modulate the methane supply. Control laws comprising the multi-frequency forcing are generated via the linear genetic programming (LGP), before being converted into square waves with different frequencies and duty cycles to activate the solenoid valve. The cost function is intended to evaluate and rank individuals of each generation, so as to select candidates for evolution. Optimized periodic forcing (OPF) with different duty cycles (d) and frequencies (fP) is set to provide a comparison with the superiority of multi-frequency forcing of LGP. Three stages of pressure oscillations and NOx emissions have been found as d increases from 0.5 to 1.0: high level, transition, and low level, revealing the transition of the combustion mode. After ten generations of development, the pressure amplitude and NOx emissions are reduced by 67.1% and 36.9% under the optimal control law identified by LGP, respectively. The flame structure images and Rayleigh index maps indicate that the convective movement of the flame, which may be the key factor driving combustion instabilities, can be suppressed by the optimal control law. Furthermore, the proximity graph of the similarity between control laws is introduced to depict the machine learning process, with the steepest descent lines visualizing its ridgeline topology. With the evolution process, individuals are found moving closer to the top right-hand corner of the map, and two main search pathways gradually become clear.

An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM

The regular detection and diagnosis mechanism for the silting disease of drainage pipelines (SDP) is critical for making dredging decisions and flood forecasting. Simultaneously, there is a complex coupling relationship between the pipeline siltation and the dynamic changes of the inlet and outlet flows. However, the traditional silting detection frameworks of drainage pipelines face difficulties in two aspects, accurate flow rate measurements and efficient and intelligent siltation diagnoses. In this paper, an automatic and integrated self-diagnosing system for the silting disease of drainage pipelines is proposed. First, a gradient penalty generative adversarial network (GPGAN), a target recognition algorithm called guided faster R-CNN (GF R-CNN) and an image segmentation method called parallel multiscale U-Net (PMSU-Net) are introduced to dynamically measure the flow of water in the drainage pipelines. Second, an automatic siltation detection and diagnosis algorithm of SDP is constructed based on a t-SNE stack sparse autoencoder (SSAE-TSNE) and multiscale long short-term memory (MS-LSTM). Then, a full-scale prototype verifies the feasibility of the system. This improved flow measurement algorithm achieves the highest accuracy of 90.32%, and an F1 score of 0.963 in comparison with the other algorithms, and the precision-recall curve was the closest to the top right corner. The error rate of the proposed self-diagnosing system is controlled within 8%, which is far better than the other algorithms. Finally, the system algorithms are embedded in an intelligent platform consisting of an unmanned pipeline measuring device (UPM), an unmanned aerial vehicle (UAV) and a server diagnostic centre. The practical application and test show that the accuracy, precision and response speed of the proposed integrated self-diagnosing system have obvious advantages in the function of siltation detection and diagnosis in drainage pipelines.

Energy Consumption Patterns and Characteristics of College Dormitory Buildings Based on Unsupervised Data Mining Method

The college building is a large energy consumer with a high density of energy consumption. However, less attention is paid to college buildings, particularly college dormitory buildings. Based on the one-year historical data collected from 20 college dormitory buildings located in Wuhan, China, this study aims to propose a three-stage strategy to identify and analyze the energy consumption patterns and characteristics of college dormitories in detail, including determining energy consumption patterns, analyzing key characteristics based on four indexes, and examining three influencing factors (occupants’ gender and floor and orientation location of rooms). The results show that the heavy energy users (around 10% of all occupants) consume around 20% of the total energy and have the narrowest comfort temperature range. However, the light energy users, 42% of total occupants, consume only approximately 27% of total energy. Their different tolerance to coldness is the main reason contributing to different energy consumption. The dormitories of males and location of the top floor and corner tend to consume significantly more energy in hot weather. This study would help campus facilities to understand the energy use behavior of occupants and formulate adequate policies so as to improve the energy management of campuses.

