As the world approaches to a keen competition for design, corporations began to be interested in CI (Corporate Identity), PI (Product Identity) as a way of enhancing the valve of corporation that has competitive power. PI (Product Identity) leads communication to an affirmative direction that is formed when the consumer uses products and feels the image of corporation. It is said to be important that it is part of synthetic and systematic strategy of corporation to gain an advantage over competitor in the market place with an unified corporate image. Even though mobile phones are sensitively changed according to a trend and public fancy, PI (Product Identity) of mobile phones is also important. The study purports to ascertain the propensity of Nokia's PI (Product Identity) and to analyze their unique PI.
The purpose of this study is examining an influence of a corporate on processed marine product's purchase intention with moderating effect of consumers' product evaluation adding processed marine product's evaluations as new variable. The hypothesis of a positive influence of processed marine product's corporate image on processed marine product's purchase intension is partially supported. Specifically, product itself, service, reliability, and communication among the factors of a processed marine product's corporate image significantly affect processed marine product's purchase intension whereas corporate social responsibility does not affect processed marine product's purchase intention. Processed marine product's evaluation also positively affects processed marine product's purchase intention. It implies that there are somewhat differences between influences of various factors of a processed marine product's corporate image on processed marine product's purchase intention but are overall influences of a processed marine product's corporate image on processed marine product's evaluation both directly and indirectly. Nowadays, consumer considers not only good quality of product but also its invisible image and value. Therefore, future studies should consider various ways to investigate a processed marine product's corporate image and processed marine product's product evaluation.
The current tariff return system requires tax officials to calculate tax amount by themselves and pay the tax amount on their own responsibility. In other words, in principle, the duty and responsibility of reporting payment system are imposed only on the taxee who is required to calculate and pay the tax accurately. In case the tax payment system fails to fulfill the duty and responsibility, the additional tax is imposed on the taxee by collecting the tax shortfall and imposing the tax deduction on For this reason, item classifications, together with tariff assessments, are the most difficult and could pose a significant risk to entities if they are misclassified. For this reason, import reports are consigned to customs officials, who are customs experts, while paying a substantial fee. The purpose of this study is to classify HS items to be reported upon import declaration and to indicate HS codes to be recorded on import declaration. HS items were classified using the attached image in the case of item classification based on the case of the classification of items by the Korea Customs Service for classification of HS items. For image classification, CNN was used as a deep learning algorithm commonly used for image recognition and Vgg16, Vgg19, ResNet50 and Inception-V3 models were used among CNN models. To improve classification accuracy, two datasets were created. Dataset1 selected five types with the most HS code images, and Dataset2 was tested by dividing them into five types with 87 Chapter, the most among HS code 2 units. The classification accuracy was highest when HS item classification was performed by learning with dual database2, the corresponding model was Inception-V3, and the ResNet50 had the lowest classification accuracy. The study identified the possibility of HS item classification based on the first item image registered in the item classification determination case, and the second point of this study is that HS item classification, which has not been attempted before, was attempted through the CNN model.
Corporate design activities have expanded from being exclusive and passive responsibilities to active participation in planning, marketing, technology and corporate brand image differentiation for successful business. Thus the communications between designers and other functions come to include critical decision making, information sharing, and objective reasoning. Given that design activities now have to involve various functions in product development, the styling-related design process, which is still developed by designer's intuition and experience, poses as an obstacle not just between various functions involved, but even within the design function. To overcome this obstacle and to lead more effective design decision process, a means for product form development assessment and management is necessary. This research proposes a foundation for managing and assessing product form based on the hypothesis and demonstration of discovering a system of formative factor and order a product form expresses that can be shared as an objective and logical system. As a result of this demonstration, the form as a unique visual expression and the factors related to the form and its co-relationship are examined. The factors are called formative parameters and the system is named as the product form alignment method. Based on the logic derived from the system, the process for developing an image that aligns with the predefined goal is explained. The method defines a balance between a designer's intuitive creativity and the extracted logic, which can act as a basis for designers to share design language among themselves and for communication between design and other functions. Based on this system, designers are able to align design work with the set goal, and focus and limit the range of form development, which is anticipated to result in lead-time reduction and minimizing unnecessary obstacles and mistakes.
