• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.1
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• pp.172-191
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• 2024

This study investigated how the visual and verbal presentation format of haptic information on apparel products in online stores affects consumers' imagery information processing. This includes the quantity and vividness of mental imagery, the ease of evoking mental imagery, and the evocation of imagination imagery. Additionally, the study explored consumer satisfaction with the information and online store. The study also tested a conceptual model to examine the effects of three imagery types on imagination imagery (as elaborated imagery) and how this imagination imagery affects consumer satisfaction. Employing a 2 × 3 × 2 between-subjects factorial design, twelve one-page websites were created for the experiment. 528 women in their 20s and 30s were randomly assigned to one of the 12 treatment conditions and answered the questionnaire. The results demonstrated significant differences in the three types of mental imagery, consumers' evocation of imagination imagery, and their satisfaction with information and online stores based on presentation format. The SEM analysis revealed that the quantity and vividness of mental imagery influenced the evocation of imagination imagery, affecting consumers' satisfaction with the information. These findings suggest that online retailers must provide close-up pictures or descriptive text of apparel products to elicit positive consumer responses.

• Journal of the Korean Chemical Society
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• v.55 no.5
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• pp.846-856
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• 2011

In this study, we analyzed the characteristics of imagery thinking in the processes of generating analogy of seventh grade science-gifted students in terms of the information-processing of imagery. The analyses of the results revealed that science-gifted students' information-processing of imagery in the processes of generating analogy consisted of image generation, image operation, and image representation. The types of imagery used by science-gifted students were classified into perception imagery, memory imagery, and imagination imagery, and there were some differences in the patterns of information-processing of imagery. In the bases of these results, we suggested the information-processing model of imagery by the types of imagery used in generating analogy. The results of this study may provide useful implication to develop effective methods for a strategy of generating analogy emphasizing the interaction between analogy thinking and imagery thinking which promotes imagery thinking of science-gifted students.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.286-289
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• 2005

Recently, in Korea, recognizing the importance of satellite imagery and a national project, the development of satellite providing satellite imagery information of 1m high resolution has been carried out. As the application of satellite. imagery information is expanded to the national land, the environment and geographical information, etc, the necessity of integrated management of satellite imagery information increases. Unfortunately, in case of Korea, currently, the results that institutes for satellite imagery processing produce with satellite imagery have been individually managed. Integrated Management of Satellite Imagery Information project which is being promoted by ETRI (Electronics and Telecommunication Research Institute) in Korea will provide the solutions for the above mentioned problems. In this research work, we designed standard metadata for integrated management of satellite imagery information in consideration of international and national standard.

• Asia Marketing Journal
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• v.22 no.2
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• pp.59-85
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• 2020

Combining prior theories on innovation newness with information processing style (imagery vs. analytical), this study presents a theoretical framework; develops hypotheses; and makes predictions on how analytical versus imagery ads influence consumers differently depending on the newness level of products. The study shows that consumers are more likely to evaluate RNPs (radically-innovative new products) positively when they are advertised with imagery cues. Compared with analytical advertisements, imagery advertisements increased advertising effectiveness, product evaluation, and purchase intention of RNPs. These effects were demonstrated by using stimuli from two product categories consisting of washing machines and cars. In particular, in advertisement for RNPs, verbal description that induced imagery processing, such as "picture yourself using this product," was more effective in generating favorable responses, compared to verbal description that induced analytical processing, such as explanation of product attributes. This difference was present for RNPs, but not for INPs (incrementally-innovative new products). INPs are continuous innovations that are easier to understand, thus imagery ads do not provide additional advantage for consumers in understanding the innovation, compared to analytical ads. In RNPs, imagery ads can highlight new benefits that may have been neglected or undervalued by consumers, leading to greater message persuasiveness. Implications for marketing of RNPs are discussed.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.442-457
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• 2024

The issues were studied of an open-source scaling drone imagery platform, called WebODM. It is known that processing drone images has a high demand for resources because of many preprocessing and post-processing steps involved in image loading, orthophoto, georeferencing, texturing, meshing, and other procedures. By default, WebODM allocates one node for processing. We explored methods to expand the platform's capability to handle many processing requests, which should be beneficial to platform designers. Our primary objective was to enhance WebODM's performance to support concurrent users through the use of container technology. We modified the original process to scale the task vertically and horizontally utilizing the Kubernetes cluster. The effectiveness of the scaling approaches enabled handling more concurrent users. The response time per active thread and the number of responses per second were measured. Compared to the original WebODM, our modified version sometimes had a longer response time by 1.9%. Nonetheless, the processing throughput was improved by up to 101% over the original WebODM's with some differences in the drone image processing results. Finally, we discussed the integration with the infrastructure as code to automate the scaling is discussed.

• Science of Emotion and Sensibility
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• v.8 no.3
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• pp.177-187
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• 2005

This article examined how the amount of information presented in ad design affect consumer's evaluation on the ad Existing researches have mainly considered external information presented in the ad from the resource principle perspective. This study investigated how internal information processing such as imagery information processing caused by brand names moderates persuasion effects according to the amount of external information through two experiments. The experiments leave us the conclusion that brand names presented in the ads stimulate imagery information processing when surplus cognitive resources do exist and they lead ad recipients' evaluation to positive direction in prestige brand condition and to the contrary to negative direction in non-prestige brand condition. The results contribute to the direction of ad design in that ad needs not contain as muck product-related information as needed in order to increase persuasion effects in prestige brand condition. Rather, it's necessary to leave the room for internal information processing such as imagery information processing by well structured brand equity. On the contrary, non-prestige brand needs to contain explicit product-relevant information to exert a potent influence on a4 persuasion. We hope this study result is helpful for design direction of advertisement in order to heighten persuasion effects toward ad recipients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3917-3941
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• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1131-1133
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• 2003

Spatial image processing software requires various user interactions to make a plan, prepare necessary data such as images, vectors, ancillary data and user-defined data, execute functions according to pre-defined procedures, analyze and store the results. In this manner, overall processes are controlled by user interactions. In this paper, we propose visual modeler which has the automated spatial image processing technique to minimize user interactions and re -use repeatable procedure. The proposed visual modeler is designed to use inter-operable components proposed by OpenGIS consortium as well as conventional COM components.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.775-779
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• 2002

Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.