Electronic Structures and NLO Properties of a Series of TMDs Lateral‐Core–Shell Heterostructures Quantum Dots

AbstractThe electronic structures and nonlinear optical (NLO) responses of eight triangle group‐VI transition metal dichalcogenides (TMDs) lateral‐core–shell heterostructures quantum dots (QDs) [MaX2MbX2 and MXa2MXb2; M (Ma, Mb) = Mo and W; X (Xa, Xb) = S and Se] have been explored by using quantum chemistry method. Frontier molecular orbital (FMOs) analyses indicate that the triangular frameworks with more active W and/or Se atoms at shell have smaller energy gaps than those with Mo and/or S atoms, and the active sites of the ultra‐small TMD heterostructures mainly locate at the edge and/or the corner of the frameworks. Generally speaking, active atoms at the shell are beneficial to the enhancement of the frequency‐dependent first hyperpolarizabilities compared with the active atoms in the cores. First hyperpolarizability density analyses show that the local contributions of the first hyperpolarizability in x direction is mainly located at the left and right corners, while that in y direction is mainly located at the bottom edge and top corner, confirming the important role that the shell of the TMDs lateral‐core–shell heterostructure QDs play in its NLO response. Further, the electronic transitions contributed to the SHG responses also occur at the shell of these triangular frameworks.

Analysis of Stress and Deformation on Surrounding Rock Mass of a Trapezoidal Roadway in a Large Inclination Coal Seam and Novel High Yielding Prop Support: A Case Study

Trapezoidal roadways in large inclination coal seams show asymmetrical tectonic characteristics, while there is still a lack of theoretical results on stress, deformation, and efficient and effective supporting methods on high walls. In this paper, based on the geological characteristics of a large, inclined coal seam roadway, a mechanical model for stress–deformation analysis of trapezoidal section roadway was established. Complex analysis and a comfort map were employed to investigate the stress and deformation distribution on the roadway surface, and a novel yielding prop with high load capacity and constant working resistance was employed to support a high wall side based on analytical results. The results are as follows: (1) The deformation of the high wall is larger than that of the low wall, and the deformation of the roof is larger than that of the floor. The overall deformation of the surrounding rock shows that the rib closure is larger than the roof-to-floor closure. (2) The stress of the surrounding rock shows that both horizontal and vertical stresses are highest in the upper corner, indicating that the broken zone is most likely to occur at this location. (3) A new support employed with a high-yielding prop and a high-strength cable in a large, inclined angle roadway is proposed. On-site experiments were conducted in a large 5-1081 roadway of a coal mine in Shanxi, China. Under the influence of mining disturbance, the deformations at the top corner decreased by 40% compared with before. The test results show that the new support scheme can effectively control the development of roadway deformation and damage during the mining process. The new support also shows friendly environmental support and fast installation.

Design of Boosted Cascade and RTLBP Features based Face Recognition Module Using ML in OpenCV

Over the past ten years, face recognition in images has become more and more important. Since facial recognition is a natural talent for humans, it could be challenging to train a computer to recognize faces. The detecting difficulty comprises three stages. Without the requirement for picture difference or skin color identification, the detector operates in real-time at fifteen frames per second. Proposed and developed is a face recognition system based on Real Time Local Binary Pattern (RTLBP) and Boosted Cascade of Simple Features (BCSF). Preprocessing, face identification and recognition, and annotation are the three stages of the system. Segmentation, filtering, thresholding, and improving image quality are all part of preprocessing. The face, which is crucial for identification, is identified using the BCSF approach. Every face in the database has a correlation and RTLBP calculation. Correlation and RTLBP analysis between the captured face and the database face is then used to conduct recognition. One statistical technique that falls within the large category of factor analysis is the Boosted Cascade of Simple Features. By reducing the massive quantity of data stored to the extent of the feature space needed to represent the data efficiently, the BCSF seeks to achieve this goal. The RTLBP is designed to recognize faces by using a wide 1-D pixel vector consisting of a 2-D face picture in compact main parts of the space function. This is referred to as self-space projection. The identity of the vectors in the covariance matrix, which is centred on a set of fingerprint images, helps determine the proper space. Using OpenCV, Open Computer Vision (OpenCV), Python, Eigen-face, Fisher Face, LBPH, and Haar Cascade programming, an algorithm for a camera-based, real-time face recognition system is developed in this project. The name of the detected individual appears in the top left corner of a highlighted rectangle that annotates the face. The process of recognition takes 10.18 seconds, with a 99.93% success rate.

