• Food Science of Animal Resources
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• v.43 no.6
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• pp.1150-1169
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• 2023

Edible insects are gaining popularity as a potential future food source because of their high protein content and efficient use of space. Black soldier fly larvae (BSFL) are noteworthy because they can be used as feed for various animals including reptiles, dogs, fish, chickens, and pigs. However, if the edible insect industry is to advance, we should use automation to reduce labor and increase production. Consequently, there is a growing demand for sensing technologies that can automate the evaluation of insect quality. This study used short-wave infrared (SWIR) hyperspectral imaging to predict the proximate composition of dried BSFL, including moisture, crude protein, crude fat, crude fiber, and crude ash content. The larvae were dried at various temperatures and times, and images were captured using an SWIR camera. A partial least-squares regression (PLSR) model was developed to predict the proximate content. The SWIR-based hyperspectral camera accurately predicted the proximate composition of BSFL from the best preprocessing model; moisture, crude protein, crude fat, crude fiber, and crude ash content were predicted with high accuracy, with R² values of 0.89 or more, and root mean square error of prediction values were within 2%. Among preprocessing methods, mean normalization and max normalization methods were effective in proximate prediction models. Therefore, SWIR-based hyperspectral cameras can be used to create automated quality management systems for BSFL.

• Korean journal of applied entomology
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• v.35 no.2
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• pp.119-125
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• 1996

Temperature-dependent development study for overwintered eggs of Pseudococcus comstocki (Kuwana) wasconducted to develop a forecasting model for egg hatch date. Hatch times of overwintered eggs were comparedat five constant temperatures (10, 15, 20, 25, 27$^{\circ}$C) and different collection dates. A nonlinear, four-parameterdevelopmental model with high temperature inhibition accurately described (R2=0.9948) mean developmentalrates of all temperatures. Variation in developmental times was modeled(~~=0.972w9)it h a cumulative Weibullfunction. Least-squares linear regression (rate=O.O06358[Temp.]-0.07566)d escribed development in the linearregion (15-25$^{\circ}$C) of the development curve. The low development threshold temperature was estimated 11.9"Cand 154.14 degree-days were required for complete development. The linear degree-day model (thermal summation)and rate summation model (Wagner et al. 1985) were validated using field phenology data. In degreedaymodels, mean-minus-base method, sine wave method, and rectangle method were used in estimation of dailythermal units. Mean-minus-base method was 18 to 28d late, sine wave method was 11 to 14d late, rectanglemethod was 3 to 5d late, and rate summation model was 2 to 3d late in predicting 50% hatch of overwinteredeggs. hatch of overwintered eggs.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.26-33
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• 2017

Vehicle communication can facilitate efficient coordination among vehicles on the road and enable future vehicular applications such as vehicle safety enhancement, infotainment, or even autonomous driving. In the $3^{rd}$ Generation Partnership Project (3GPP), many studies focus on long term evolution (LTE)-based vehicle communication. Because vehicle speed is high enough to cause severe channel distortion in vehicle-to-vehicle (V2V) environments. We can utilize channel estimation methods to approach a reliable vehicle communication systems. Conventional channel estimation schemes can be categorized as least-squares (LS), decision-directed channel estimation (DDCE), spectral temporal averaging (STA), and smoothing methods. In this study, we propose a smart channel estimation scheme in LTE-based V2V environments. The channel estimation scheme, based on an LTE uplink system, uses a demodulation reference signal (DMRS) as the pilot symbol. Unlike conventional channel estimation schemes, we propose an adaptive smoothing channel estimation scheme (ASCE) using quadratic smoothing (QS) of the pilot symbols, which estimates a channel with greater accuracy and adaptively estimates channels in data symbols. In simulation results, the proposed ASCE scheme shows improved overall performance in terms of the normalized mean square error (NMSE) and bit error rate (BER) relative to conventional schemes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.11-22
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• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.177-187
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• 2014

This paper proposes a fast subspace tracking methods, which is called GVFF FAPI, based on FAPI (Fast Approximated Power Iteration) method and GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Lease Squares). Since the conventional FAPI uses a constant forgetting factor for estimating covariance matrix of source signals, it has difficulty in applying to non-stationary environments such as continuously changing DOAs of source signals. To overcome the drawback of conventioanl FAPI method, the GVFF FAPI uses the gradient-based variable forgetting factor derived from an improved means square error (MSE) analysis of RLS. In order to achieve the decreased subspace error in non-stationary environments, the GVFF-FAPI algorithm used an improved forgetting factor updating equation that can produce a fast decreasing forgetting factor when the gradient is positive and a slowly increasing forgetting factor when the gradient is negative. Our numerical simulations show that GVFF-FAPI algorithm offers lower subspace error and RMSE (Root Mean Square Error) of tracked DOAs of source signals than conventional FAPI based MUSIC (MUltiple SIgnal Classification).

