• International journal of advanced smart convergence
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• v.11 no.3
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• pp.157-161
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• 2022

The coffee industry continues to grow steadily due to the spread of coffee and changes in consumer awareness. Once upon a time, instant coffee was common, People today have distinct personal preferences As consumption needs for favorite foods are segmented, ways to enjoy coffee are diversifying. This study was conducted through analysis of consumption changes for specialty coffee as a changed issue of COVID-19 The goal is to present a vision for the future of the specialty coffee industry. As a research method, text mining through big data analysis was conducted to extract and analyze factors affecting the change in specialty coffee consumption. As a result of the study, we judged that specialty coffee is consumed by using a drip tool that allows you to easily enjoy coffee at home after Corona 19. Therefore, hand drips used in home cafes were found to play a central role in the change in specialty coffee consumption.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1178-1184
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• 2015

In conventional robotics, charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS) cameras have been utilized for acquiring vision information. These devices have problems, such as narrow optic angles and inefficiencies in visual information processing. Recently, biomimetic vision sensors for robotic applications have been receiving much attention. These sensors are more efficient than conventional vision sensors in terms of the optic angle, power consumption, dynamic range, and redundancy suppression. This paper presents recent research trends on biomimetic vision sensors and discusses future directions.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.738-747
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• 2021

Today, with the improvement of deep learning technology, computer vision areas such as image classification, object detection, object segmentation, and object tracking have shown remarkable improvements. Various applications such as intelligent surveillance, robots, Internet of Things, and autonomous vehicles in combination with deep learning technology are being applied to actual industries. Accordingly, the requirement of an efficient compression method for video data is necessary for machine consumption as well as for human consumption. In this paper, we propose an object-based compression of thermal infrared images for machine vision. The input image is divided into object and background parts based on the object detection results to achieve efficient image compression and high neural network performance. The separated images are encoded in different compression ratios. The experimental result shows that the proposed method has superior compression efficiency with a maximum BD-rate value of -19.83% to the whole image compression done with VVC.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.89-94
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• 2022

The Saudi Vision 2030 defined the directions of the national economy and market towards diversifying sources of income, and developing energy to become less dependent on oil. The study sought through a theoretical review to identify the reality of the energy sector and the areas of investment available in the field of renewable energy. Findings showed that investment in the renewable energy sector is a promising source according to solar, wind, hydrogen, geothermal energy and burning waste than landfill to extract biogas for less emission. The renewable energy sector faces challenges related to technology, production cost, price, quantity of production and consumption, and markets. The study revealed some recommendations providing and suggested electronic marketing system to provide investors and consumers with energy available from renewable sources.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.89-98
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• 2024

Due to the increase in population and consequently the increase in the production of plastic waste, recovery of this part of the waste is an undeniable necessity. On the other hand, the recycling of plastic waste, if it is placed in a systematic process and controlled, can be effective in creating jobs and maintaining environmental health. Waste collection in many large cities has become a major problem due to lack of proper planning with increasing waste from population accumulation and changing consumption patterns. Today, waste management is no longer limited to waste collection, but waste collection is one of the important areas of its management, i.e. training, segregation, collection, recycling and processing. In this study, a systematic method based on machine vision for sorting plastic bottles in different colors for recycling purposes will be proposed. In this method, image classification and segmentation techniques were presented to improve the performance of plastic bottle classification. Evaluation of the proposed method and comparison with previous works showed the proper performance of this method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.476-479
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• 2003

The Rough transform (HT) is often used for extracting global features in binary images, for example curve and line segments, from local features such as single pixels. The HT is useful due to its insensitivity to missing edge points and occlusions, and robustness in noisy images. However, it possesses some disadvantages, such as time and memory consumption due to the number of input data and the selection of an optimal and efficient resolution of the accumulator space can be difficult. Another problem of the HT is in the difficulty of peak detection due to the discrete nature of the image space and the round off in estimation. In order to resolve the problem mentioned above, a possibilistic C-means approach to clustering [1] is used to cluster neighboring peaks. Several experimental results are given.

• Journal of Fashion Business
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• v.7 no.6
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• pp.21-31
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• 2003

The CLI(Consumer Life Information) is a new study to unite and create new values recognizing the importance of knowledge and information in information-oriented society based on domestic science and digital technology. The objective of this research is to define academic identity of consuming science and CLI, to analyze the theory, styles, manners, psychology and the concept of consumption, which is the base of consuming life, and to present the direction of CLI with tasks and three major axises of CLI. Nowadays, international order demands new paradigms from human beings. Especially, vision and creation of the values are settled as methodological ways considering the economic power. The CLI should be on the same horizon adjusting social change of pointing values and quality in consuming patterns of diversity and variety. Therefore, I would suggest the ways for the CLI to head for as follows. First, it is to perceive the 3 major Axises & Task of CLI. Second, it is to develope service (experiencing goods) and goods that can lead consuming lives. Third, it is to study merchandising strategy, to create new signs and symbols of goods, and to collaborate of R & D(reseach and developement) and Business. Fourth, it is to head for globalization. Consequantly, this study will be helpful to establish the theory of relationship between producer and consumer in fashion business included research and developments of qualitative goods.

• Journal of the Korea Institute of Building Construction
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• v.20 no.1
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• pp.53-60
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• 2020

This paper aims to examine the insulation performance of insulated gang form by changing the energy (power) consumption and concrete calorific value to assist in concrete protection in cold weather. According to the test results, the general gang form will generate three times the energy (power) consumption for 12 hours after the concrete is poured. In contrast, insulated gang foam consumed no energy (power) for 21 hours after pouring. The final power consumption was 3.7 times higher than that of the general gang form, confirming the improved performance of insulated gang form with regard to energy (power) consumption. The calorific value examination shows that the calorific value changes significantly according to the change of outside temperature after concrete placement in the case of the general gang form. However, in the case of the insulated gang form, only a slight heat loss occurred in the part of the frame, and it showed a constant heating pattern from the concrete casting to the demolding of the mold.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.2
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• pp.85-92
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• 2015

Since the consumption of the livestock products increased for the past 10 years in Korea, the water use for live animals has become more important in terms of water savings. Therefore, the index connecting water use and livestock products consumption should be required for sustainable water management, and water footprint concept could be suggested as the index. The aim of this study is to estimate the water footprint for livestock products; beef cattle, swine, and broiler chicken. The water footprint for livestock products is divided into direct and indirect water. The direct water includes the drinking and servicing water, and the indirect water includes the water for the cultivation of feed crops. The water footprint of beef cattle was calculated to $17,023.1m^3/ton$, and direct water was $91.2m^3/ton$, and indirect water was $16,931.9m^3/ton$. The water footprint of swine was calculated to $4,235.8m^3/ton$, and direct water was $129.7m^3/ton$, and indirect water was $4,106.0m^3/ton$. The water footprint of broiler chicken was calculated to $2,427.7m^3/ton$, and direct water was $7.6m^3/ton$, and indirect water was $2,420.1m^3/ton$. Also, we compared the water footprint to water demand of water vision 2020 which is the main report for national water management. The water vision 2020 reported only direct water for live animal, but the water footprint includes the direct and indirect water. Therefore, the water footprint could be applied to various fields relating water and food.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.183-195
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• 2016

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.