Study of finite fracture of the micro contact on the friction interface induced by stress waves

Frictional interface commonly exist in nature and kinds of materials. The dynamic behavior of the frictional interface has a profound impact on the macro strength and other properties of materials. This paper mainly studies the influence of finite fracture of the micro contact the interface under stress wave loading theoretically and simulatively. Based on the micro contact fracture mechanism of friction, a two-dimensional interface friction model including a triangular micro bulge is established with linear elastic constitutive relationship and D-P failure criterion. The results show that the interaction of the incoming stress disturbance and the micro bulge will induce the fracture of the bulge, and with the decrease of the inclination angle of the micro-contact, the fracture position of the triangular micro contact gradually moves upward from the root, and a crack propagating towards the matrix occurs in the top corner of the triangle. Moreover, in the micro process of fracture, a three wave profile centered on the fracture surface: longitudinal wave, transverse wave and interface wave, will be generated A new interesting phenomenon is that at the moment of loading, a micro stress disturbance is produced synchronously from the interface and propagates to the substrate in the form of longitudinal wave. More comparative examples and analysis show that the mechanism of this disturbance is related to the overall gravity micro adjustment acting on the interface. This work connects fracture and wave, and reveals the finite fracture of micro contact of the friction interface and wave effect, which is expected to provide an effective way for earthquake prediction, so as to advance the earthquake prediction time.

Estimating Forming Conditions for Deep Drawn SUS304 Square Cups Having no Delayed Cracks Using FE Simulation

Forming conditions for deep drawn SUS304 square cups having no delayed cracks are determined using finite element (FE) simulations based on the threshold % of wall thickening for delay cracking obtained from deep drawing tests of SUS304 cylindrical cups. The maximum drawing ratio and the initial blank thickness are fixed at 1.87 and 0.8 mm, respectively in this study taken into the considerations of the capacity of the press machine i.e., 100 kN. The blank holding forces (BHF), punch corner radius, rp and die corner radius, rd are varied to obtain 75 mm x 75 mm square cups having % of local thickening less than the threshold value i.e., 47% in the cracking zones located adjacent to the top corners of the cups. A quarter 3D FE simulation model of the deep drawing process is constructed, the wall thickness distributions of the cups are calculated. The simulation results showed that the forming conditions for the crack-free cups could be obtained with BHF ≥ 47 kN, rp ≥ 8.5 mm and 6.8 mm ≤ rd ≤ 9.5 mm. A method for designing the forming conditions of deep drawn SUS304 square cups is proposed in this study.

Hot deformation characteristics and dynamic recrystallization of biomedical CoCrWCu alloy

In order to explore the dynamic recrystallization of biomedical CoCrW-2Cu alloy, the hot deformation behavior was investigated by isothermal compression tests. True stress-true strain curves showed that the true stress increased with increasing strain rate or decreasing deformation temperature. Meanwhile, obvious dynamic softening was observed. The constitutive equation and processing maps were constructed to elucidate the relationship between true stress and deformation parameter. The phase component and microstructure were investigated to reveal the relationship between microstructure evolution and deformation condition, which was beneficial to the optimization of the hot deformation parameter. The variation of deformation condition has a limited influence on the phase component. The strain rate has a significant influence on the extent of recrystallization. An obviously discontinuous dynamic recrystallization (DDRX) process was occurred in this study. Furthermore, the extent of dynamic recrystallization (DRX) of sample deformed at 1100 °C/0.01 s -1 was the highest. Negative value of efficiency of power dissipation could be found in the top left corner of processing maps, while high value of efficiency of power dissipation was observed in the region with high temperature and low strain rate. The processing maps predicted that the optimized deformation parameters were 1100~1150 °C and 0.01~0.1 s -1 .

