• 한국축산식품학회지
• /
• 제43권3호
• /
• pp.428-440
• /
• 2023

Global meat consumption is increasing worldwide, however, supply remains lacking. Several alternative protein sources, such as cultured meat, plant-based protein production, and edible insects, have been proposed to overcome this shortage. Interestingly, edible insects are characterized by superior digestive and absorptive qualities that make them the ideal replacement for traditional protein production. This study aims to further the processing ability of insect protein by investigating the effects of various pre-treatment methods, such as blanching (HB), roasting (HR), and superheated steam (HS), on the nutritional properties and physicochemical characteristics of proteins extracted from Hermetia illucens larvae. The drying rate, pH value, color analysis, amino and fatty acid profile, as well as bulk density, shear force, and rehydration ratios of the above pre-treatment methods, were explored. HS was found to have the highest drying rate and pH value analysis showed that HB and HS samples have significantly higher values compared to the other modalities. Raw edible insects had the highest value in the sum of essential amino acid (EAA) and EAA index when compared to EAAs. HB and HS showed significantly lower bulk density results, and HS showed the highest shear force and the highest value in rehydration ratio, regardless of immersion time. Therefore, taking the above results together, it was found that blanching and superheated steam blanching pre-treatment were the most effective methods to improve the processing properties of H. illucens after hot-air drying.

• 동아시아식생활학회지
• /
• 제27권4호
• /
• pp.365-377
• /
• 2017

The objective of this study was to investigate the sensory quality characteristics of coffee under various processing and roasting conditions of green beans. Colombia green bean samples were obtained from three processing methods: natural, pulped-natural, and washed methods. The green beans were roasted differently according to Agtron number: light (Agrton #65), medium (Agtron #55), and dark (Agtron #45). Moisture content, density, color value, pH, and total dissolved solid contents (TDS) were measured, and quantitative descriptive analysis (QDA) with 23 sensory attributes was performed for nine coffee samples. Hunter L values were significantly elevated with the degree of processing but reduced with roasting intensity. The pH values of the nine coffee samples were 5.6~6.2 and significantly increased with intensity of roasting. TDS decreased with an increase in processing and increased with roasting intensity. QDA results show that smoky aroma and nutty and chocolate flavor significantly increased while fruit and floral aroma decreased with intensity of processing. The attributes of brownness, oily surface, smoky aroma, bitter and burnt flavor, and greasy and heavy mouthfeel significantly increased while fruity and floral aroma, black tea, sour and umami flavor, pureness, and softness decreased as roasting intensity increased. Principle component analysis showed the overall significant relationships between 23 sensory attributes and nine coffee samples under different processing and roasting conditions.

• 융합신호처리학회논문지
• /
• 제16권3호
• /
• pp.83-89
• /
• 2015

Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.

• Nuclear Engineering and Technology
• /
• 제51권1호
• /
• pp.146-154
• /
• 2019

An improved principal component analysis (PCA) method is applied for sensor fault detection and isolation (FDI) in a nuclear power plant (NPP) in this paper. Data pre-processing and false alarm reducing methods are combined with general PCA method to improve the model performance in practice. In data pre-processing, singular points and random fluctuations in the original data are eliminated with various techniques respectively. In fault detecting, a statistics-based method is proposed to reduce the false alarms of $T^2$ and Q statistics. Finally, the effects of the proposed data pre-processing and false alarm reducing techniques are evaluated with sensor measurements from a real NPP. They are proved to be greatly beneficial to the improvement on the reliability and stability of PCA model. Meanwhile various sensor faults are imposed to normal measurements to test the FDI ability of the PCA model. Simulation results show that the proposed PCA model presents favorable performance on the FDI of sensors no matter with major or small failures.

• 한국도로학회논문집
• /
• 제9권4호
• /
• pp.215-226
• /
• 2007

차량방호 안전시설에 대한 성능의 검증은 충돌시험의 가속도와 각속도 데이터를 사용하여 산정한 탑승자 안전지수를 평가하여 이루어진다. 탑승자 안전지수로는 THIV(Theoretical Head Impact Velocity), PHD(Post-impact Head Deceleration), ASI(Acceleration Severity Index), OIV(Occupant Impact Velocity)와 ORA(Occupant Ridedown Acceleration)가 있다. 탑승자 안전지수 계산에 상이한 데이터 처리과정과 수치절차의 적용이 가능하기 때문에 동일한 시험 데이터에 대하여 다양한 탑승자 안전지수값이 결정될 수 있어서 혼란이 초래되고 있는 실정이다. 이러한 문제를 해결하기 위하여 다양한 상세절차와 데이터 처리과정이 탑승자 안전지수에 미치는 영향을 조사하였다. 지침에 제시된 계측시간간격을 사용하여 차량충돌시험이 수행된다면 보간법과 수치적분방법은 THIV와 OIV 값에 영향을 크게 미치지 않았다. 그리고 PHD에 대한 10msec 이동평균방법과 데이터 처리과정의 영점보정은 탑승자 안전지수에 상당한 영향을 미치기 때문에 이에 관한 구체적인 방법이 지침에 규정되어야 한다.

• 한국컴퓨터정보학회논문지
• /
• 제22권6호
• /
• pp.131-140
• /
• 2017

As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

• International Journal of Advanced Culture Technology
• /
• 제10권2호
• /
• pp.252-259
• /
• 2022

Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

• 한국연소학회지
• /
• 제16권3호
• /
• pp.21-26
• /
• 2011

Thermal analyses are conducted to measure chemical kinetic parameters of an unknown liquid fuel with various components. Thermal Analyses are divided into two different methods such as TGA(Thermo-Gravimetric Analysis) and DSC(Differential Scanning Calorimety). Non-isothermal experimental results are analyzed by adopting TGA and they are filtered by Freeman-Carroll method. As a results of the analysis, chemical parameters of the activation temperature and the reaction order are measured to be 6128.2 K and 1.4, respectively. Furthermore, the chemical kinetic parameters are obtained by a variety of mathematical processing methods. It has been found that they show a little difference depending on the processing method.

• 한국공작기계학회논문집
• /
• 제16권5호
• /
• pp.178-182
• /
• 2007

This study represents the efficient depth measurement for 3-dimensional microsystems using the disparity histogram from stereo images. Implementation of user-friendly Windows program written in C++ involves the various methods for the stereo-image processing in which the minimization of matching-pixel error upon the unique point for stereo images was carried out as a pre-processing method. Even though MPC among various methods was adopted in the present measurement, the resulting measurements seem to require optimizations of the windows sizes and corrections of post-manipulation for stereo images. The present work using Windows program is promising to measure the 3-dimensional depth of micro-system efficiently in implementing the 3-dimensional structure of micro-systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권10호
• /
• pp.4948-4967
• /
• 2017

On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.