• English & American cultural studies
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• v.18 no.3
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• pp.65-92
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• 2018

According to Wenying Xu, Asian American literature abounds in culinary metaphors and references (8); subsequently, a growing number of critics have begun to recognize that food "feeds into the literary rendering of Asian American subjectivity [and] provides a language through which to imagine Asian alterity in the American imagination" (Mannur 13). Ann Mah's Kitchen Chinese: A Novel about Food, Family, and Finding Yourself (2010) is yet another text within which to investigate how food "operates as one of the key cultural signs that structure people's identities" (Xu 2). Even as Kitchen Chinese insists on underscoring that Chinese food, as much as the voyage to her "motherland" China, is critical to protagonist Isabelle's quest to gain a better understanding of herself, we are able to observe how Isabelle exploits Chinese culture and its foodways as "food pornography" in order to align herself with mainstream America. Needless to say, the novels' relegation of Chinese food as "food porn" is problematic in that it encourages readers to participate in the exoticization of Asia and its culture, and the reduction of its people as the other. Ultimately, this essay aims to consider how the consumption and rejection of food becomes a critical means by which the Asian American subject fashions her identity.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• SUVANNABHUMI
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• v.15 no.2
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• pp.23-55
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• 2023

Just as globalization has many aspects and has developed in various, sometimes contradictory ways with both positive and negative impacts, so too would the reverse process of deglobalization have wide-ranging effects for individuals, communities, and nations. Some parts of globalization began to fray during the coronavirus pandemic (e.g. failing supply chains and disarray in the global shipping industry). Deglobalization would bring about much more significant changes in focusing on local production and consumption, eschewing non-essential flights and international tourism, and replacing personal experience with virtual presence. These impacts would be particularly severe for Vietnam, since its government has placed intensive connectivity with global production at the center of its model for the rapid development on which much of its legitimacy rests and it has joined as many international, multilateral organizations, and protocols as it has been able to do. Through critical analysis of secondary data from a wide range of sources, this paper examines the motivations that people, institutions, and governments might have to pursue deglobalization and then seeks evidence for whether the changes that would bring have started to affect Vietnam. While it is difficult to be too certain about this while the pandemic continues, it is evident that pressures are building in the global north to reconfigure supply chains for greater security, to reduce carbon emissions through regulating long-distance exchanges, and to withdraw from personal contacts. It is argued that a focus on digitalization in economy and society will help to mitigate the negative effects of deglobalization on Vietnam, at least in the medium-term.

• Journal of Fashion Business
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• v.27 no.5
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• pp.78-92
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• 2023

Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1022-1027
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• 2003

The Motion controllers provide the sophisticated performance and enhanced capabilities we can see in the movements of robotic systems. Several types of motion controllers are available, some based on the kind of overall control system in use. PLC (Programmable Logic Controller)-based motion controllers still predominate. The many peoples use MCU (Micro Controller Unit)-based board level motion controllers and will continue to in the near-term future. These motion controllers control a variety motor system like robotic systems. Generally, They consist of large and complex circuits. PLC-based motion controller consists of high performance PLC, development tool, and application specific software. It can be cause to generate several problems that are large size and space, much cabling, and additional high coasts. MCU-based motion controller consists of memories like ROM and RAM, I/O interface ports, and decoder in order to operate MCU. Additionally, it needs DPRAM to communicate with host PC, counter to get position information of motor by using encoder signal, additional circuits to control servo, and application specific software to generate a various velocity profiles. It can be causes to generate several problems that are overall system complexity, large size and space, much cabling, large power consumption and additional high costs. Also, it needs much times to calculate velocity profile because of generating by software method and don't generate various velocity profiles like arbitrary velocity profile. Therefore, It is hard to generate expected various velocity profiles. And further, to embed real-time OS (Operating System) is considered for more reliable motion control. In this paper, the structure of chip-based precision motion controller is proposed to solve above-mentioned problems of control systems. This proposed motion controller is designed with a FPGA (Field Programmable Gate Arrays) by using the VHDL (Very high speed integrated circuit Hardware Description Language) and Handel-C that is program language for deign hardware. This motion controller consists of Velocity Profile Generator (VPG) part to generate expected various velocity profiles, PCI Interface part to communicate with host PC, Feedback Counter part to get position information by using encoder signal, Clock Generator to generate expected various clock signal, Controller part to control position of motor with generated velocity profile and position information, and Data Converter part to convert and transmit compatible data to D/A converter.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.2897-2901
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• 2013