:Lines of Thought: Branching Diagrams and the Medieval Mind

:<i>Lines of Thought: Branching Diagrams and the Medieval Mind</i>

A small wideband inverted l-shaped flexible antenna for sub-6 GHz 5G applications

This manuscript carries out design and examination of flexible inverted l-shaped connected with a circular ring having plus-shaped geometry on the top left corner and a partial ground on the back. The antenna is realized on a flexible polyimide substrate which is fabricated for further investigation. The flexible resonator achieves a designed footprint of 20 × 30 × 0.2 mm3. The antenna is analyzed in terms of |S11|, 2D gain, radiation patterns, and efficiency under both normal and bend conditions. The antenna shows a decent match between experimental and software simulated data. To establish the use of the proposed design for 5G MIMO applications, an 8-port MIMO with the common ground is designed where the antenna shows satisfactory isolation >15 dB and ECC <0.01 which makes the flexible antenna an excellent choice for realizing the 5G MIMO antennas working at sub-6 GHz band.

Design and Evaluation of a Silent Speech-Based Selection Method for Eye-Gaze Pointing

We investigate silent speech as a hands-free selection method in eye-gaze pointing. We first propose a stripped-down image-based model that can recognize a small number of silent commands almost as fast as state-of-the-art speech recognition models. We then compare it with other hands-free selection methods (dwell, speech) in a Fitts' law study. Results revealed that speech and silent speech are comparable in throughput and selection time, but the latter is significantly more accurate than the other methods. A follow-up study revealed that target selection around the center of a display is significantly faster and more accurate, while around the top corners and the bottom are slower and error prone. We then present a method for selecting menu items with eye-gaze and silent speech. A study revealed that it significantly reduces task completion time and error rate.

Circular slotted patch with defected grounded monopole patch antenna for microwave-based head imaging applications

Medical microwave imaging (MWI) research has gained more attention in recent decades, particularly with regard to the early detection of brain tumors. It offers numerous benefits over existing imaging technologies, including magnetic resonance imaging (MRI) and computed tomography (CT) scans. Antennas represent a key element of MWI systems, so optimizing their performance is critical. A new, simple patch antenna for MWI is presented in this article. The radiating patch has a circular slot and a tiny triangular cut at the top right corner, and it is designed and manufactured with a low-cost FR4-epoxy substrate with a loss tangent of 0.02 and a dielectric constant of 4.4. The overall dimensions are 0.28λ × 0.22λ × 0.005λ (where λ is the wavelength of a lower frequency of 1.22 GHz). A total impedance bandwidth (<-10 dB) of 2.23 GHz (1.22–3.45 GHz) is achieved with a very decent gain of above 5 dBi (measured) and above 85 % efficiency over the functional range. Time-domain assessment of the antenna confirms minimum signal distortion and shows a better response in terms of group delay (GD) and fidelity factor (FF, 92 %). Measurements confirm the results from simulations (CST and HFSS) with a reasonable degree of agreement. Finally, the 3D-electromagnetic CST simulator was utilized to analyze the behavior of a nine-antenna array placed around a 3D-realistic Hugo-head model; it yielded satisfactory results and proved the practical utility of the proposed antenna in the intended MWI application.