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.559-570
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• 2017

A partial least squares regression (PLSR) model was developed to map the internal soluble solids content (SSC) of apples using a ground-based hyperspectral scanner that could simultaneously acquire outdoor data and capture images of large quantities of apples. We evaluated the applicability of various preprocessing techniques to construct an optimal prediction model and calculated the optimal band through a variable importance in projection (VIP)score. From the 515 bands of hyperspectral images extracted at wavelengths of 360-1019 nm, 70 reflectance spectra of apples were extracted, and the SSC ($^{\circ}Brix$) was measured using a digital photometer. The optimal prediction model wasselected considering the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP) and coefficient of determination of prediction $r_p^2$. As a result, multiplicative scatter correction (MSC)-based preprocessing methods were better than others. For example, when a combination of MSC and standard normal variate (SNV) was used, RMSECV and RMSEP were the lowest at 0.8551 and 0.8561 and $r_c^2$ and $r_p^2$ were the highest at 0.8533 and 0.6546; wavelength ranges of 360-380, 546-690, 760, 915, 931-939, 942, 953, 971, 978, 981, 988, and 992-1019 nm were most influential for SSC determination. The PLSR model with the spectral value of the corresponding region confirmed that the RMSEP decreased to 0.6841 and $r_p^2$ increased to 0.7795 as compared to the values of the entire wavelength band. In this study, we confirmed the feasibility of using a hyperspectral scanner image obtained from outdoors for the SSC measurement of apples. These results indicate that the application of field data and sensors could possibly expand in the future.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.252-257
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• 2012

Purpose: The net rind pattern and color of melon surface are important for a high market value of melon fruits. The development of the net and color are closely related to the changes in shape, size, and maturing. Therefore, the net and color characteristics can be used indicators for assessment of melon quality. The goal of this study was to investigate the possibility of estimating melon soluble solids content (SSC) and firmness by analyzing the net and color characteristics of fruit surface. Methods: The true color images of melon surface obtained at fruit equator were analyzed with 18 color features and 9 texture features. The partial least squares (PLS) method was used to estimate SSC and firmness in melons using their color and texture features. Results: In sensing melon SSC, the coefficients of determination of validation (${R_v}^2$) of the prediction models using the color and texture features were 0.84 (root mean square error of validation, RMSEV: 1.92 $^{\circ}Brix$) and 0.96 (RMSEV: 0.60 $^{\circ}Brix$), respectively. The ${R_v}^2$ values of the models for predicting melon firmness using the color and texture features were 0.64 (RMSEV: 4.62 N) and 0.79 (RMSEV: 2.99 N), respectively. Conclusions: In general, the texture features were more useful for estimating melon internal quality than the color features. However, to strengthen the usefulness of the color and texture features of melon surface for estimation of melon quality, additional experiments with more fruit samples need to be conducted.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.447-461
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• 2018

Domestic film industry sales are increasing every year. Theaters are the primary sales channels for movies and the number of audiences using the theater affects additional selling rights. Therefore, the number of audiences using the theater is an important factor directly linked to movie industry sales. In this paper we consider a hybrid model that combines a multiple linear regression model and the Bass model to predict the audience numbers for a specific day. By combining the two models, the predictive value of the regression analysis was corrected to that of the Bass model. In the analysis, three films with different release dates were used. All subset regression method is used to generate all possible combinations and 5-fold cross validation to estimate the model 5 times. In this case, the predicted value is obtained from the model with the smallest root mean square error and then combined with the predicted value of the Bass model to obtain the final predicted value. With the existence of past data, it was confirmed that the weight of the Bass model increases and the compensation is added to the predicted value.

• Development and Reproduction
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• v.16 no.4
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• pp.309-314
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• 2012

This study was conducted to analyze the difference of body types within and between wild and farmed populations of olive flounder Paralichthys olivaceus using measured records of morphological traits. The results showed that surveyed traits and standard deviation were $1,355{\pm}742g$ of body weight, $48.01{\pm}7.79cm$ of total length, and $40.96{\pm}6.80cm$ of body length. Also body height, body shape index and condition factor were $17.19{\pm}3.43cm$, $9.99{\pm}0.74$ and $11.16{\pm}1.54$, respectively. As result of least squares mean and standard error for each trait assumed in this study, those of farmed population showed significantly higher than those of wild population in all traits, exclusively in total length and body length (p<0.01). Particularly, the values of the body height and the body weight of the farmed population were higher than those of the wild population in the same total length. And the phenotypic correlation coefficients of the body weight, the total length, the body length and the body height showed strong positive correlation in all populations. These result suggested that morphological differences exist in farmed and wild flounder. Therefore, introduction of wild flounder is essential for the future production to improve the body type of farmed flounder, and parental fish should be chosen by considering selection of commercially important traits in the production process.