Gastric cancer is the second most common cause of cancer-related deaths in the world. Although certain dietary factors and lifestyles have been suggested to be associated with gastric carcinogenesis, there have been few investigations focusing on rural areas. A case-control study was therefore carried out to investigate the risk factors of gastric cardia cancer (GCC) in rural areas of Linzhou. A total of 470 newly diagnosed cases of GCC and 470 healthy controls were included. Face-to-face interviews were conducted, using a uniform questionnaire containing questions on demographics, per capita income, living habits, dietary habits and family history of tumors. The relationship between putative risk factors and GCC was assessed by odds ratios (OR) and their 95% confidence intervals (95%CI) derived from conditional logistic regression model by the COXREG command using SPSS 12.00. Multivariate logistic regression analysis was used to evaluate simultaneously the effects of multiple factors and other potential confounding factors. Multivariate logistic analysis showed that smoking (OR=1.939, 95%CI:1.097-3.426), alcohol drinking (OR=2.360, 95%CI: 1.292-4.311), hot food consumption (OR=2.034, 95%CI: 1.507-2.745), fast eating (OR=1.616, 95%CI: 1.171-2.230), mouldy food (OR=4.564, 95%CI: 2.682-7.767), leftover food (OR=1.881. 95%CI: 1.324-2.671), and family history of tumor (OR=2.831, 95%CI: 1.588-5.050) were risk factors for GCC. High per capita income (OR=0.709, 95%CI: 0.533-0.942), high education level (OR=0.354, 95%CI: 0.163-0.765), consumption of fresh fruits (OR=0.186, 95%CI: 0.111-0.311) and vegetables (OR=0.243, 95%CI: 0.142-0.415), and high BMI (OR=0.367, 95%CI: 0.242-0.557) were protective factors for GCC. Our data indicate that unhealthy lifestyle and dietary habits might be important contributors to GCC in this population.

• Journal of the Korean Electrochemical Society
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• v.8 no.4
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• pp.149-154
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• 2005

Fuel cell performance evaluation logic was developed using G-language (LabVIEW) to measure performance stability. Degree of stability and reliability of performance data were improved with averaged value and standard deviation method. Water injection system was introduced and the performance using this method was comparable to that of conventional humidification method. Water injection system has advantage of lowering operation energy consumption, reducing the number of parts needed in humidification, therefore increasing efficiency of fuel cell system. Fuel cell performance was decreased in case of low temperature operation such as sub freezing condition. Air purge method was tested to reduce the water content in cell fixture before sub freezing condition. The performance degradation due to low temperature operation was minimized by air purge method in medium size cell fixture ($25cm^2$) case.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.53-58
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• 2008

This paper designs sigma-delta D/A Converter with a high resolution and low power consumption. It reorganizes the input data along LJ, RJ, I2S mode and bit mode to the output data of A/D converter. The D/A converter decodes the original analog signal through HBF, Hold and 5th CIFB(Cascaded Integrators with distributed Feedback as well as distributed input coupling) sigma-delta modulation blocks. It uses repeatedly the addition operation in instead of the multiply operation for the chip area and the performance. Also, the half band filters of similar architecture composed the one block and it used the sample-hold block instead of the sinc filter. We supposed simple D/A Converter decreased in area. The filters of the block analyzed using the matlab tool. The top block designed using the top-down method by verilog language. The designed block is fabricated using Samsung 0.35um CMOS standard cell library. The chip area is 1500*1500um.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.98-106
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• 2013

The duty-cycle synchronization among mobile sensor nodes with energy-harvesting is very important. The nodes should keep their duty-cycle same to others as much as possible because they have to cooperate each other and to consume energy efficiently. The distribution of node position in network affects not only node connectivity but also the active time of synchronized nodes, and it relates to network life-time finally. In this paper, we introduce a network topology change algorithm (TCA) for energy-harvesting mobile sensor networks based on self-synchronized duty-cycling. The algorithm tries to change a network topology into a balanced topology where the mobile sensor nodes are unified according to the density of the number of nodes. For TCA, both fluid flow algorithm and flock dispersion algorithm are proposed and they are evaluated through the simulation in agent based modeling language. TCA is applied to the energy-harvesting mobile sensor networks to improve the synchronization of duty-cycle and to reduce the variation of energy consumption among nodes.