Along with the spotlight of storytelling, storydoing has attracted public's attention as it has been utilized in various different areas. There are valued message by producer and story to back it up in the storydoing. Recipient will acknowledge the affordance encouraged by producer and confirm the message by practicing it. Finally producer will evaluate the practice process. Therefore, storydoing promotes the product of company, strengthens the brand image and delivers message and value through a previously mentioned cycle. Ultimately, storydoing is operated based on user's experience. In this study, based on the experience theory of John Dewey, in order to discover how the interactivity and continuity operate story doing, we conducted a study on the concept of storydoing, the national and international story doing status, the difference between storytelling and storydoing, the elements of story doing, the relationship with user experience, and the principle of operating story doing. As a result, we learned that story doing had the five elements of message, story, characters, action, and confirmation, and operated by the interaction and continuity between the producer and receptor. Thus, through this research to understand the nature of storydoing, we have identified new trends of the cultural industries and discovered the possibilities to expand the application scope of storydoing, which was currently applied by companies to promote their brand images, onto contents field. More importantly, the proposal of theoretical differences between storytelling and storydoing makes this report meaningful in terms of sociocultural, industrial and academic aspect.
Suho Bak;Seon Woong Jang;Heung-Min Kim;Tak-Young Kim;Geon Hui Ye
Korean Journal of Remote Sensing
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v.39
no.2
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pp.193-205
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2023
A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.6
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pp.1-14
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2018
As interest and consumption of luxury goods have become more popular, luxury goods market is growing rapidly. Consumers can acquire psychological satisfaction with material abundance by purchasing and using luxury goods. Also, from the view of corporations, luxury goods have price inelastic characteristics, so they can enjoy price premium and it is good to produce good performance. That is the reason why they should pay much attention to securing luxuriousness. This study examined the establishment of brands luxuriousness in Korean SMEs. First, it examined the world market of luxury goods industry and the present condition of Korean market. Then it identified the constituents of luxuriousness by examining the prior studies and related literatures, and designed a research model based on the theoretical grounds to suggest the methods of brand luxuriousness building of Korean SMEs. Luxuriousness can be defined as the attribute of product that distinguishes luxury goods from other products by consumers' perceptions, and the factor that provides situational benefits that motivate consumers' purchasing behavior. In this study, I identified the sub-dimensions of luxuriousness according to whether there are product related attributes and consumers' benefit in consideration of the problems of existing studies. Product related luxuriousness are classified into superiority(functional benefit) and scarcity(experiential benefit), while non-product related luxuriousness are classified into differentiation(symbolic benefit) and traditionality(exclusive benefit). The following are the ways to build brand luxuriousness. First, company can use product factors. High quality, excellent design, high recognized brand with strong, favorable and unique images can enhance the luxuriousness of brand. Second, company can use price factors. Consumers tend to perceive luxury goods as high-priced items, so lowering the price of product can undermine the luxuriousness of product. Third, company can use distribution factors. It is effective for making consumers to perceive the differentiation and scarcity of luxuriousness through limited distribution channel. In addition, store atmosphere suitable for luxury brands should be created. Fourth, company can use promotion factors. The more consumers are exposed to advertisements, the more positive attitudes toward luxury brands are made, and consumers recognize luxuriousness higher. Price promotion negatively affects consumers' perception of luxuriousness. Fifth, company can use corporate factors. Consumer evaluations of products are influenced not only by the product attributes but also by the corporate association and corporate image surrounding the product. Considering the existing researches, it is possible to enhance the brand luxuriousness through high corporate competence and good corporate reputation. In order to increase the competence of the enterprise, it is useful to approach multidimensionally in relation with the knowledge creation capability. In corporate reputation, the external stakeholders' reputation is important, but the internal members' reputation is also important. Korean SMEs will be able to build brand luxuriousness by establishing marketing strategies as above and/or mix(integrate) them according to the situation.
IT investment is usually very costly and takes a long time to get the results out of investment. However, most of currently available evaluation methods for IT investment are based upon short-term effects, hence their results are not fully trustworthy. In addition, those methods commonly consider only financial aspects such as ROI. For more reliable evaluation, it is necessary to consider non-financial factors such as system utilization, customer satisfaction, public relations, and so on, as well as financial factors. In this research, we propose an evaluation method that can evaluate both financial and non-financial aspects on a long-term base. For this purpose, we employed the research results developed in System dynamics and Balanced scorecard. System dynamics is useful in analyzing long term behavior of a given system, and Balanced scorecard is useful for evaluating both financial and non-financial aspects. We demonstrated the usefulness of our method by applying it to the evaluation of RFID (Radio Frequency Identification) investment in a distribution and retail industry. From this application, we found that RFID investment may not be rewarding in the short term, but is sure to be returning the income relative to its investment in the long run.
Suho Bak;Heung-Min Kim;Tak-Young Kim;Jae-Young Lim;Seon Woong Jang
Korean Journal of Remote Sensing
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v.39
no.3
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pp.297-309
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2023
The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.19
no.1
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pp.161-170
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2019
Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.
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