• KCI Concrete Journal
• /
• v.13 no.2
• /
• pp.10-18
• /
• 2001

The spectral analysis of surface waves (SASW) method, which is an in-situ seismic technique, has mainly been developed and used for many years to determine the stiffness profile of layered media (such as asphalt concrete and layered soils) in an infinite half-space. This paper presents a modified experimental technique for nondestructive evaluation of in-place cement mortar compressive strength in single-layer concrete slabs of rather a finite thickness through a correlation to surface wave velocity. This correlation can be used in the quality control of early age cement mortar structures and in evaluating the integrity of structural members where the infinite half space condition is not met. In the proposed SASW field test, the surface of the structural members is subjected to an impact, using a 12 mm steel ball, to generate surface wave energy at various frequencies. Two accelerometer receivers detect the energy transmitted through the medium. By digitizing the analog receiver outputs, and recording the signals for spectral analysis, surface wave velocities can be identified. Modifications to the SASW method includes the reduction of boundary reflections as adopted on the surface waves before the point where the reflected compression waves reach the receivers. In this study, the correlation between the surface wave velocity and the compressive strength of cement mortar is developed using one 36"x36"x4"(91.44$\times$91.44$\times$91.44 cm) cement mortar slab of 2,000 psi (140 kgf/$\textrm{cm}^2$) and two 36"x36"x4"(91.44$\times$91.44$\times$91.44 cm) cement mortar slabs of 3,000 psi (210 kgf/$\textrm{cm}^2$).

• Proceedings of the Korean Geotechical Society Conference
• /
• 2000.03b
• /
• pp.109-116
• /
• 2000

Rippability refers to the ease of excavation by construction equipment. Since it is related to rock quality in terms of hardness and fracture density, which may be measured by seismic refraction surveys, correlations have been made between rippability and seismic P wave velocities. The 1-channel signal enhancement seismograph(Bison, Model 1570C) was used to measure travel time of the seismic wave through the ground, from the source to the receiver. The seismic velocity measurement was conducted with 153 lines at 5 rock slopes of Chungbuk Youngdong area. Schmidt rebound hardness test were conducted with 161 points on rock masses and the point load test also on 284 rock samples. The uniaxial compressive strength and seismic wave velocity of 60 rock specimens were measured in laboratory. These data were used to evaluate the rock quality of 5 rock slopes.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.2141-2145
• /
• 2015

A new broadcasting signal transmission, which can save its channel bandwidth using compressive sensing(CS), is proposed in this paper. A new compression technique, which uses two dimensional discrete wavelet transform technique, is proposed to get high sparsity of multimedia image. A L1 minimization technique based on orthogonal matching pursuit is also introduced in order to reconstruct the compressed multimedia image. The CS enables us to save the channel bandwidth of wired and wireless broadcasting signal because various transmitted data are compressed using it. A $256{\times}256$ gray-scale image with compression rato of 20 %, which is sampled by 10 Gs/s, was transmitted to an optical receiver through 20-km optical transmission and then was reconstructed successfully using L1 minimization (bit error rate of $10^{-12}$ at the received optical power of -12.2 dB).

• Computers and Concrete
• /
• v.32 no.3
• /
• pp.327-337
• /
• 2023

Concrete is the most widely used building material, with various types including high- and ultra-high-strength, reinforced, normal, and lightweight concretes. However, accurately predicting concrete properties is challenging due to the geotechnical design code's requirement for specific characteristics. To overcome this issue, researchers have turned to new technologies like machine learning to develop proper methodologies for concrete specification. In this study, we propose a highly accurate deep learning-based predictive model to investigate the compressive strength (UCS) of lightweight concrete with natural aggregates (pumice). Our model was implemented on a database containing 249 experimental records and revealed that water, cement, water-cement ratio, fine-coarse aggregate, aggregate substitution rate, fine aggregate replacement, and superplasticizer are the most influential covariates on UCS. To validate our model, we trained and tested it on random subsets of the database, and its performance was evaluated using a confusion matrix and receiver operating characteristic (ROC) overall accuracy. The proposed model was compared with widely known machine learning methods such as MLP, SVM, and DT classifiers to assess its capability. In addition, the model was tested on 25 laboratory UCS tests to evaluate its predictability. Our findings showed that the proposed model achieved the highest accuracy (accuracy=0.97, precision=0.97) and the lowest error rate with a high learning rate (R2=0.914), as confirmed by ROC (AUC=0.971), which is higher than other classifiers. Therefore, the proposed method demonstrates a high level of performance and capability for UCS predictions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4160-4176
• /
• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.

• Journal of Biomedical Engineering Research
• /
• v.23 no.1
• /
• pp.49-60
• /
• 2002

Receive dynamic focusing with an array transducer can provide near optimum resolution only in the vicinity of transmit focal depth. A customary method to increase the depth of field is to combine several beams with different focal depths, with an accompanying decrease in the frame rate. In this Paper. we Present a simultaneous multiple transmit focusing method in which chirp signals focused at different depths are transmitted at the same time. These chirp signals are mutually orthogonal in a sense that the autocorrelation function of each signal has a narrow mainlobe width and low sidelobe levels. and the crossorelation function of any Pair of the signals has values smaller than the sidelobe levels of each autocorrelation function. This means that each chirp signal can be separated from the combined received signals and compressed into a short pulse. which is then individually focused on a separate receive beamformer. Next. the individually focused beams are combined to form a frame of image. Theoretically, any two chirp signals defined over two nonoverlapped frequency bands are mutually orthogonal In the present work. however, a tractional overlap of adjacent frequency bands is permitted to design more chirp signals within a given transducer bandwidth. The elevation of the rosscorrelation values due to the frequency overlap could be reduced by alternating the direction of frequency sweep of the adjacent chirp signals We also observe that the Proposed method provides better images when the low frequency chirp is focused at a near Point and the high frequency chirp at a far point along the depth. better lateral resolution is obtained at the far field with reasonable SNR due to the SNR gain in Pulse compression Imaging .