Aaru

<i>Aaru</i>

PENGARUH LATIHAN VARIASI SHOOTING TERHADAP KEMAMPUAN SHOOTING PADA PEMAIN SEPAK BOLA

The purpose of this study was to determine the effect of shooting variations on shooting skills in soccer games for PS Malaju players, Kilo District, Dompu Regency in 2022. The design of this study used an experimental method with data collection techniques using test and measurement techniques. The population in this study were all players of the PS Malaju Club, totaling 23 players with probability techniques. The instrument used is by dividing the goal field into six scoring areas. The top corner is worth 40 points, the bottom corner is worth 50 points, the top half is worth 20 points, the bottom half is worth 10 points with four balls in front of the goal. Players have 15 seconds to kick all four balls towards the goal and record the score. The data analysis technique used in this study uses the Analytical Requirements Test, Normality Test, Homogeneity Test and Hypothesis Testing. Based on the research data, most of the PS Malaju Club players experienced an increase in the shooting variation practice test on their shooting ability. It can be seen that most of the PS Malaju Club players have a large score difference. The difference score is obtained by subtracting the post-test score from the pre-test score. Of the 23 players of the PS Malaju Club, only five players did not experience an increase in shooting variations after doing 2 treatments or 12 times of treatment. The results of the data obtained are with a confidence level = 95% or (α) = 0.05 the number of samples for the experimental club = 23, obtained t-table = 2.073. Based on the calculation results, the average value of the pre-test data was 82.61 while the post-test data obtained a value of 115.65 and t-count = 3.902 with a sig = 0.001 &gt; 40.613 so "Ho is rejected", it can be concluded that there is an average difference The mean is significant between the pre-test data and the post-test data for shooting variations. The results of the regression analysis showed that it was significant 0.00 or P &lt;0.05 and the coefficient of influence was 0.01.

Investigating the performance of high-strength steel shear wall with opening and pre-crack Community Verified icon

The use of steel shear wall in engineering construction, including high-rise building projects that bear several sides, is very interesting and practical. Since the steel shear wall with opening may be damaged by pre-cracks and cause damage to the shear wall, in this study, the effect of pre-crack and opening in the three-span and one-span frame with steel shear wall has been evaluated. In this study, 48 samples have been studied using finite element method and Abaqus software. Separate and lateral loading has been applied to the samples and pre-crack positions, pre-crack length and shear steel sheet material have been investigated The results of this study showed that the numerical model made for the shear wall provides reliable answers compared to the laboratory model. In the studied shear walls, the parameter of crack length and crack position has a great effect on the ductility capacity, while it has little effect on the hardness and strength index. The most critical pre-crack modes in the horizontal position, located at the top or bottom corner of the frame, have had a great impact on the lateral behavior and reduced ductility by 60% and wall strength by 32%. On the other hand, by changing the materials of the shear wall steel sheet from LYP steel to St37 and St52, the ultimate strength and hardness have increased by 3.63 and 1.45 times, respectively, and the ductility has decreased by 30% .

Analysis on wear patterns and mechanisms of carbide tool for face-hobbing of spiral bevel gear

Spiral bevel gear is widely used in the automotive and aerospace manufacturing industries, and the machining process is complex and the material is difficult to cut. The characteristics of high hardness, strong chemical reactivity and poor heat dissipation make the machinability of 20CrMnTi poor for face-hobbing machining of spiral bevel gear. In the process of cutting, there are some problems such as severe tool wear, poor machining quality and low machining efficiency caused by higher cutting force and higher cutting temperature. Therefore, it is necessary to study and analyze the wear experiment of the cutting tools of spiral bevel gear for face-hobbing deeply. Firstly, under the single factor experimental conditions, the wear patterns of inside blade and outside blade are observed and analyzed at different rotational speeds, and the tool wear conditions are detected and measured analysis. Secondly, the tool wear morphology and element distribution of rake face and flank face of inside blade and outside blade are analyzed by scanning electron microscope and energy spectrometer, and the tool wear mechanism for face-hobbing of spiral bevel gear is discussed in depth. The results demonstrate that chipping and fracture are the main patterns of tool wear; the tool wear mechanism are mainly embodied in adhesive wear, diffusion wear and oxidation wear. The tool wear is mainly distributed on the main cutting edge, top edge and corner radius, and the top edge and corner radius are more seriously worn. The research results can provide an effective basis for exploring the tool wear mechanism and improving the tool life, and provide technical support for the design and development of gear machining tools.